Dunarea de Jos University of Galati (UDJG) [600667]

“Dunarea de Jos” University of Galati (UDJG)
Faculty of Engineering – Department of Manufacturing Engineering

“M’Hamed Bougara ” University of Boumerdes (UMBB)
Faculty of Engineering Sciences – Department of Mechanical Engineering

Maintenance of Flexible Manufacturing
Systems using Petri Nets Modeling

Master student: [anonimizat]:
Prof. Djamal BENAZZOUZ (UMBB)
Prof. Gabriel FRUMUSANU (UDJG)
Prof. Vasi le MARINESCU (UDJG)

Galati – 2019

This work was supported by Erasmus+ Programme, KA2 Capacity Building in Higher Education, project no. 586035 -EPP-1-
2017 -1-DZ-EPPKA2 -CBHE -JP, entitled Algerian National Laboratory for Maintenance Education – ANL Med.

ANL -MEd
II ANL -MED
ANL -MEd assembles for 36 months a consortium with 14 partners with unique
combination of skills and expertise. The consortium, coordinated by USTHB, h as a hierarchical
structure that ensures an efficient communication and cooperation. Four European universities
with solid competence in maintenance engineering and management will contribute to
development of teaching material and training students, teach er, trainers and industry staff. This
will contribute to strengthening the active cooperation between university and industry, as well
between Algeria and EU. The project activities are distributed in 7 work packages according to
a detailed work plan that adequately structures the efforts into manageable work packages with
clear responsibilities and objectives. For improved effectiveness in the project for organization
of implementation, the partners are grouped in three clusters: ANL -EDUC – cluster for
education, ANL -VET – cluster for vocational education and training and ANL -ORG for
organization of the ANL, coordinating the resources for integration, communication and
exploitation. The goal of the ANL -MEd is to provide Algerian industry with a new generati on
of skilled personnel, especially at mid – and higher levels, along with ensuring flexible and
continuing education and training of industry personnel at all levels. Flexibility is necessary to
adapt and update the knowledge according to the day -to-day pr ogress of science and
technology. The partners in the project have been selected above all to suit to the genuine
structure of Algerian academia and industry and to align it to a modern and dynamic European
standard. The reference line is represented by th e two main characteristics of the Algerian
industry
Relative low productivity determined especially by the lacking knowledge in
modern manufacturing technology, maintenance and asset integrity.
Few large companies and many SMEs with very small resources fo r internal
development.

Acknowledgements
III ACKNOWLEDGEMENTS
I can’t begin this report without thinking of all who contributed, near or far to this
work I thank first God who alone guided us in the direction during our lives and helps us to
achieve this modest work.
First, I would to thank my parents, they do the impossibl e just for me and for the
education they taught, also my brothers and my sister for the support.
I would like to express my deep gratitude to all those who participated in the
development of this work and in particular Prof. Smail A DJERID and Prof. Viorel PAUNOIU
and I would like to thank him for his welcome and h is help while I arrived in Galati and in
their University .
I would especially like to thank my supervisors Professor Djamel BENAZZOUZ from
UMBB, Vasile MARINESCU and Gabriel FRUMUSANU from UDJG for allowing me to
carry out this work and for their help and availability.
I also associate all members of the University “Dunarea de Jos of Galati” and for their
welcome and availability also the Universit y “ M’hamed Bougara of Boumerdes”.
I do not forget the ERASMUS group, Algerian National Laboratory for Maintenance
Education and European Union who allowed us to do this project in Romania.
I thank the URB group for their help and their valuable advice tha t guided me
throughout my internship.
Finally, I sincerely like to thank all my colleagues from Annaba and Boumerdes who
shared with me this internship period and this experience and for supporting me .
This work was supported by a grant of the European Commission thought Erasmus +
program, code 586035 -EPP-1-2017 -1-DZ-EPPKA2 -CBHE -JP. The information and views set
out in this publication are those of the authors and do not necessarily reflect the official
opinion of the European Union. Neither the European Union institutions and bodies nor any
person acting on their behalf may be held responsible for the use which may be made of the
information contained therein.

Abstract
IV ABSTRACT
This paper presents a production manufacturing system model based on Petri N ets. In
this work we are interested to studying the performance evaluation of the flexible
manufacturing system (FMS) using Petri nets which are a powerful tool in modeling production
systems. The studied model is a real production system from (Berlad URB groupe -Romania).
The FMS type where we have considered various ratios to job to increase the complexity, like
shared machines. The performance analysis of this FMS is based on these parameters
scheduling routings, machines availability and insufficiency. T he Petri net reacts to detected
errors by changing the control flow of tokens in the Petri net during the operation of the system.
The modeling and simulation allow to determine the FMS productivity, these parameters are
important for the political choice strategy of reparation (maintenance) by switching defective
machines with similar machines in the same system . We show the flexibility and simplicity of
our modeling approach.
A case study of a manufacturing system is presented, the obtained results of sim ulation
allows us to identify the best scheduling in the considered case, this scheduling will provide an
optimal objective between production and maintenance of the manufacturing system.
Keywords:
Flexible manufacturing systems – Petri nets – Modeling – Maintenance

Resumé
V RESUME
Ce document présente un modèle de système de fabrication basé sur les réseaux de Petri.
Dans ce travail, nous intéressons à l’évaluation de la performance du système flexible de
production (FMS) à l’aide des réseaux de Petri, qui constit uent un puissant outil de modélisation
des systèmes de production. Le modèle étudié est un véritable système de production de (Berlad
URB groupe -Romania). Le type FMS où nous avons envisagé divers ratios d’emploi pour
augmenter la complexité, comme des mac hines partagées. L'analyse des performances de ce
FMS est basée sur ces paramètres : ordonnancement des routages, disponibilité et insuffisance
des machines. Le réseau de Petri réagit aux erreurs détectées en modifiant le flux de contrôle
des jetons dans l e réseau de Petri pendant le fonctionnement du système. La modélisation et la
simulation permettent de déterminer la productivité de système , ces paramètres sont importants
pour le choix politique de la stratégie de réparation (maintenance) en commutant des machines
défectueuses avec des machines similaires dans le même système . Nous montrons la flexibilité
et la simplicité de notre approche de modélisation.
Une étude de cas d’un système de fabrication est présentée, les résultats obtenus de la
simulation nous permettent d’identifier le meilleur ordonnancement dans le cas considéré. Cet
ordonnancement fournira un objectif optimal entre la production et la maintenance du système
de fabrication.
Les mots clés :
Systèmes de fabrication flexibles – Réseaux de Petri – Modélisation – Maintenance

Table of Contents
VI TABLE OF CONTENTS
ANL -MEd ………………………….. ………………………….. ………………………….. ………………… II
Acknowledgements ………………………….. ………………………….. ………………………….. …..III
Abstract ………………………….. ………………………….. ………………………….. ………………….. IV
Resumé ………………………….. ………………………….. ………………………….. …………………….. V
Table of Contents ………………………….. ………………………….. ………………………….. …….. VI
List of figures ………………………….. ………………………….. ………………………….. …………… X
List of tables ………………………….. ………………………….. ………………………….. ………….. XII
Introduction ………………………….. ………………………….. ………………………….. ……………… 1
Chapter I: Presentation of the working environment ………………………….. …………… 4
I.1. Introduction ………………………….. ………………………….. ………………………….. ………. 4
I.2. General pre sentation of the University “Dunarea de Jos” of Galati ……………….. 4
I.3. General presentation of URB Group – Rulmenti S.A Barlad ………………………… 7
Chapter II Generality on Petri nets ………………………….. ………………………….. ………. 14
II.1. Introduction ………………………….. ………………………….. ………………………….. ……. 14
II.2. Definition ………………………….. ………………………….. ………………………….. ………. 15
II.2.1. Formal definition ………………………….. ………………………….. ………………….. 16
II.3. Ba sic design and definitions ………………………….. ………………………….. …………. 17
II.3.1. Concept of marking ………………………….. ………………………….. ………………. 17
II.3.2. Incidence matrix ………………………….. ………………………….. …………………… 17
II.3.3. Awareness Rule ………………………….. ………………………….. ……………………. 18
II.3.4. Fi ring of a Transition ………………………….. ………………………….. …………….. 19
II.4. Petri nets properties ………………………….. ………………………….. …………………….. 20
II.4.1. Vivacity ………………………….. ………………………….. ………………………….. …… 20
II.4.2. Consistency and reversibility ………………………….. ………………………….. ….. 20
II.4.3. Persistence ………………………….. ………………………….. ………………………….. . 20
II.4.4. Structural and effective conflict ………………………….. ………………………….. . 21
II.4.4.1. Structural conflict ………………………….. ………………………….. …………… 21
II.4.4.2. Effective conflict ………………………….. ………………………….. …………….. 21
II.4.5. Mutual exclusion ………………………….. ………………………….. …………………… 21
II.4.6. Blocking ………………………….. ………………………….. ………………………….. ….. 21
II.4.7. Modeling competition ………………………….. ………………………….. ……………. 21
II.4.8. Confusion ………………………….. ………………………….. ………………………….. … 22

Table of Contents
VII II.4.9. Producer and consumer ………………………….. ………………………….. ………….. 23
II.5. Petri net’s modeling ………………………….. ………………………….. …………………….. 23
II.5.1. Synchronization ………………………….. ………………………….. ……………………. 23
II.5.2. Parallelism ………………………….. ………………………….. ………………………….. . 24
II.6. Particular petri nets ………………………….. ………………………….. ……………………… 24
II.6.1. Stat graph ………………………….. ………………………….. ………………………….. … 24
II.6.2. Event graph ………………………….. ………………………….. ………………………….. 24
II.6.3. Free choice ………………………….. ………………………….. ………………………….. . 25
II.6.4. Pure PN ………………………….. ………………………….. ………………………….. …… 25
II.6.5. Simple PN ………………………….. ………………………….. ………………………….. .. 26
II.7. Modeling a system ………………………….. ………………………….. ………………………. 26
II.8. High level petri nets ………………………….. ………………………….. …………………….. 28
II.7.1. Timed Petri nets ………………………….. ………………………….. ……………………. 28
II.7.1.1. Definition ………………………….. ………………………….. ………………………. 29
II.7.1.2. Fo rmal definition ………………………….. ………………………….. ……………. 29
II.7.1.3. State of TPN ………………………….. ………………………….. …………………… 29
II.8. Augmentation Methods of Petri Nets ………………………….. …………………………. 29
II.8.1. Input Conditioning Method ………………………….. ………………………….. ……. 30
II.8.2. Alternate Path Method ………………………….. ………………………….. …………… 30
II.8.3. Backward Error Recovery Method ………………………….. ………………………. 30
II.8.4. Forward Error Recovery Method ………………………….. …………………………. 30
II.8.5. Maintainability of behavioral Properties ………………………….. ………………. 30
II.9. Conclusion ………………………….. ………………………….. ………………………….. …….. 32
Chapter III: FLE XIBLE MANUFACURING SYSTEMS ………………………….. ….. 34
III.1. INTRODUCTION ………………………….. ………………………….. ……………………… 34
III.2. Definition ………………………….. ………………………….. ………………………….. ……… 35
III.2.1. Manufac turing systems ………………………….. ………………………….. …………. 35
III.3. Production modes ………………………….. ………………………….. ………………………. 35
III.3.1. Continuous production ………………………….. ………………………….. …………. 35
III.3.2. Discrete production ………………………….. ………………………….. ……………… 36
III.3.3. Comparison between continuous production and discrete production ….. 36
III.4. Flexibility ………………………….. ………………………….. ………………………….. …….. 37
III.5. Flexibility in a production system ………………………….. ………………………….. … 37

Table of Contents
VIII III.5.1. Basic flexibility ………………………….. ………………………….. …………………… 37
III.5. 1.1. Flexibility of machines ………………………….. ………………………….. …… 37
III.5.1.2. Flexibility of handling tools ………………………….. ………………………… 37
III.5.1.3. Flexibility of operations ………………………….. ………………………….. …. 37
III.5.2. System flexibilities ………………………….. ………………………….. ………………. 38
III.5.2.1. Flexibility of manufacturing processes ………………………….. …………. 38
III.5.2.2. Product flexibility ………………………….. ………………………….. ………….. 38
III.5.2.3. Flexibility of product routing ………………………….. ………………………. 38
III.5.2.4. Flexibility of product volumes ………………………….. …………………….. 38
III.5.2.5. Expansion flexibility ………………………….. ………………………….. ……… 38
III.5.3. Aggregate flexibilities ………………………….. ………………………….. ………….. 39
III.5.3.1. Flexibility of control programs ………………………….. …………………….. 39
III.5.3.2. Flexibility of production ………………………….. ………………………….. …. 39
III.5.3.3. Market flexibility ………………………….. ………………………….. …………… 39
III.6. Flexible manufacturing systems ………………………….. ………………………….. …… 39
III.7. Different types of FMS ………………………….. ………………………….. ……………….. 40
III.7.1. Flexible module: (FM) ………………………….. ………………………….. …………. 40
III.7.2. Flexible cell: (FC) ………………………….. ………………………….. ………………… 40
III.7.3. Flexible group: (FG) ………………………….. ………………………….. …………….. 40
III.7.4. Flexible system: (FS) ………………………….. ………………………….. ……………. 40
III.7.5. Flexible line : (FL) ………………………….. ………………………….. ……………….. 40
III.8. Area of application of FMS in industry ………………………….. ……………………… 41
III.9. Component of a FMS ………………………….. ………………………….. …………………. 42
III.9.1. Workshops ………………………….. ………………………….. ………………………….. 42
III.9.1.1. Flo w-shop ………………………….. ………………………….. …………………….. 42
III.9.1.2. Job -shop ………………………….. ………………………….. ……………………….. 43
III.9.1.3. Open -shop ………………………….. ………………………….. …………………….. 43
III.10. Problems in a flexible manufacturing system ………………………….. …………… 43
III.10.1. FMS design problems ………………………….. ………………………….. …………. 43
III.10.2. FMS planning problems ………………………….. ………………………….. ……… 43
III.10.3. FMS scheduling problems ………………………….. ………………………….. …… 44
III.10.4. FMS control problems ………………………….. ………………………….. ………… 44
III.11. Solution of FMS Problems: ………………………….. ………………………….. ……….. 44

Table of Contents
IX III.12. Modeling of production systems ………………………….. ………………………….. … 44
III.12.1. Objectives of modeling a production system ………………………….. ……… 45
III.13. Petri nets modeling and production systems: ………………………….. ……………. 45
III.14. Conclusion ………………………….. ………………………….. ………………………….. ….. 48
Chapter IV: An alysis and simulation of a real production system …………………… 50
IV.1. Introduction ………………………….. ………………………….. ………………………….. ….. 50
IV.2. Resources ………………………….. ………………………….. ………………………….. …….. 50
IV.3. Shared and u nshared Resource ………………………….. ………………………….. …….. 51
IV.4. Description of the system ………………………….. ………………………….. ……………. 52
IV.5. Operating cycle ………………………….. ………………………….. …………………………. 54
IV.6. Modeling general system ………………………….. ………………………….. ……………. 55
IV.6.1. Workshops modeling ………………………….. ………………………….. ……………….. 55
IV.7. Modeling the system ………………………….. ………………………….. ………………….. 57
IV.7.1. Block 1 ………………………….. ………………………….. ………………………….. ….. 58
IV.7.2. Block 2 ………………………….. ………………………….. ………………………….. ….. 59
IV.7.3. Block 3 ………………………….. ………………………….. ………………………….. ….. 60
IV.7.4. Block 4 ………………………….. ………………………….. ………………………….. ….. 61
IV.7.5. Block 5 ………………………….. ………………………….. ………………………….. ….. 62
IV.4.6. Full system ………………………….. ………………………….. …………………………. 63
IV.5. Tables of places and transitions ………………………….. ………………………….. …… 64
IV.5.1. Significance of places ………………………….. ………………………….. …………… 64
IV.5.2. Significance of transitions ………………………….. ………………………….. …….. 69
IV.6. model validation and Results of the simulation ………………………….. ………….. 73
IV.7. Augmentation of the model ………………………….. ………………………….. …………. 74
IV.8. Conclusion ………………………….. ………………………….. ………………………….. ……. 77
General Conclusi on ………………………….. ………………………….. ………………………….. …. 78
References ………………………….. ………………………….. ………………………….. ………………. 80
Annex 1 ………………………….. ………………………….. ………………………….. …………………… 85
Annex 2 ………………………….. ………………………….. ………………………….. …………………… 87

List of figures
X LIST OF FIGURES
Figure I. 1 Map of Romania ………………………….. ………………………….. …………………….. 4
Figure I. 2 Dunarea de Jos University of Galati ………………………….. ………………………. 5
Figure I. 3 Entrance of the Faculty of Engineering ………………………….. ………………….. 7
Figure I. 4 URB Group ………………………….. ………………………….. ………………………….. .. 8
Figure I. 5 URB Group – Rulmenti S.A. ………………………….. ………………………….. ……. 9
Figure I. 6 Sales regions of URB ………………………….. ………………………….. ……………… 9
Figure I. 7 URB Group Softwares ………………………….. ………………………….. …………… 10
Figure I. 8 DOOSAN bought from south Korea ………………………….. ……………………. 10
Figure I. 9 Tooling workshop ………………………….. ………………………….. …………………. 11
Figu re I. 10 Marking and wrapping machines ………………………….. ………………………. 12

Figure II. 1 The four seasons and their changes ………………………….. …………………….. 14
Figure II. 2 Graphical representation of the elements of petri net ………………………… 15
Figure II. 3 Simple Example ………………………….. ………………………….. ………………….. 16
Figure II. 4 Petri net, not marked and marked models ………………………….. ……………. 17
Figure II. 5 Firing of a transition ………………………….. ………………………….. …………….. 19
Figure II. 6 The composition of water modeled with PN (2H2+O2 = 2H2O) ………… 20
Figure II. 7 Convergence of arcs ………………………….. ………………………….. …………….. 21
Figure II. 8 Divergence of arc s ………………………….. ………………………….. ………………. 22
Figure II. 9 Confusion situations ………………………….. ………………………….. …………….. 22
Figure II. 10 Producer and consumer ………………………….. ………………………….. ………. 23
Figure II. 11 Synchronized operations ………………………….. ………………………….. …….. 23
Figure II. 12 Parallel petri net ………………………….. ………………………….. ………………… 24
Figure II. 13 Stat graph ………………………….. ………………………….. …………………………. 24
Figure I I. 14 Event graph ………………………….. ………………………….. ………………………. 25
Figure II. 15 Pure and impure PN [8], [9] ………………………….. ………………………….. … 25
Figure II. 16 Simple PN ………………………….. ………………………….. ………………………… 26
Figure II. 17 Starting two racing cars example [10] ………………………….. ………………. 26
Figure II. 18 Graphical representation of phases ………………………….. …………………… 27
Figure II. 19 Net of the full system ………………………….. ………………………….. …………. 28
Figure II. 20 Illustrative schema ………………………….. ………………………….. …………….. 28
Figure II. 21 Associated Petri net S* ………………………….. ………………………….. ………. 31

List of figures
XI
Figure III. 1 Different types of FMS between flexibility and productivity ……………. 41
Figure III. 2 Area of applications of FMS in an industry ………………………….. ……….. 41
Figure III. 3 Components and structure of Flexible Manufacturing System ………….. 42

Figure IV. 1 Types of resources example ………………………….. ………………………….. …. 51
Figure IV. 2 Shared and unshared resource ………………………….. ………………………….. 52
Figure IV. 3 The Manufacturing System ………………………….. ………………………….. ….. 54
Figure IV. 4 Modeling of general system ………………………….. ………………………….. …. 55
Figure IV. 5 The output matrix ………………………….. ………………………….. ………………. 56
Figure IV. 6 The input matrix ………………………….. ………………………….. ………………… 56
Figu re IV. 7 The incidence matrix ………………………….. ………………………….. ………….. 56
Figure IV. 8 Oscillogram of evolution state of places ………………………….. ……………. 57
Figure IV. 9 Modeling of block 1 ………………………….. ………………………….. ……………. 58
Figure IV. 10 Modeling of block 2 ………………………….. ………………………….. ………….. 59
Figure IV. 11 Modeling of block 3 ………………………….. ………………………….. ………….. 60
Figure IV. 12 Modeling of block 4 ………………………….. ………………………….. ………….. 61
Figure IV. 13 Modeling of block 5 ………………………….. ………………………….. ………….. 62
Figure IV. 14 Modeling of the full system ………………………….. ………………………….. .. 63
Figure IV. 15 A place with ℇ(p), T(p), and Tmax(P) in a Petri net ……………………….. 74
Figure IV. 16 Change tool of machine R242 ………………………….. ………………………… 75
Figure IV. 17 Switching the resources ………………………….. ………………………….. …….. 76

Figure A1. 1 Software credits ………………………….. ………………………….. …………………. 85
Figure A1. 2 Graphical interface of the software ………………………….. …………………… 86

Figure A2. 1 Turning B1 Data ………………………….. ………………………….. ………………… 87
Figure A2. 2 Grinding of B1 Data ………………………….. ………………………….. …………… 87
Figure A2. 3 Turning of B2 Data ………………………….. ………………………….. ……………. 88
Figure A2. 4 Grinding of B2 Data ………………………….. ………………………….. …………… 88

List of tables
XII LIST OF TABLES
Table II. 1 Petri Nets elements representation ………………………….. ……………………….. 15
Table II. 2 List of conditions and actions ………………………….. ………………………….. …. 27

Table III. 1 The difference between continuous and discrete production ………………. 36
Table III. 2 Components and structure of Flexible Manufacturing System ……………. 47

Table IV. 1 Some machines in the system and their jobs ………………………….. ………… 53
Table IV. 2 State of places ………………………….. ………………………….. ……………………… 57
Table IV. 3 Significance of places P1 to P66 ………………………….. ………………………… 65
Table IV. 4 Significance of places P67 to P132 ………………………….. …………………….. 66
Table IV. 5 Significance of places P133 to P198 ………………………….. …………………… 67
Table IV. 6 Significance of places P199 to P264 ………………………….. …………………… 68
Table IV. 7 Significance of places P265 to P327 ………………………….. …………………… 68
Table IV. 8 Signification of transitions Bloc 1 (B1.1) ………………………….. ……………. 69
Table IV. 9 Signification of transitions Bloc 2 (B1.2) ………………………….. ……………. 70
Table IV. 10 Signification of transitions Bloc 3 (B2.2) ………………………….. ………….. 71
Table IV. 11 Signification of transitions Bloc 4 (B2.1) ………………………….. ………….. 72
Table IV. 12 Signification of transitions Bloc 5 (as sembling) ………………………….. …. 73

Introduction
1 INTRODUCTI ON
The master degree project mechatronics, carried out at the University of Galati, is part
of the mobility of students of the project of the European Union "A lgerian National Laboratory
for Maintenance Education Project No. 586035 -EPP- 1-2017 -1-DZ-EPPKA2 -CBHE -JP ".
DUNAREA DE JOS University of Galati (Romania) and M'HAMED BOUGARA University
of Boumerdes (Algeria) are partners in this international project.
The final project is entitled: Maintenance of flexible manufacturing systems using petri
nets modeling. In this subject, three fundamental notions are predominant and deserve detailed
explanations in the following chapters: maintenance, flexible manufacturing systems and Petri
nets modeling.
Flexibility, responsiveness and agility are essential qualities for production systems that
are faced with a varied and fluctuating demand with increasingly high quality and time
constraints. The challenge for companies is therefore to install modular and flexible production
tools with control systems capable of managing them. These must, on the one hand, adapt to
the heterogeneity of available equipment (computers, robots, machines, etc.), equipment that
can be replaced, removed or reconfigured as needed, and on the other hand, be robust face to
the various malfunctions and hazards. Often there is a dilemma of modeling flexible production
systems, between the development of an overly simplistic model that allows an analysis of the
easy behavior of the manufacturing system that is flexible but far from its actual behavior, and
a model that is closer to the real system, but whose the study is too complex. The ever -increasing
complexity of production systems require s more and more representation methods and analysis
techniques to efficiently account for the various features associated with the system as well as
its temporal characteristics. This imperative inevitably leads to the need to have formal methods
to verify a certain number of properties of interest of the modeled system. In recent years we
have seen many methods and tools for the modeling, simulation and analysis of complex
systems . To this end our choice fell on the Petri nets .
The using of Petri nets in t he modelling has been emerged during 1960, from the
contributions of Petri which won him the Degree of Ph.D. during 1962. The momentum of
using of Petri nets and analysis based on transitions from firing of the nets has gained in the
earlier 1980s. Petri net models, therefore, the resulting controlled model of the system is not
maximally permissive. That is, the solutions obtained in such case are suboptimal. To overcome
such situation in FMSs, a flexible manufacturing system (FMS) model is developed using Petri

Introduction
2 nets for analyzing the important qualitative aspects of FMS behavior such as existence / absence
of deadlocks and butter overflows. It has also been observed that the classical invariant analysis
of Petri net related to qualitative properties of the FMS such as existence of deadlocks, buffer
overflow, invariance of number of jobs and recoverability from failures is determined. Later –
on the FMS has undergone more than four generations by the year 1986 with the emergence
Tool Management issues. To star t with, issues are dealt with the analysis of Scheduling, Tool
Management, Deadlocks and Overflows, Liveness and Siphons, and Monitoring and Control.
Using of supervisory control theory on the real systems in many modeling tools such as
Petri Net (PN) be comes challenging in recent years due to the significant states in the automata
models or uncontrollable events. The uncontrollable events initiate the forbidden states which
might be removed by employing some linear constraints. Although there are many me thods
which have been proposed to reduce these constraints, enforcing them to a large -scale system
is very difficult and complicated. This paper proposes a new method for controller synthesis
based on PN modeling. In this approach, the original PN model is broken down into some
smaller models in which the computational cost reduces significantly. Using this method, it is
easy to reduce and enforce the constraints to a Petri net model. The appropriate results of our
proposed method on the PN models denote wo rthy controller synthesis for the large -scale
systems.
To present the work done in this project we have presented the following chapters:
• Chapter I: PRESENTATION OF THE WORKING ENVIRONMENT
• Chapter II: GENERALITY ON PETRI NETS
• Chapter III: FLEXIBLE MANUFACU RING SYSTEMS
• Chapter IV: ANALYSIS AND SIMULATION OF A REAL PRODUCTION
SYSTEM
• Chapter V: GENERAL CONCLUSION

3

CHAPTER

I
Presentation of the working environment

Chapter I: Presentation of the work ing environment
4 CHAPTER I: PRESENTATION OF THE WORKING ENVI RONMENT
I.1. INTRODUCTION
My internship took place in Romania, in a laboratory of the Department of
Manufacturing Engineering, Faculty of Engineering, Dunarea de Jos University of Galati.
During my internship I v isited the society URB G roup – Rulmenti S.A. from Barlad. In my
project I have used a data base obtained from this manufacturing company in order t o modeling
the process of work using Petri net .
I.2. GENERAL PRESENTATION OF THE UNIVERSITY “DUNAREA DE JOS” OF
GALATI
Galati city , which is known to be the fifth most important town of the country, is set at
the east of the land, close to the border with Moldova and Ukraine, and on the banks of the end
of Danube. This region owns a deeply rooted industrial base, as the most major Roman ian
steelworks (Arcelor Mittal Galați) or the dockyard can bear witness.

Figure I. 1 Map of Romania
The main asset of Galați, in terms of education and scientific research, lies in the
Dunărea de Jos Uni versity. It is made up of fifteen faculties with more than thirty departments.
It has diverse unique fields of education in the country, such as naval engineering or fishery. It
also organizes programs for doctoral and master degrees in various technical fields, such as
chemistry, physics, mathematics, economy, food technology and fishing, automatic control and

Chapter I: Presentation of the working environment
5 computation techniques, artificial intelligence, or even social and humanistic sciences. During
the years, specialists covering a wide range of education fields ha ve been trained in this
University, like engineers, teachers and programmers.

Figure I. 2 Dunarea de Jos University of Galati

Dunarea de Jos University of Galati is the most important institution of higher
education in the South -East of Romania.
Dunarea de Jos University of Galati functions according to the university Charter, whose
provisions are in agreement with the national legislation and with the principles of the European
Space and Higher Education, being recognized b y all members of the university community.

The history of higher education in Galati covers the following stages:
1948: establishment of the Land Improvement Institute;
1951: establishment of the Naval -Mechanical Institute;
1953: merging the Naval -Mecha nical Institute with the Agronomic Institute, and with
the Fish Farming and Fishing Institute (transferred from other University centres), and the
establishment of the Technical Institute in Galati;

Chapter I: Presentation of the working environment
6 1955: merging of the Technical Institute with the Food Industry Institute in Bucharest;
1957: transforming the Technical Institute into the Polytechnic Institute;
1959: establishment of the Pedagogic Institute and relocation of the Land Improvement
Institute to Iași;
1974: establishment of the University of Galati by merging the Polytechnic Institute
with the Pedagogic Institute (State Council Decree of 20 March 1974);
1991: the University of Galati becomes Dunarea de Jos University of Galati
(Government Decision of 4 January 1991).
In the structure of t he above mentioned institutes, there were a series of study
programmes that were unique in the country: Naval Constructions, Harbours and Ship
Exploitation, Food Industry, Fish Farming Technology, Cooling Devices – which meant
that an important creation pr ocess on elaborating educational curricula and syllabi, lectures,
laboratory equipment etc., presently being used in other university centres around the country,
was fully the work of the academics in Galati higher education.
The internship took place m ore accurately in a division of the University, w hich is the
Faculty of Engineering . This entity is an historic one of the University, because it directly
results from the former Technical Institute of Galați.
Initially reputable for its competence in two domains, namely naval construction and
technology of ships and ports, this division has regularly grown through the years, by extending
its specializations such as:
 Refrigeration and T echnology of machinery building in 1960
Thermal machines and W elding technology in 1978
 Metallurgical engineering , Mechatronics and Robotics and Economical Engineering
in 1990 .
Become in the late nineties one of the largest faculty of mechanics in the country, a
breaking up took place, which resulted in a transfer of competences to the F aculty of
Engineering of Brăila and the Technical C ollege. Nowadays, the mission assumed by the
faculty of mechanics is to form specialists through training (normal and post university studies)
in areas such as mechanical engineering , industrial engineering, or environmental engineering.

Chapter I: Presentation of the working environment
7 This mission includes the development of scientific research centers in strong fields,
promoting the national and international cooperation of inter -university and economic
environment, and contributi ng to the universal heritage of knowledge. Over the years, the
faculty of mechanics has forged strong ties with the field of industry, even with multinational
companies such as Dacia, Fiat, or Mittal Steel. In terms of figures, this entity represented in
2008:

 More than 7 0% of research projects accepted for the whole university
 More than 1400,000 € allocated for research, a tenfold growth over the last 3 years
 More than 50 papers published in professional journals
 More than 30 scientific papers published in conferences

Figure I. 3 Entrance of the Faculty of Engineering
I.3. GENERAL PRESENTATION OF URB GROUP – RULMENTI S.A BARLAD
The manufacturing company, Rulmenti S.A. from Barlad, Romania, is a part of the large
URB Group.

Chapter I: Presentation of the working environment
8
Figure I. 4 URB Group
The short history of this company is :
1953 – Barlad Factory started production;
1973 – The Forging technology from Haterbur and Wagner Germany was applied
successfully;
1975 -1982 – Modernization of turning and grinding workshops;
1992 -1996 – Continuous modernization of various machinery and equipment ;
2000 – Finalization of privatization process;
2001 -2005 – A period of big investments in machine technologies;
2006 – Founding Anadolu Rulman factory (ART) in Turkey;
2007 – Acquisition of MGM factory in Hungary;
2011 – Starting the building of India fac tory;
2018 – Continued investment .

Chapter I: Presentation of the working en vironment
9
Figure I. 5 URB Group – Rulmenti S.A.

The Group URB produce different kinds of bearings (cylindrical, spherical, radial,
axial), turning components and other components. The sales regions of their products are
presented in the (figure I.5).

Figure I. 6 Sales regio ns of URB

The conception activity in URB Group use computer aided design software
Pro/ENGINEER, a 3D CAD/CAM/CAE parametric software, and the computer aided analysis
software – ANSIS in order to assure the good quality of their products.

Chapter I: Presentation of the working environment
10
Figure I. 7 URB Group Softwares
The total area of tooling workshop (figure I.8) is 10,900 m2. There are 357 direct
machines & 114 auxiliary machines , capable of:
❖ Turning;
❖ Milling;
❖ Grinding;
❖ Metallic structuring (bending, shocking, rolling, welding);
❖ Heat treatment;
❖ Titanium covering;
❖ Electrical discharging.
The turning process for the bearing rings has been modernized with CNC turning lathes
(PUMA, DOOSAN (Korea) , OKUMA (Japan) , Fuji, MURATA).

Figure I. 8 DOOSAN bought from south Korea

Chapter I: Presentation of the working environment
11

Figure I. 9 Tooling workshop
One of the main parts of tooling workshop is Grinding Section consisting in following
grinding equipment:
➢ CNC – grinding machines ;
➢ Centerless grinding machines ;
➢ Classic grinding machines ,
and quality c ontrol equipment for :
➢ Dimensional (ID/OD/H, angles, raceways, recess, radius)
➢ Form deviations (ovality, profile deviation, parallelism, conicity, raceway
deviations)
➢ Surface checki ng (surface defects, roughness).

Chapter I: Presentation of the working environment
12 Assembly workshop:
All bearings components are inspected before assembly activities by qualified quality
inspectors.

Figure I. 10 Marking and wrapping machines

13

CHAPTER II
GENERALITY ON PETRI NETS

Chapter II Generality on Petri nets
14 CHAPTER II GENERALITY ON PETRI NETS
II.1. INTRODUCTION
Petri net [1] is a modelling formalism proposed by Carl Adam Petri in 1962 for
modelling distributed systems. It was rapidly recognized as a promising formalism, due to its
adequacy to represent a number of features of discrete event dynamic system behavior. PN are
used for modeling complex systems in order to analyze and verify their properties. Petri nets
are particularly suited to the modeling of distributed systems operating in parallel and with
synchronization constraints. The analysis of the models in Petri nets h ighlights the absence of
blockage during the evolution of the modeled system or the existence of a steady state, this
makes it possible to detect the errors of design, to reduce the risks as well as the time and cost
of design.
This chapter introduces the basic concepts of basic Petri nets as well as the high -level
Petri nets that allow to analyze and verify certain qualitative and quantitative properties of the
systems. Petri nets can be used to specify, validate and implement any discrete system includin g
simultaneous evolutions, they are recommended when these systems communicate with the
outside world.
There are several application domains, implementation of dynamics in information
systems, production management, the design of resource allocation mechan isms and task
synchronization procedures in centralized or distributed systems or good for the development
of specifications of industrial process control system.

Figure II. 1 The four seasons and their changes

Chapter II Generality on Petri nets
15 II.2. DEFINITION
A Petri net may be identified as a particular kind of bipartite directed graphs populated
by three types of objects. These objects are places, transitions, and directed arcs (Figure II.2 ).
A place is represented by a circle and a transition by a bar (certain authors represent a transition
by a box). Places and transitions are connected by arcs. The number of places is finite and not
zero. The number of transitions is also finite and not Zero. The ar cs of the graph are directed
and run from places to transitions or transition to a place. The state of a Petri net is the
distribution of tokens (Black dots) on its places, called a marking of the net. A transition is
enabled if each of its input places ho lds at least one token. Firing a transition means removing
one token from each input place and adding one token to each output place. A Petri Net is a
graph model for the control behavior of systems exhibiting concurrency in their operation. [2]

Figure II. 2 Graphical representation of the elements of petri net
Input places may represent preconditions, output places may represent postconditions
and the transition an event. Input places may represent the availability of resources, the
transition their utilization, output places the release of the resources.
Inpu t places Transitions Output places
Preconditions
Input data
Input signals
Resources needed
Conditions
Buffers Event
Computation step
Signal processor
Task for job
Clause in logic
Processor Postconditions
Output data
Output signals
Resources released
Conclusions
Buffers

Table II. 1 Petri Nets elements representation

Chapter II Generality on P etri nets
16 An example of a Petri net is shown in Fig. II.3 .

Figure II. 3 Simple Example
This net consists of three places, represented by circles, two transitions, depicted by
bars, and directed arcs connecting places to transitions and transitions to places. In this net,
places P1 and P2 are two input places of transition t1. Place P3 is an output place of transition
t1 and it is an input of transition t2. Each place may potentially hold either none or a positive
number of tokens, pictured by small solid dots, as shown in Fig II.3 . The presence or absence
of a token in a place can indicate wh ether a condition associated with this place is true or false,
for instance. For a place representing the availability of resources, the number of tokens in this
place indicates the number of available resources [3]. For exampl e, a token in P1 and P2 means
a component and a robot available, respectively. At any given time instance, the distribution of
tokens on places, called Petri net marking, defines the current state of the modeled system. A
marking of a Petri net with n plac es is represented by an (n x 1) vector m, elements of which,
denoted as m(p), are nonnegative integers representing the number of tokens in the
corresponding places, A Petri net containing tokens is called marked Petri net. For example, in
the Petri net mo del shown in Fig.II.3 ,
II.2.1 . Formal definition
Mathematically, a Petri Net (PN) is defined as a 5 -tuple:
PN = <P, T, I, O, M 0> where: (1)
P: a finite set of places, {p1, p2, …, pn}
T: a finite set of transitions, {t1, t2, …, ts}
I: an input function, (T x P) −−> {0, 1}
O: an output function, (T x P) −−> {0, 1}
M0: an initial marking, P −−> N

Chapter II Generality on Petri nets
17 II.3. BASIC DESIGN AND DEFI NITIONS
II.3.1 . Concept of marking

Figure II. 4 Petri net, not marked and marked models
Figure II.4 (b) represents a marked Petri net. And Figure II.4 (a) represents a not
marked Petri net. [1]
the number of tokens contained in a place P i, will be called m(P i) or m i
The net marking m is defined by the vector m= (m 1, m 2, m3, m 4, m 5, m 6, m 7)
For example, in Figure II.4(b) we have m 1 = m 3 = 1, m 6 = 2 and m 2 = m 4 = m 5 = m7 = 0
So, the marking of PN is m= (1, 0, 1, 0, 0, 2, 0 ). Always marking defines the state of the
system described by PN
II.3.2 . Incidence matrix
The input incidence matrix is called the matrix:
W-ij = I (P i, Tj) (2)
The output matrix is called the matrix:
W+ij= O (P i, Tj) (3)

Chapter II Generality on Petri nets
18 The incidence matrix (W) of a Petri net whose lines identify places and columns
transitions; is defined by:

W=W+ij-W-ij W[i][j] = O (P i, Tj) – I (P i, Tj) (4)

W[i][j]=

II.3.3 . Awareness Rule
A transition t is sensitized (validated, passable or pullable) if each of the places of entry
p contains a number of tokens greater than or equal to the weight of the arc connecting p to t.

∀ 𝑝 ∈ P, M(𝑝) ≥ I (𝑝, t) (5)
T1 T2 T3 T4.Tn
P1
P2
Pn

Pm

Chapter II Generality on Petri nets
19 II.3.4 . Firing of a Transition

Figure II. 5 Firing of a transition
The firing of a transition t with draws from each of its places of entry p a number of
tokens equal to the weight of the arc connecting p to t (I (p, t)) and deposits on each of
its places of exit p a number of tokens equal to the weight of the arc connect ing t to
P (O (p, t)).
o Note:
• When a transition is validated, it does not imply that it will be immediately fired; this
represents only a possibility of firing. In a PN, even if several transitions are validated
by the same marking one and only a transit ion can be fired .
• Firing is an instant operation.
A transition t = < I, O > can be fired from m if for any place p:
M(p) ≥ I(p) (6)

Chapter II Generality on Petri nets
20 Figure II.6 illustrates the chemical reaction (2H 2 + O 2→2H 2O) and the change in
labeling after crossing the transition t .

Figure II. 6 The composition of water modeled with PN (2H2+O2 = 2H2O)
Before firing M0 = {2, 2, 0}, after firing M1 = {0, 1, 2}. Places are ordered in this vector
as follows: {H 2, O2, H2O}.
II.4. PETRI NETS PROPERTIES
Among these properties we will mention the following ones [2] [1]:
II.4.1 . Vivacity
A Petri network is said to be alive for an initial marking Mo if, whatever the attainable
marking M ∈R (Mo), it is possible to find a firing sequences which makes it possible to fire any
transition. A blocking corresponds to a marking or no transition is negotiable. The vivacity
property therefore ensures non -blocking. Vivacity Verifies that a system state can be re ached
regardless of the state in which it is located
II.4.2. Consistency and reversibility
A PN is said to be consistent if there is an initial mark Mo and a firing sequence
containing at least once each transition .
A PN is reversible for an initial marking Mo if, whatever the attainable firing, In other
words, in a reversible PN, it is always possible to return to the initial marking. Most industrial
processes have a repetitive operation. It is therefore important to check if the PNs that represent
them are reset.
II.4.3. Persistence
A PN is persistent for an initial marking Mo if whatever the transition torque that can
be firing for this marking, the firing of one of the two transitions does not prevent the firing of
the other. Persistent PN does no t require decision making for conflict resolution, as the firing

Chapter II Generality on Petri nets
21 order will not result in the cancellation of a crossing opportunity. For this reason, a persistent
PN and also called a Petri Net without a decision.
A Petri Net without conflict is always pe rsistent.
II.4.4. Structural and effective conflict
II.4.4.1. Structural conflict
A structural conflict is a set of transitions that have at least one entry point in common.
II.4.4.2. Effective conflict
An effective conflict corresponds to the existence of a structural conflict and a firing M
such that the number of marks in the place of the conflict is lower than the number of marks
necessary to ignite any exit transitions of this place which are validated by M.
II.4.5. Mutual exclusion
Two places are in m utual exclusion if for a given initial marking Mo, they cannot be
simultaneously marked regardless of the marking M reached from Mo.
Mutual exclusion is encountered in any system that includes resource sharing.
II.4.6. Blocking
A blocking is a marking such that no transition is validated.
II.4.7. Modeling competition
Competition: Checks whether the transition to a state involves the collaboration of two
or more parts of the system.
It is the convergence of arcs on a place [4]: figure II.7

Figure II. 7 Convergence of arcs

Chapter II Generality on Petri nets
22 It is the divergence of arcs from a place figure II.8: this "structural conflict" must be
arbitrated (when it actually occurs both must be activated) by a rule of any priority; if not the
behavior of the system is not fully specified [4]

Figure II. 8 Divergence of arcs

II.4.8. Confusion
Situations in which competition and conflict are present are called confusing situations.
Suppose that in the network of Figure II.9 tokens in P1 and P4 arrive simultaneously in
these places. In this case the transitions T1 and T3 are in conflict and it is necessary to make
the choice of the transition which must be fired [5]

Figure II. 9 Confusion situations
Suppose now that the token of place P4 arrives in this place at a time after the arrival
time of the token in P1. At this moment, the transitions T1 and T3 are not in conflict, T1 is
passable T1 immediately does not guarantee in any way that the speed of the operation is
maximum.

Chapter II Generality on Petri nets
23 II.4.9. Producer and consumer

Figure II. 10 Producer and consumer
II.5. PETRI NET’S MODELING
II.5.1. Synchronization
The figure II.9 shows two synchronized operations

Figure II. 11 Synchronized operations

Chapter II Generality on Petri nets
24 II.5.2. Parallelism
In Figure II.10 the transitions t1 and t2 are drawn in parallel

Figure II. 12 Parallel petri net
II.6. PARTICULAR PETRI NETS
II.6.1. Stat graph
An unmarked or marked petri net is a state graph (SG) if and only if any transition has
exactly one entry place and one exit place [2] [6].

Figure II. 13 Stat graph
II.6.2. Event graph
An Event Graph (EG) is a Petri Network in which each place has exactly one input
transition and one output transition. It is characterized by the absence of structural conflicts . [2]

Chapter II Generality on Petri nets
25
Figure II. 14 Event graph
II.6.3. Free choice
Two definitions exist, which are distinguished by the appellations free choice and
extended free choice. [7]
A free choice PN is a PN in which for every conflict none of the transitions posses ses
another input place.
An extended free choice PN is such that for every conflict all the transitions have the
same set of input places.
In such a PN (free choice or extended free choice), if a transition involved in a
conflict is enabled, all the transitions involved in the same conflict are also enabled.
II.6.4. Pure PN
A transition is said to be pure if it has no place that is both an e ntry place and an exit
place ( Figure II.14.a ). If all PN transitions are pure the PN is pure. [8] [9]
A transition is said to be impure if it has a place that is both a place of entry and a place
of exit ( Figure II.14.b) . If the PN transitions are impure the PN is impure. [8] [9]

Figure II. 15 Pure and impure PN [8], [9]

Chapter II Generality on Petri nets
26 II.6.5. Simple PN
Simple Petri nets are ordinary PN such that each transition has at most one entry place
that can be related to other transitions, (Any transition belongs to one conflict at most).

Figure II. 16 Simple PN
II.7. MODELING A SYSTEM
Example:
We have one starter and two cars. When the starter receives ready signs from the two
cars ( a, b), he gives the starting signal and the cars begin the race. [10]

Figure II. 17 Starting two racing cars example [10]
So, the cars send ready sign after preparing for start and then still waiting for start
(figure II.17 a). The starter gives start sign to the cars (figure II.17 b). Both of cars a and
b running after the sign given by the starter (figure II.16 c) . Essenti al conditions and actions
have been identified on the following table:

Chapter II Generality on Petri nets
27 List of conditions List of actions
P1: car a; preparing for start t1: car a; send ready sign

t2: car a; start race

t3: starter; give start sign

t4: car b; send ready sign

t5: car b; start race P2: car a; waiting for start
P3: car a; running
P4: ready sign of car a
P5: start sign for car a
P6: starter; waiting for ready signs
P7: starter; start sign given
P8: ready sign of car b
P9: start sign for car b
P10: car b; preparing for start
P11: car b; waiting for start
P12: car b; running
Table II. 2 List of conditions and actions

Figure II. 18 Graphical representation of phases

Chapter II Generality on Petri nets
28
Figure II. 19 Net of the full system
II.8. HIGH LEVEL PETRI NETS
There are several types of petri nets and in our case, we will only study the timed petri
nets which belongs to the category of non -autonomous PN like synchronized petri nets and
other types.

Figure II. 20 Illustrative sche ma
: means that there are other PN’s types that belong to this category
II.7.1. Timed Petri nets
The Petri nets discussed so far model systems whose evolution does not depend on
time. Indeed, in the classical model, transitions are activated without taking into account time
constraints such as timers for example. There are also time petri nets which allow to study more
specific problems with real time systems, such as dynamic scheduling. These networks have
shown their interest in particular in evaluating the performance of a system.

Chapter II Generality on Petri nets
29 Among the proposed techniques for specifying and verifying systems in which time
appears as a parameter, two are widely used: Timed Automata and Time Petri Nets, introduced
in [11].
II.7.1.1. Definition
A timed Petri net is used to describe a system whose operation depends on time. For
example, there may be some time between the start of an operation and the end of this operation.
If a mark in a certain place indicates that this operation is in progress, a timed PN will account
for this duration. Timed Petri nets are useful for evaluatin g the performance of a system. There
are mainly two ways to model the delay: either the delays are associated with the places we say
that we have a P -timed PN, or the delays are associated with the transitions we say we have a
T-timed PN.
II.7.1.2 . Formal definition
A timed Petri net ( TPN) with n places and p transitions is a doublet RT= <R, D> (7)
R is a PN < P, T, I, O> with initial marking M 0
D is a function called static interval:
D : T Q+
Q+: is the set of real non-empty intervals with non -negative rational bounds.
The application D associates a time interval D(t) with each transition of the network.
II.7.1.3 . State of TPN
A state of a temporal network is a couple s= (m, D) in which m is a marking and D a
functio n that associates a time interval with every transition sensitized by m.
The initial state is e 0 =(m 0, D0) where D 0 is the restriction of D to transitions sensitized
by the initial mark m 0. [12] .
II.8. AUGMENTATION METHODS OF PETRI NETS
We desire to incorporate the results of error recovery planning to augment the model Z
to form Z'. Four basic methods for augmentation to Z' from Z are proposed. They are input
conditioning, alternate path, backward error recovery, and forward error recovery . The last
subsection will deal with the maintainability of behavioral properties .

Chapter II Generality on Petri nets
30 II.8.1 . Input Conditioning Method
The idea of the input conditioning method is that an abnormal state in a place that
represents a process or a state of a manufacturing system can become a normal state after other
actions are finished or some conditions a re satisfied. An example of this is the arrival of a part
that requires additional finishing prior to processing at a workstation.
II.8.2 . Alternate Path Method
The philosophy of the alternate path method (also called error avoidance) states that
there exi sts another sub -Petri net which can transform an abnormal state in place p directly into
a normal state in a system. Depicts this type of construction of Z' from Z. It is assumed that the
state in the place w will be achieved after the state in the place p . S' and Z satisfy the same
conditions described as in the last subsection.
II.8.3 . Backward Error Recovery Method
Backward error recovery suggests that under the assumption that the state is normal, i.e.
e(p) = 1, Q in Z is executed and a new faulty state in place w results. But this state can become
a normal state in place p after the operation of a sub -Petri net .
II.8.4 . Forward Error Recovery Method
The forward error recovery method is similar to the backward error recovery method;
suppose that a faulty state results after the operation of Q in Z. However, this state can be
directly transformed into a normal state in Z after a Petri net controller S' operates. Again, the
same conditions about Z and S' are assumed. This strategy is particularly usef ul when a fault at
p is difficult to detect while it can be relatively easier to detect at w.
II.8.5 . Maintainability of behavioral Properties
The property analysis of a Petri net includes boundedness, safeness, liveness (absence
of system deadlock), and r eversibility (re -initializability or properness). The following will
focus on the maintainability of these properties of a Petri net when Z' is constructed from Z
using the four basic construction methods discussed above. The four basic construction method s
are input conditioning, alternate path, backward error recovery, and forward error recovery. For
each method, there are t' , r' ,S' that do not belong to the controller Z. Let S' be a Petri net block
which represents the error recovery procedure with its initial marking mo· An associated Petri
net S* is defined as a Petri net which consists of a place p, t', r', and S' where p is called an idle

Chapter II Ge nerality on Petri nets
31 place. Its initial marking is mo*= (1, mo) where mo is the initial marking of S' and 1 implies
that the idle pla ce is initially marked.

Figure II. 21 Associated Petri net S*

Chapter II Generality on Petri nets
32 II.9. CONCLUSION
This chapter was the subject of the presentation of the basics of the Petri nets. Petri nets
are particularly well suited to describe some aspect of control of systems with parallel evolution,
such as conflicts. Sequencing as well as basic communication mechanisms. Their interest in the
representation of discontinuous or discrete proce sses is well established. The Petri nets is a
powerful tool both for its diversity of modeling and the technical tool associated with it, that’s
why Petri net tool attracts more and more researchers . On our part, we have found it useful for
modeling and an alysis our application which concerns the study of a production system. it
allows us to analyze the behavior of the system represented and to determine many properties .

33

CHAPTER III
FLEXIBLE MANUFACURING SYSTEMS

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
34 CHAPTER III: FLEXIBLE MANUFACURIN G SYSTEMS
III.1 . INTRODUCTION
To produce quality products in large quantities and at a lower cost, which entrepreneur
was not haunted by this objective! Indeed, considering the separation of production or
processing (one sector for turning, another for milling, a third for sharpening, a sector for the
assembly… The parts follow a complex circuit in workshop, the consequence immediate is
naturally a waste of time due to transfers and waiting as well as a multiplication of the
adjustment times, the question is posed: how to overcome thes e disadvantages? [13]
So engineering product development has moved away from the traditional linear steps
to a more integrated product life cycle development process , Manufacturing requires materials,
manpower, machines, metho ds, and measures, to achieve the challenge posed by variable
demand, manufacturing companies have two basic alternatives: build manufacturing plants with
excess capacity and stock excess goods in inventory to smooth fluctuations in demand, or
increase the flexibility of their manufacturing plants so that production volume and variety can
be varied more easily to match changes in demand. Numerous manufacturers have pursued this
second option of increased flexibility. [14]
In orde r to bring a good understanding to the modeling of the flexible workshop, we
will first give the general notions associated with flexible production systems.

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
35 III.2. DEFINITION
The development of CNC and DNC led to the first U.S. implementation of a Flexible
Manufacturing System (FMS) at Caterpillar Tractor in the mid -1970's. The typical
configuration of an FMS is an integrated group of processing CNC machines and material –
handling equipment under computer control for the automatic processing of palletized parts.
Many of these systems use robots or automated guided vehicles for loading and unloading parts.
The operation of the FMS is integrated by supervisory computer control. The major advantage
of a FMS is ability to produce in ra ndom order a variety of products as well as new products on
the same machine and accommodate design changes. FMS is called flexible because it is
capable of processing a variety of different part types and quantities of production.
So simply FMS can be def ined as a group of processing work stations interconnected
by means of an automated material handling and storage system and controlled by integrated
computer control system. [15]
III.2.1. Manufacturing systems
A production sys tem consists of all the necessary resources, both human and material,
that make it possible to transform the raw material or the components into finished products.
Production systems are organized and managed according to the demands and resources
availabl e.
III.3. PRODUCTION MODES
III.3.1. Continuous production
Homogeneous products (manufacture of steel, chemical products), is carried out continuously,
by a continuous flow of materials and products, and is concentrated in one place. Automation
is important (little manpower and a lot of machines).
The most characteristic examples of continuous production are products such as sugar, oil,
cement, steel in continuous casting. [16] This type of workflow typically has the fol lowing
characteristics:
✓ Single or quasi product
✓ Machine layout linearly
✓ Little flexibility
✓ Balancing machine capacity very good
✓ Significant investment and strong automation

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
36 III.3.2. Discrete production
production on demand or fractionated in time or space, concerns the production of
relatively small quantities of very varied products which require different assembly processes.
This production system results in the creation of large stocks of intermediat e products. [16]
Mechanical industries are examples of this type of production (workshop).
This type of workflow typically has the following characteristics:
✓ implementation of machines by function,
✓ great flexibility because the machines are not specific,
✓ Balancing the capacity of the machines difficult hence the appearance of current.
III.3.3. Comparison between continuous production and discrete production

Table III. 1 The difference between continuous and discrete production

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
37 III.4. FLEXIBILITY
A flexible system must be capable of changing in order to deal with a changing
environment. According to Kickert (1985) [17], flexibility increase control capacity by means
of an increase in variety, speed and amount of responses as a reaction to uncertain future
environmental developments.
Flexibility in manufacturing means being able to reconfigure manufacturing resources
so as to produce efficiently different products of acceptable quality.
III.5. FLEXIBILITY IN A PROD UCTION SYSTEM
III.5.1. Basic flexibility
III.5.1.1. Flexibility of machines
The flexibility of a machine refers to the variety of operations that can be performed by
it. [18] The advantages of the flexibility of the machines in a system are: the decrease of the
size of the transport batches, the increase of the utilization rate of the machines, the production
of complex parts, the reduct ion of the time of introduction of new products in the production
system
III.5.1.2. Flexibility of handling tools
It is the ability of a handling system to move the different parts efficiently through the
production system during a production phase. [18] The purpose of the flexibility of handling
means is to increase the availability of machines, to increase the rate of use of machines, to
reduce production times and consequently to increase the efficiency of the manufactu ring
production system.
III.5.1.3. Flexibility of operations
It is the ability to replace operations that allow the manufacture of a part. In this case,
this means that there are no precedence constraints between all the manufacturing operations of
a part. The objectives of the flexibility of the operations are the improvement of the availability
of the machines, and of their rate of use, the possibility to continue the production even if a
machine is defective.

Chapter III: FLEXIBLE MANUFACU RING SYSTEMS
38 III.5.2. System flexibilities
III.5.2.1. Flexibility of manufacturing processes
It is the set of parts that a system can produce without making major changes. The goal
of such flexibility is to reduce the size of production batches and inventories, increase resources
and minimize duplication of machines.
It should be noted that the presence of personnel with transversal skills makes it possible
to improve the flexibility of the manufacturing processes.
III.5.2.2. Product flexibility
It's the ability to integrate a new part into a production syste m while minimizing
changeover times and minimizing costs. This flexibility can be achieved through machine
flexibility but also through an efficient planning and control system. [18]
III.5.2.3. Flexibility of product routing
It is the ability of a production system to take into account machine failures that occur
during production and still continue to produce. Product flexibility is an asset for innovative
companies or those in a growth phase because the introduction of a new product usually follows
a technological innovation or a strategy of growth of the offer. [19]
III.5.2.4. Flexibility of product volumes
It is the ability of a system to adapt to the variation of orders. This adaptation can result
in an addition / deletion of a machine (s) in case of increase / decrease of the production volume
or by a modification of the configuration of the workshop according to the manufacturing
processes of the parts. [20]
III.5.2.5. Expansion flexibility
It is the capacity of expansion of a production system according to the will of the
designer. To achieve this level of flexibility, it is essential to have flexibility in machinery and
flexibility in the means of handling. The expansion flexibility of a production system concerns
companies that are growing in activity. According to [21] expansion flexibility helps to reduce
the costs of implementation times and costs of new products. In addition, to achieve this level
of flexibility it is necessary to avoid design processes based on the implementation of
production systems (eg . dedicated production lines), it is preferable to have modular flexible
production cells. [22]

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
39 III.5.3. Aggregate flexibilities
III.5.3.1. Flexibility of control programs
In the factories where several teams work but at odd hours, there is a time when the
change of team has to take place. This period causes a slowdo wn in production. One of the
solutions to stabilize the production during the change of team is the increase of the flexibility
of the control programs of the production system. Thus, the flexibility of control programs is
the ability of a production syste m to run idle for a relatively long period of time. The aim of
such flexibility is to: enable team changes, reduce production start -up times and consequently
increase production system yields. [18]
III.5.3.2. Flexibility of prod uction
It is the set of parts that can produce a production system without it adding another major
equipment. This characteristic defines the production potential. The flexibility of production
allows companies that position themselves in new product areas to continually remain
competitive. It reduces production costs and introduces new products and also replaces them
with a production system, allowing a company to diversify its products. activities and therefore
to reduce its risks. [22]
III.5.3.3. Market flexibility
It is the ability of a production system to adapt to the changing market environment.
This type of flexibility is very important for business survival in a constantly changing
environment. This shift cou ld be due to technological innovations, changes in consumer tastes
and behaviors, short product life or uncertainty of supply sources. Market flexibility allows
firms to cope with these changes, and this flexibility is also a real asset to a company in the face
of its competitors. [22]
III.6. FLEXIBLE MANUFACTURIN G SYSTEMS
A flexible production system represents several flexible cells linked together by wire –
guided vehicles that make up the various production areas. The flexible system is a system able
to adapt to any new constraint imposed by the environment of which the production is managed
by a computer system (change of product, modification of production flow) [23]

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
40 A flexible workshop allows the automatic production of parts of various types and in
variable quantities. Operators do not intervene directly in the manufacturing process and
essentially limit their interventions to maintenance; the scheduling of production is managed
by a computer syst em [24]
III.7. DIFFERENT TYPES OF FMS
According to [25] the FMS can be divided into five categories:
III.7.1. Flexible module: (FM)
The flexible module: is an NC machine with a storage area, a parts loader and an atomic
tool magazine
III.7.2. Flexible cell: (FC)
Represents several modules connected by a guided vehicle allowing the power of
machines in pieces
III.7.3. Flexible group: (FG)
The flexible group (FG) is a set of cells and modules forming the same production area
(manufacture, machining or assembly) joined by wire -guided vehicles; everything is managed
by a central computer .
III.7.4. Flexible system: (FS)
The FS represents several flexible cells interconnected by wire -guided vehicles making
up the various production zones
III.7.5. Flexible line : (FL)
The FL is a set of instruments allocated to various machines such as a line of wire –
guided vehicles, robots, conveyors, shuttles, … [26]

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
41
Figure III. 1 Different types of FMS between flexibility and productivity
III.8. AREA OF APPLICATION OF FMS IN INDUSTRY
The following chart in the Fig. III.2 shows the various applications in an industry

Figure III. 2 Area of applications of FMS in an industry
CAD: Computer Aided Design CAQ: Computer Aided Quality Control

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
42 III.9. COMPONENT OF A FMS

Figure III. 3 Components and structure of Flexible Manufacturing System
III.9.1. Workshops
A workshop is characterized by the number of machines it contains and by its type. [27].
There are three types of workshops: flow -shop, job-shop and open -shop, with possible
extensions for each of them. [28]
III.9.1.1. Flow-shop
These are workshops where a production line consists of several machines in series; all
the operations of all the tasks go through the machines in the same order, s o a flow -shop is a
single path workshop, for example, if the product needs two drilling operations, you will have
two drilling machines.
• Easy to automate: It is simple to apply robotics to a flow shop because the steps are
consistent and repetitive.
• Easy to measure: Many manufacturing KPIs (Key Performance Indicators) are designed for
flow shops.
• Easy to optimize: As a result of being easy to measure, it is also easy to tell which stages in
the process need to be optimized and there are clear solutions for dealing with unoptimized
steps.

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
43 III.9.1.2. Job-shop
These are workshops where operations are carried out according to a well -defined order,
varying acc ording to the task to be performed; the flexible job -shop is an extension of the classic
job-shop model; its particularity lies in the fact that several machines are potentially capable of
performing a subset of operations. Also called multi -path workshops
Easy to set up: Small businesses often implement jobs shops because they are simple
to set up and the initial investment is minimal. You can begin with one or two machines and
add them as needed.
High flexibility: It is easy to add, change or re move stages in the process. If a part needs
to be re -machined, it is simply sent to the corresponding machine.
Easy to increase capacity: Because it is easy to add a new machine to a job shop, you
can increase capacity incrementally by adding a new machine .
III.9.1.3. Open-shop
Compared to other workshop models, open -shop is not commonly used in companies.
This type of workshop is less constrained than that of flow -shop type or job -shop type. Thus,
the order of operations is not fixed , it have no schedulin g at all, operations can take place in any
order, which means they are very flexible but hard to optimize in practice, the problem of
scheduling consists, on the one hand, in determining the path of each product and, on the other
hand, in scheduling the pr oducts taking into account the ranges found.
III.10. PROBLEMS IN A FLEXIBL E MANUFACTURING SYST EM
There are four problems with flexible production systems [29]:
III.10.1. FMS design problems
In developing an FMS design, there is a partial ordering to some of the decisions that
have to be made. Some decisions must precede others in time. We partition these into initial
specification decisions and subsequent implementation decisions.
III.10.2. FMS planning problems
We define FMS planning problems to be those decisions that have to be made before
the FMS can begin to produce parts. Once the FMS is 'set -up', production can start.

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
44 When the FMS planning problems have been solved, and all of the cutting tools have
been loaded into the appropriate tool magazines, production can begin. These FMS planning
problems can be solved sequentially, or iteratively, or several simultaneously. They can be re –
solved as often as every couple of days or weeks. Th ey may re – quire re -solving if one of the
machine tools is down for a long time.
III.10.3. FMS scheduling problems
MS scheduling problems are concerned with running the FMS during real time once it
has been set up during the planning stage which is in adva nce of actual production. There are
many possible approaches that can be taken to schedule the manufacture of parts through the
system. Different approaches might be applicable in different situations [28].
III.10.4. FMS control problems
We define FMS control problems to be those associated with the continuous monitoring
of the system, the keeping track of production to be certain that production requirements and
due dates are being met as scheduled.
III.11. SOLUTION OF FMS PROBLEMS :
There are many models available that can be applied to help answer some of the
preceding problems. Each model can structure the problems differently. Each model ignores or
aggregates some features of the system to focus on particular aspec ts. The models have
provided either operational or qualitative insights into some of the FMS decision problems. A
list of several of the models that can and have been applied include: simulation, group
technology, computer aided process planning, queueing networks, mathematical programming
(linear, nonlinear, integer), perturbation analysis, Petri nets, and artificial intelligence.
III.12. MODELING OF PRODUCTIO N SYSTEMS
We are engaged in the proposal of a simulation model of production systems, so it is
important to remember what are the objectives of modeling for production systems, what are
the main models used, and also what are the approaches and approaches used in this modeling.
In this way we will be able to choose the model that we will use as part of our work. Before
that, let us recall the objectives of the modeling of production systems.

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
45 III.12.1. Objectives of modeling a production system
❖ Analysis: description or simulation: the analysis and description tools make it possible
to define the models o f the subsystems of a production system as defined in [30], namely
the physical subsystems, d. information and decision -making.
❖ Evaluation : evaluation models make it possible to determine the performance of a
production system through indicators defined by the manager of the production
system. The models that allow the evaluation of a production system are most often
so-called simulation models. These simulation models are based on mathematical
equations or gra ph theory. Simulation is obviously only possible with the help of
appropriate calculation or simulation software.
❖ Optimization : it is done by the exact methods or approximate methods, using
mathematical models or graphs.
There are two main types of models, mathematical models, and discrete event models.
Among mathematical models we have linear models, integer models, quadratic models. And
among the models with discrete events we distinguish disjunctive -connective graphs,
precedence graphs, automatons, and P etri nets.
III.13 . PETRI NETS MODELING AND PRODUCTION SYST EMS:
Petri nets have been used for more than 30 years for modeling and verifying different
aspects of flexible production system s.
Date and
reference Type of Petri
nets Description
1989
[31] Timed Petri nets Modeling flexible production systems using timed
PN.
2002
[32] Colored Petri
nets Multi -objective optimization for minimizing
production costs under multiple production plans and
minimizing reconfiguration costs. The PN are coupled to
the genetic algorithms as well as to the priority rule SIO
(Shortest Imminent Operation time)
2003
[33] Timed Petri nets Optimized scheduling using the A* algorithm (the
smallest path search) and marking graphs in order to

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
46 Date and
reference Type of Petri
nets Description
minimize productivity (Makespan) flexible production
workshops
2007 [34] Timed Petri net Modeling and analysis of a flexible workshop
using Petri nets
2008 [35] High level Petri
nets The purpose of this work is the use of PNs for the
modeling and evaluation of Flexible Production Systems.
The author also proposes an object vision of Petri nets,
where tokens are now considered as objects.

2009 [36] Colored Petri
nets Modeling and maximization of the performance
of the transport system consisting of automatically
guided vehicles. The activity of a machine is repr esented
by a transition.
2011 [37] Colored Petri
nets Using timed state graphs to model the processing
of a two -machine Job Shop.
2011 [38] Stochastic Petri
nets In this work, the authors present a methodology
for the analysis of flexible production systems. This
methodology is based on stochastic and modular Petri
nets. The authors present in their work the models of the
basic elements of a flexible production system, namely:
machines, tra nsport resources, products. The authors also
develop a stochastic model to model the dependability.
2013 [39] Timed Petri nets Modeling and simulation of the scheduling of the
Job-Shop using timed Petri nets. The models of the
machines which are presented take into account the
availability of the machine but do not seem to take into
account the various tools.
2014 [40] deterministic
and stochastic
Petri nets The models are used to evaluate the performance
of the Manufacturing Production Systems. The machine
models used take into account the availability problem

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
47 Date and
reference Type of Petri
nets Description
by the tool change. This work presents a methodology
for the design of modular production systems ta king into
account transport times, machine breakdowns, and
maintenance tasks.
2014 [41] Fuzzy Petri nets Planning of maintenance of time -constrained
production manufacturing systems based on Fuzzy PN
2016 [42] Place&
transition Petri
nets Development of a methodology for increasing the
flexibility of planning in service -oriented production
systems.
2017 [43]
Nested Petri
nets Authors use the synthesis -based modeling
approach to synthesize a Petri net from specified
behavior. they have a model of simple executions of a
process by means of a very intuitive modeling language.
And use a synthesis algorithm to produce a relative Petri
net model.
2017 [44] Place&
transition Petri
nets This paper illustrates the Petri net modeling of a
conceptual model of flexible manufacturing system
(FMS) and addresses the problem of deadlock by
deadlock prevention policy.
2018 [45] Place&
transition Petri
nets The authors focused on solving deadlock
problems in flexible manufacturing systems modeled
with Petri nets by adding a set of recovery transitions.
Table III. 2 Components and structure of Flexible Manufacturing System

Chapter III: FLEXIBLE MANUFACURING SYSTEMS
48 III.14 . CONCLUSIO N
It must be recognized that flexible systems are a wonderful tool that technology makes
available to us to achieve significant progress, regardless of the technological and human levels
of the companies. The real novelty does not lie in the technology implemented, except at the
level of control and management software. The evolution is in the mode of conception, in the
approach that must be applied and in the operations that must be solved. As such an analogy is
possible with t he simulation, it is necessary before the actual processing to make model .

49

CHAPTER

IV
ANALYSIS AND SIMULATION OF A REAL PRODUCTION SYSTEM

Chapter IV: Analysis and simulation of a real production system
50 CHAPTER IV: ANALYSIS AND SIMULATI ON OF A REAL
PRODUCTION SYSTEM
IV.1. INTRODUCTION
The Petri net description of a system concentrates on two concepts: events and
conditions [46]. Events are actions that occur in the system and conditions describe the state of
various parts of the system. The condition is either true or false. In order for events to occur
certain conditions, referred to as preconditions, must exist. After an event occurs these
preconditions usually change and another set of conditions, referred to as postconditions,
becomes val id. The postconditions of one event may be the preconditions of another and so a
sequence of events may occur .
Our study of Petri net for manufacturing systems begins with the classification of places
in a Petri net model. The modeling approach in which pl aces are used to model operation
processes and the availability of resources, and in which transitions are used to model the start
and/or end of operations makes such a distinction among places possible .
IV.2. RESOURCES
A resource is a technical or human m eans to be used for the completion of a task and
available in limited quantities [47]. Resources, whether human or material, are essential for the
maintenance function. However, the costs they entail require better exploitation and allocation
of resources because of conflicts that arise when a resource is solicited by more than one
machine.
The resolution of this conflict takes into consideration the different types of resources.
This notion of conflict is relative t o a decision to be made, according to unforeseen criteria.
Each maintenance task requires the use of one or more types of resources. In terms of
model we can present the resources as places containing each a number of tokens, this number
means the availabl e quantity of such a resource.
We have two types of resources which is Renewable resources and consumable
resources:
❖ Renewable resources
This type of resource is reusable, for example (machine, man, etc.).

Chapter IV: Anal ysis and simulation of a real production system
51 ❖ Consumable resources
The consumption of the resource is considered a constraint in addition to its availability.
Examples include raw materials and financing.
The different types of resources were represented in ( Figure IV.1) .

Figure IV. 1 Types of resources example
Tokens in P 0 represent the number of raw materials available, tokens in places P3 and
P4 represent the availability of the resource, the machine is available but the robot is not.
IV.3. SHARED AND UNSHARED RESOURCE
Each manufacturing process, what ever its type, needs resources, these resources may be
shared with other operations or may be private :
• Private resource (unshared): each operation has its own resources .
• Shared resource: resources in such systems may be shared by different processes .
In ma nufacturing we need machines, robots and transports means as a resource , these
operations can be in parallel so we can share machines, robots and transports means between
different operations. A simple example below in Figure IV .2.

Chapter IV: Analysis and simulation of a real production system
52
Figure IV. 2 Shared and unshared resource
The initial marking is: M0= (0,0,0,0,1,1,1)
In this example we have 2 parallel process, each process with two operations and every
operation uses one resource.
Operation 1 and operation 3 use M1 as a shared resource between both of it, the other
operations op2 and op4 use M2 and M3 respectively .
IV.4. DESCRIPTION OF THE SYSTEM
This system uses a workstation developed at the URB Factory. The workstation uses
robot s to place and pull the bearing into the machines and uses Automated guided vehicles to
transport the parts from block to another block. This system's layout is depicted in Fig IV. 3
and comprises the following components:
• 28 Turning Machines.
• 83 Grinding m achines.
• 4 Automated guided vehicles.
• 2 Assembling stations.
• 41 Robots
• Sensors installed in the robots.
• Storage station
• 4 entries
• 2 exits

Chapter IV: Analysis and simulation of a real production system
53 Code of
machines The Role of the machine
G 40_OS Drilling machine GCO -40
KH300_W3 Hydraulic lathe SHM -300 (canal W33)
L.KH.OSC Lathes line KH -300
MK 248 Front al lathe MK -248 (MA -730)
AJ_GA_OS Adjustment after drilling
CNC_OCAR Couple 2xCNC lathes
(2XOKUMA/3XPUMA/3XLYNX)
3183 Centerless grinding machine 3183
DISC_PE Device for grinding rings
ICHIKAWA Rectified plan machine ICHIKAWA
LZ 259 Grinding machine LZ -259
R 236 Grinding machine GIUSTINA R -236
R 242 Grinding machine GIUSTINA R -242
SASL 200 Centerless grinding machine SASL -200
SASL 5AD Centerless grinding machine SASL -5AD
SL 631 Centerless grinding machine SL -631
AGL315_E Grinding machine CDR SWaAGL -315
AGL315_G Grinding machine CDR SWaAGL -315
MA464_E Corrugated grinding machine MA -464
PRI 300 Grinding machine CDR PRI -300A
SAW 6 Grinding machine SAW -6F
SIW4B_E Grinding machi ne SIW -4/1B
ECOCA_R Numerical lathe machine ECOCA
IGL450_E Grinding machine -SWaIGL450 CNC -inel 10
6A-ASCE Interior grinding machine 52ACE
AFCC 450 Grinding machine CDR AFCC -450AR
MRG 140 Corrugated grinding machine MRG -140
SAW 4 Exter ior grinding machine SAW -4f
Table IV. 1 Some machines in the system and their jobs
In this manufacturing system we have three mains operations which are turning,
grinding and assembling. Two products B1 and B2 are manufactured and their process ranges
are shown in Figure IV. 3 We divided the system in to five blocks :
• Block 1: turning and grinding of part B1.1 (22230 CW33 -10)
• Block 2: turning and grinding of part B1.2 (22230 MB -20)
• Block 3: t urning and grinding of part B2.2 (22232 MB -20)
• Block 4: turning and grinding of part B2.1 (22232 MBW33 -10)
• Block 5: assembling of B1 and B2

Chapter IV: Analysis and simulation of a real production system
54
Figure IV. 3 The Manufacturing System
IV.5. OPERATING CYCLE
An unlimited source of raw materials is assumed. Once machines, robots, or AGVs start
work on any operation, they cannot be interrupted until the work is complete.
There are four entries for raw materials, which are produced into four different kinds of
products . Initially, the vehicles (AGV) are empty and available for upload. Four AGVs are
designed for the delivery of final parts from the turning station to the grinding station in the
system . The first transfer is made from the output of Turning to the input of grinding where the
produc t will then be grinded . From AJ_GA_OS (Manual loading) , AGV1 and/or AGV4 sends
final parts to the input of grinding and back to Entry . From AJ_GA_OS (Manual loading) ,
AGV2 and or AGV3 sends final parts to the input of grinding . The transfer mu st wait in its state
until the Robot unloading of the part. Once the vehicle is unloaded, it goes into the initial state
to load new parts.
Robot R 1 unloads AGV1 and AGV2 and none of these AGVs has any priority to use
this robot. R 1 chooses one machine if raw material is available and the AGV is ready. Robot s
R2, R3, R4, R5, R6, R7 and R8 used to loads and unloads machines in the grinding station in
Block 1. Robot s R1 and R38 is shared between block1 and block4, the robots R18 and R3 9 is
shared between block2 and block3 .
There are two exits for finished parts B1 and B2 where we have the assembling area,
Parts from Block1 will be assembled with parts from Block2 and block3 parts assembled with
block4 parts .

Chapter IV: Analysis and simulation of a real production system
55 IV.6. MODELING GENERAL SYSTEM
The criteria most used in the choice of models are:
System data .
Adaptation and simplicity of the model to the system .
The implementation of the model on computers .
For the modeling we u sed a simulator called GreatSPN (description in Annex 1) to
modeling the system and we used another simulator which is PIPEv4.3.0 to get the properties
and the matrix.
The model is built in 2 steps:
Workshops modelin g.
The modeling of operations and machines .
IV.6.1. WORKSHOPS MODELING
The Petri Net model of the workstation s is shown in Figure IV.4

Figure IV. 4 Modeling of general system
In this model we see the course of the general system block by block, the incidence
matrix of the system is showed in figure IV.4, IV.5 and IV.6

Chapter IV: Analysis and simulation of a real production system
56
Figure IV. 5 The output matrix

Figure IV. 6 The input matrix

Figure IV. 7 The incidence matrix

Chapter IV: Analysis and simulation of a real production system
57 To make an oscillogram for the system we have the table of state of places Table IV.1
to see how the course of simulation .

Table IV. 2 State of places

Figure IV. 8 Oscillogram of evolution state of places
The oscillogram of evolution state of places is showed in Figure IV.7
IV.7. MODELING THE SYSTEM
The system may contain shared and unshared resources, renewable and consumable
resources . The token ( ●) in the net sets (free or busy) the state of the machine s or robots
(resource place) .
The modeling of the five blocks and the full system using GreatSPN Tool is in the next
figures. This model represents the scheduling of the system.

Chapter IV: Analysis and simulation of a real production system
58 IV.7.1. Block 1

Figure IV. 9 Modeling of block 1

Chapter IV: Analysis and simulation of a real production system
59 IV.7.2. Block 2

Figure IV. 10 Modeling of block 2

Chapter IV: Analysis and simulation of a real production system
60 IV.7.3. Block 3

Figure IV. 11 Modeling of block 3

Chapter IV: Analysis and simulation of a real production system
61 IV.7.4. Block 4

Figure IV. 12 Modeling of block 4

Chapter IV: Analysis and simulation of a real production system
62 IV.7.5. Block 5

Figure IV. 13 Modeling of block 5

Chapter IV: Analysis and sim ulation of a real production system
63 IV.4.6 . Full system

Figure IV. 14 Modeling of the full system

Chapter IV: Analysis and simulation of a real production system
64 IV.5. TABLES OF PLACES AND TRANSITIONS
IV.5.1 . Significance of places
Places Significance Places Significance Places Significance
P1 part 1 loaded P23 Availability of R
236 P45 Availability of MRS 650
P2 Operation 1 P24 op 9 finis hing
rectification P46 Intermediate place
P3 Operation 2 P25 Availability of R
242 P47 operation
P4 Operation 3 P26
P48 Availability of LZ 259
P5 Operation 4 P27 op 10, exter ior
rectification P49 operation
P6 operation 5 P28 Availability of SL
631 P50 Availability of 6ASCE
P7 Availability
of
L.KH.OSC P29 op 11, external
rectification P51 operation
P8 Availability
of
KH300_W3 P30 Availability of
3183 P52 Availability of MRS 650
P9 Availability
of TRC -100 P31 Intermediate
place P53 Intermediate place
P10 Availability
of MK 248 P32 operation 12 P54 operation
P11 Availability
of
KH300_W3 P33 Availability of LZ
259 P55 Availability of SASL
5AD
P12 Availability
of OK 300 P34 operation 13 P56 operation
P13 Operation 6 P35 Availability of
MRS 650 P57 Availability of SASL 200
P14 Availability
of G 40_OS P36 Intermediate
place P58 Intermediate place
P15 operation 7 P37 operation 14 P59 operation
P16 Availability
of
AJ_GA_OS P38 Availability of
SASL 5AD P60 Availability of R 236
P17 transport P39 operation 15 P61 operation
P18 Availability
of AGV P40 Availability of
SASL 200 P62 Availability of R 242
P19 loading of
Part 1 P41 Intermediate
place P63 B1 ready for assembling
P20 Availability
of Robot 1 P42 operation P64 Availability of Robot 2
P21 Intermediate
place P43 Availability of LZ
259 P65 Availability of Robot 3

Chapter IV: Analysis and simulation of a real production system
65 Places Significance Places Significance Places Significance
P22 op 8
finishing
rectification
1 P44 operation P66 Availability of Robot 4
Table IV. 3 Significance of places P1 to P66
P1 – P16, Turning of B1,1
P21-P63 Grinding of B1,1

Places Significance Places Significance Places Significance
P67 Availability of
Robot 5 P89 operation P111 Availability of
AFCC 450
P68 Availability of
Robot 6 P90 Availability of R 242 P112 operation
P69 Availability of
Robot 7 P91 Intermediate place P113 Intermediate
place
P70 Availability of
Robot 8 P92 operation P114 operation
P71 Intermediate place P93 Availability of R 236 P115 Availability of
AGL315_G
P72 Operation P94 operation P116 operation
P73 Availability of
SHS28_OS P95 Availability of R242 P117 Availability of
AFCC 450
P74 Availability of
CNC_OCAR P96 Intermediate place P118 Intermediate
place
P75 operation P97 operation P119 operation
P76 Availability of
MK6751 P98 Availability of SASL
200 P120 Availability of
SIW5B_E
P77 Availability of
CNC_OCAR P99 operation P121 operation
P78
operation P100 Availability of SASL
5AD P122 Availability of
SWaIGL
450CNC
P79 Availability of FR.
X53K P101 Intermediate place P123 Intermediate
place
P80 operation P102 operation P124 operation
P81 Availability of
AJ_GA_OS P103 Availability of
SIW5B_E P125 Availability of
MA464_E
P82 transport P104 operation P126 operation
P83 Availability of
AGV P105 Availability of
SWaIGL 450CNC P127 Availability of
MRG 140
P84 loading P106 Intermediate place P128 operation
P85 Availability of
Robot 18 P107 operation P129 Availability of
ECOCA
MT312/500
P86 Intermediate place P108 Availability of
AGL315_E P130 operation

Chapter IV: Analysis and simulation of a real production system
66 P87 operation P109 operation P131 Availability of
MA464_E
P88 Availability of R
236 P110 Availability of SAW 6 P132 operation
Table IV. 4 Significance of places P67 to P132
P71 – P81 Turning B1,2
P86 – P146 Grinding B1,2

Places Significance Places Significance Places Significance
P133 Availability of
MRG 140 P155 Availability of OK
300 P177 Availability of SL 631
P134 operation P156 Availability of
TRC -100 P178 operation
P135 Availability of
ECOCA
MT312/500 P157 Availability of MK
248 P179 Availability of 3183
P136 Intermediate place P158 Availability of
L.KH.OSC P180 Intermediate place
P137 operation P159 operation P181 operation
P138 Availability of
AGL315_E P160 Availability of
KH300_W3 P182 Availability of LZ 259
P139 operation P161 operation P183 operation
P140 Availability of
SAW 4 P162 Availability of
KH300_W3 P184 Availability of MRS
650
P141 Intermediate
place P163 operation P185 Intermediate place
P142 operation P164 Availability of G
40_OS P186 operation
P143 Availability of
PRI 300 P165 operation P187 Availability of R 242
P144 operation P166 Availability of
AJ_GA_OS P188 operation
P145 Availability of
DISC_PE P167 Transport P189 Availability of
ICHIKAWA
P146 Intermediate
place P168 Availability of
AGV P190 Intermediate place
P147 Loading B1,2 for
assembling P169 loading P191 operation
P148 Availability of
Robots R41 P170 Intermediate place P192 Availability of 3183
P149 Loading B1,1 for
assembling P171 operation P193 operation
P150 B1 Finished P172 Availability of R
242 P194 Availability of SL 631
P151 Intermediate
place P173 operation P195 Intermediate place
P152 operation P174 Availability of R
236 P196 operation

Chapter IV: Analysis and simulat ion of a real production system
67 P153 operation P175 Intermediate place P197 Availability of LZ 259
P154 operation P176 operation P198 operation
Table IV. 5 Significance of places P133 to P198
P147 – P150 Assembling the two parts B1,1 and B1,2 to get the first piece B1
P151 – P166 Turning of B2,1 . P167 – P168 AGV transport B2,1 from turning workshop to the
grinding workshop , P170 – P217 Grinding of part B2,1

Places Significance Places Significance Places Significance
P199 Availability of
MRS 650 P221 Availability of
CNC_OCAR P243 operation
P200 Intermediate place P222 operation P244 Availability of SASL
200
P201 operation P223 Availability of
MK6751 P245 operation
P202 Availability of LZ
259 P224 Availability of
CNC_OCAR P246 Availability of 3183
P203 operation P225 operation P247 Intermediate place
P204 Availability of
6ASCE P226 Availability of
FR. X53K P248 operation
P205 operation P227 operation P249 Availability of
SIW5B_E
P206 Availability of
MRS 650 P228 Availability of
AJ_GA_OS P250 operation
P207 Intermediate place P229 Transport P251 Availability of SWaIGL
450CNC
P208 operation P230 Availability of
AGV P252 Intermediate place
P209 Availability of
3183 P231 Loading P253 operation
P210 operation P232 Intermediate
place P254 Availability of
AGL315_E
P211 Availability of SL
631 P233 operation P255 operation
P212 Intermediate place P234 Availability of R
236 P256 Availability of SAW 6
P213 operation P235 operation P257 Intermediate place
P214 Availability of R
242 P236 Availability of R
242 P258 operation
P215 operation P237
P259 Availability of
AGL315_G
P216 Availability of R
236 P238 operation P260 operation
P217 Intermediate place P239 Availability of R
236 P261 Availability of AFCC
450
P218 Intermediate place P240 operation P262 Intermediate place
P219 operation P241 Availability of R
242 P263 operation

Chapter IV: Analysis and simulation of a real production system
68 P220 Availability of
SHS28_OS P242 Intermediate
place P264 Availability of
SIW5B_E
Table IV. 6 Significance of places P199 to P264
P218 – P228 Turning of B2,2
P229 – P230 AGV transport B2,2 from turning workshop to the grinding workshop
P232 – P292 Grinding of part B2,2
P293 – P296 Assembling the two parts B2,1 and B2,2 to get the first piece B2

Places Significance Places Significance
P265 operation P287 Intermediate place
P266 Availability of SWaIGL
450CNC P288 operation
P267 Intermediate place P289 Availability of PRI 300
P268 operation P290 operation
P269 Availability of MA464_E P291 Availability of DISC_PE
P270 operation P292 Intermediate place
P271 Availability of MRG 140 P293 Loading B2,1 for
assembling
P272 operation P294 loading B2,2 for
assembling
P273 Availability of MT 312/500 P295 Availability of Robot R42
P274
P296 B2 finished
P1, P21, P26, P31,
P36, P41, P46, P53,
P58, P63, P71, P86,
P91, P96, P101,
P106, P113, P118,
P123,
P277, P136, P141,
P146,
P151, P170, P175,
P180, P185, P190,
P195, P200, P207,
P212, P217, P218,
P232, P237, 242,
P247, P252, P257,
P262, P267, P274,
P282, P287,P292,

Intermediate Place P297, P 298,
P299, P 300,
P301, P 302,
P303, P 304,
P305, P 306,
P307, P 308,
P309, P 310,
P311, P 312,
P313, P314,
P315, P316,
P317, P318 P319,
P320 , P321,
P322 , P323,
P324, P325

Availability of Robot s R9,
R10, R11, R12, R13, R14,
R15, R16, R17, R19, R 20
R21, R22, R23, R24, R 25,
R26, R 27, R28, R29, R30,
R31, R32, R33, R 34, R35,
R36, R37, R38,
P275 operation P281 Availability of MT 312/500
P276 Availability of MA464_E P283 operation
P277 Intermediate place P284 Availability of AGL315_E
P278 operation P285 operation
P279 Availability of MRG 140 P286 Availability of SAW 4
CNC
P280 operation P326, P327 Availability of Robots R 39,
R40
Table IV. 7 Significance of places P265 to P327

Chapter IV: Analysis and simulation of a real production system
69 IV.5.2 . Significance of transitions
Transitions Representation Transitions Representation
T1 Start B1,1 T10 End of previous operation and start of next
operation
T2 Start operation 1
for 1,1 T11 End of previous operation and loading of
P1,1 by the AGV
T3 Start operation 2
for 1,1 T12 Unloading of B1,1 and loading by the robot
T4 Start operation 3
for 1,1 T13 Unloading of B1,1 and start the next
operation

T5

End of previous
operation and
start of next
operation T14, T15,
T18, T19,
T22, T24,
T26, T27,
T30, T31,
T34, T35,
T36, T40,
T41, T44,
T45

Unload by the robot and start the next
operation

T6

End of previous
operation and
start of next
operation T16, T17,
T20, T21,
T23, T25,
T28, T29,
T32, T33,
T37, T38,
T39, T42,
T43, T43,
T46, T47

End of previous operation and load by
robot
T7 End of previous
operation and
start of next
operation
T8 End of previous
operation and
start of next
operation
T9 End of previous
operation and
start of next
operation
Table IV. 8 Signification of transitions Bloc 1 (B1.1)

Chapter IV: Analysis and simulation of a real production system
70
Transitions Representation Transitions Representation
T49 Start B1,2 T55 End of previous operation and loading of
B1,2 by the AGV
T50 Start operation
1 for B1,2 T56 Unloading of B1,2 and loading by the
robot
T51 Start operation
2 for B1,2 T57 Unloading of B1,2 and start the next
operation

T52

End of
previous
operation and
start the next
operation T58, T59, T62,
T63, T66, T67,
T70, T71 , T74,
T75, T76, T80,
T81, T84, T85,
T88, T89 , T98,
T90, T94, T95,
T96,
T100, T101
T104, T105

Unload by the robot and start the next
operation

T53

End of
previous
operation and
start the next
operation T60, T61
T64, T65
T68, T69
T72, T73
T77, T78
T79, T82
T83, T86
T87, T91
T92, T93,
T97, T98 , T99,
T102, T 103,
T106, T 107

End of previous operation and load by
robot
T54 End of
previous
operation and
start the next
operation
Table IV. 9 Signification of transitions Bloc 2 (B1.2)

Chapter IV: Analysis and simulation of a real production system
71 Transition Representation Transition Representation
T110 Start B2,2 T116 End of previous operation and loading of
B2,2 by the AGV
T111 Start operation
1 for B2,2 T117 Unloading of B2,2 and loading by the robot
T112 start operation
2 for B2,2 T118 Unloading of B1,2 and start the next
operation

T113

End of
previous
operation and
start the next
operation T119, T120
T123, T124
T127, T 128
T131, T132
T135, T136
T139, T 143
T124, T147
T148, T149
T153, T 154
T155, T159
T160, T164

Unload by the robot and start the next
operation

T114
End of
previous
operation and
start the next
operation T121 , T122
T125 , T126
T129 , T130
T133 , T134
T137 , T138
T141 , T142
T145 , T146
T150 , T151
T152 , T157
T158 , T161
T162 , T165 ,
T166

End of previous operation and load by robot
T115 End of
previous
operation and
start the next
operation
T116 End of
previous
operation and
loading of
B2,2 by the
AGV

Table IV. 10 Signification of transitions Bloc 3 (B2.2)

Chapter IV: Analysis and simulation of a real production system
72 Transition Representation Transition Representation
T168 Start B2,1 T177 End of previous operation and start of
next operation
T169 Start operation 1
for B2,1 T178 End of previous operation and loading
of B2,1 by the AGV
T170 Start operation 2
for B2,1 T179 Unloading of B2,1 and loading by the
robot
T171 Start operation 3
for B2,1 T180 Unloading of B2,1 and start the next
operation

T172

End of previous
operation and
start the next
operation T181, T182
T183, T185
T186, T189
T190, T193
T194, T197
T198, T201
T202, T205
T206, T207
T211, T212
T215, T216

Unload by the robot and start the next
operation

T173

End of previous
operation and
start the next
operation T183, T184,
T187 , T188,
T191 , T192,
T195 , T196,
T199 , T200,
T203 , T204,
T208 , T209,
T210 , T213,
T214 , T217,
T218

Unload by the robot and start the next
operation
T174 End of previous
operation and
start of next
operation
T175,
T176 End of previous
operation and
start of next
operation
Table IV. 11 Signification of transitions Bloc 4 (B2.1)

Chapter IV: Analysis and simulation of a real production system
73 transition Representation
T48 B1,1 (22230 CW33 -10) ready to assembly
T108 B1,2 (22230 MB -20) ready to assembly
T109 B1 go to stock
T167 B2,2 (22232 MB -20) ready to assembly
T219 B2,1 (22232 MBW33 -10) ready to assembly
T220 B2 go to stock
Table IV. 12 Signification of transitions Bloc 5 (assembling)
IV.6. MODEL VALIDATION AND RESULTS OF THE SIMULATION
In the validation of the model we will seek to define the properties of the model and the
evaluation of its performances, which will be useful to us to introduce some parameters in the
software which allows us to make the simulation.
Boundedness : All the places of the network are bounded so we deduce that the PN is
bounded. there is no accumulation in progress i n the production system.
Liveliness : All transitions are alive; there is no blockage, so the P N is alive.
State graph : The Petri net is not a state graph. If we want it to be a state graph, all
transitions must have exactly one input and one output, and th is is not the case in our model.
Event graph : The Petri Net is not an event graph. Because not all places have exactly
one input transition and one output transition
Persistent: the firing of one of two transitions does not prevent the firing of the other .
So, our model is persistent.
With the GreatSPN software, which allowed us to confirm a number of properties and
especially if there is no conflict in our model. The results obtained are as follows:
After the end of each operation, the resource will be ava ilable again for the next part,
the transitions T13 and T180 cannot fire simultaneously because of the shared robot, one token
can fire only one transition, the shared resource is live and reversible no matter how many
tokens are initially distributed in t he system .

Chapter IV: Analysis and simulation of a real production system
74 IV.7. AUGMENTATION OF THE MODEL
No matter how fast and efficient CNC machines is, they’re not infallible. They develop
problems and need maintenance just like any other type of machine or tool . No matter how well
you maintain your machines, how well you train your controllers or how carefully you care for
your tools, problems will still pop up. Some will be easy to solve, and some will be confusing,
leaving you wondering what could possibly be wrong.
To maintain the proper functioni ng of the system we must add maintenance models .

Figure IV. 15 A place with ℇ(p), T(p), and Tmax(P) in a Petri net
ℇ(p): the error information function, τ(p) elapsed time in a place, τmax(p) maximum
elapsed time in a place
ℇ (p) = 1: the normal execution of the Petri net takes place if there is at least one token
in the place p. Initially, ℇ(p)= 1, p in the Petri net controller.
ℇ(p)= 2: emergency shut down procedure starts if there is a token in this place p.
ℇ(p)= 3: the error is handled by executing a special part of the Petri net controller.
If no error takes place or an old error is detected through the sensor data then the net
will be executed without augmentation of this Petri net .

Chapter IV: Analysis and simulation of a real production system
75 We have the machine R242 tool is broken and the error is detected in the place P 24, then a
petri net block is added to the net.
The error processing procedure includes:
▪ P328 the machine waits for repair .
▪ P329 New tool available .
▪ P330 R242 Ready .
And three transition :
▪ T221 start of reparation
▪ T222 insert new tool
▪ T223 end of the reparation and the machine will be available again.

Figure IV. 16 Change tool of machine R242
The error information function ℇ (P24) =3, when this error is first occurred in this place.
The liveness, safeness and reversibility properties remain unchanged for the system. The
marking after the first step of the simulation shows that P( 25) = 0, P(328) = 1, P(329) = 4 and
P (330)=0, this means the start of execution of the task of the M aintenance (Figure IV. 16). with
the firing of the transition T 222 by the resource that will consumed at the first validation and
the consumed resource (New tool s) in the place P(3 29). The marking after the second step
shows the firing of the transition by a single token because the weight of the arc between P329
and T222 is equal to 1 .

Chapter IV: Analysis and simulation of a real production system
76 Machines like MRS650 and LZ259 (P35, P182) can do the same work, so it can be used to
double production and it can produce another type of part according to the order without any
effect to the main production . This type of machine can replace the other machine in case of
something goes wrong on it. The production keeps going whatever the time to repair it. By
adding a token on the new command 1 place (P331) we will switch the work from the
unavailable machine to the other machine to be shared between two operation.

Figure IV. 17 Switching the resource s
MRS650 (P35) is in repair, so it is not available for the operation, in this case we activate
the three command places (P331 , P333 and P335 ), LZ259 (P182) will be a shared machine to
grinding two types of bearing B1.1 and B2.1
P331 is a command place, it w ill be activated after the breakdown of MRS650 .
P333 is a command place, it is activated after the first command to prevent accumulation
of tokens in Place P182 .
P332 is a n intermediate place .
P334 the number of times LZ259 replace MRS650 .
P335 command pla ce, activated in case when MRS650 is unavailab le
In normal state, when MRS650 is available, P331 , P333 and P335 are unmarked.

Chapter IV: Analysis and simulation of a real production system
77 IV.8. CONCLUSION
We can conclude from this chapter which expresses the diversity of petri nets for the
modeling of production systems. The modeling of maintenance tasks is based on Petri nets, so
by this diversity we can model Production Systems with great complexity and the basic
principle developed is always valid. This part also expresses that the petri nets are a r eliable
tool that allow the modeling of the production systems, see the behavior of the system and the
different situations. Petri nets offer a simple graphic support for the representation, the
understanding and the synchronization of the tasks, the execu tion and the means necessary for
the interventions. These tasks can be either those of the production or those of the Maintenance.
The complexity of production systems requires us to put into practice or use software
that facilitates the manipulation of th is modeling. Maintenance modeling by petri nets has the
practical advantage of allowing the specification of a system's behavior in a form that can be
easily used by a design engineer. In other words, it makes it possible to carry out the evaluation
of the desired quantitative parameters, and to resolve conflicts related to resource sharing and
to estimate the operating time of the tasks.

General Conclusion
78 GENERAL CONCLUSION
The objective of this work was to suggest a modeling of the flexible systems of
production by Petri nets. To do this, our approach focused on two areas of work:
The first part of the work is composed of three chapters. It aims to provide an overview
of the state of the art, delimit the research context and present some work already done in the
field.
In the first chapter we presented the work environment by describing The University of
Dunarea de Jos of Galati and a general presentation of URB Group – Rulmenti S.A Barlad . In
the second chapter, Petri nets were presented as a set of tools for both modeling and analyzing
the dynamics of complex systems. They have the dual benefit of providing both a graphical
representation and the mathematical underpinnings for studying properties to evaluate the
behavior of modeled systems. the third chapter presents general notions associated with the
flexible system of production . In the last chapter we laid the foundations of our work by defining
the production system first. We have paid particular attention to the flexible production system
and th e notion of flexibility which are at the heart of our concerns. Subsequently, we chose
Petri nets as a modeling tool. In fact, unlike analytical models, petri nets offer the following
advantages:
Better process analysis because of its graphical representat ion.
A possibility of integration in a simulator .
The use of the properties of the Petri nets ( boundedness , mutual exclusion,
liveliness) ensures a representation of the problems of resource sharing, but also
to ensure the non -blocking of the simulation mo del.
The complexity of the production systems requires us to use software that facilitates the
manipulation of this modeling, that they are based on algorithms that help us to choose the type
of PN adaptable to our model and to verify the validation of the models and define the properties
of our PN. The use of Petri nets remains broader in the industrial field, they can be used to
implement real -time control systems, which can handle the tasks of production and maintenance
in case the system breaks down. We can say that PNs are modern, powerful, flexible and
efficient tool for modeling and simulating FMS.

General Conclusion
79 A Petri net simulator simulates execution of a Petri net, the flow of tokens in the places
of the net through transitions. Simulation gives a vivid graph ic description of a system's
operation to aid in model design and debugging. Simulation becomes necessary when the
performance cannot be predicted by the system .
This internship was not just a technical experience but also a human experience. Indeed,
it enlarged my mind and gave me another vision of living abroad, particularly in Romania. I
met several persons and I keep contact with them through social and professional networks.
I think this internship abroad will be an advantage for my future career because it g ave
me an international profile. And I want to work abroad during some years, in mechanical
engineering, so this internship will be beneficial for my future career.

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Annex 1
85 ANNEX 1
Simulation Software

Figure A1. 1 Software credits
GreatSPN (GRaphical Editor and Analyzer for Timed and Stochastic Petri Nets) is a
software package for the modeling, validation, and performance evaluation of distributed
systems using Generalized Stochastic Petri Nets and their colored extension, Stochastic Well –
formed Nets. The tool provides a friendly framework to experiment with timed Petri net based
modeling techniques. It implements efficient analysis algorithms to allow its use on rather
complex applica tions.
The GreatSPN Framework is licensed under the GPLv2.0 license, which is available
within the repository in the LICENSE. The source code owner is the University of Torino, Italy .
Ajmone Marsan, Balbo, Bobbio, Chiola .
Histoy:
➢ 1982 -1984 – SPN model
o Text interface, Pascal.
o Introduction of GSPN models .
➢ 1980s
o Integration of qualitative analyzes: invariants: semiflots of places,
transitions, syphons, traps, …
o Introduction of deterministic and type -phase distributions.

Annex 1
86 o Graphic interface .
➢ 1990s – high level models
o WN and SWN models
o Stochastic simulation (ordinary and symbolic)
➢ 2000s extensions by complements
o Extended SRG (partial symmetries, LIP6) .
o Temporal logic .
o Decomposition of SWN .
➢ Developed by the Dpt Performance Group. of computer science from the
University of Torino
o Partial symmetries, extensions, temporal logic: LIP6 .
o Composition: LISTIC, LAMSADE .
The interface of the software is shown in figure A1. 2.

Figure A1. 2 Graphical interface of the software

Annex 2
87 ANNEX 2
The collected data from URB GROUP – RULMENTI S.A BARLAD are used in the
modeling of the system and it is in the following figures :

Figure A2. 1 Turning B1 Data

Figure A2. 2 Grinding of B 1 Data
Turning B1,1 machines Turning of B1,2 machines
1909 Strunjire ebos plan/cdr L.KH.OSC 1916 Strunjire finis int.+eb. Pl+ext SHS28_OS
1909 Strunjire finis plan/ext./raza ext. L.KH.OSC 1916 Strunjire cdr+deg.+raze(prin int.) CNC_OCAR
1909 Strunjire finis plan/cdr/raze ext./int. L.KH.OSC 1916 Frezare laterala FR. X53K
1909 Strunjire canal W33 / raza int. KH300_W3 1916 Ajustare AJ_GA_OS
1909 Gaurire (inele W33) G 40_OS Varianta 1
1909 Ajustare (inele W33) AJ_GA_OS 1916 Strunjire plan/interior MK6751
Varianta 1 1916 Strunjire plan/exterior MK6751
1909 Strunjire finis plan/int. TRC-100 1916 Strunjire cdr+deg.+raze(prin int.) CNC_OCAR
1909 Strunjire finis plan/ext. TRC-100 1916 Frezare laterala FR. X53K
1909 Strunjire ebos cdr+finis cdr MK 248 1916 Ajustare AJ_GA_OS
1909 Strunjire canal W33 KH300_W3 1916 Marcare PAY63_OS
1909 Strunjire raze int./ext.(intoarcere) KH300_W3 1916 Control strunjire CTC_STR
1909 Gaurire (inele W33) G 40_OS 1916 Tratament termic EBNER
1909 Ajustare (inele W33) AJ_GA_OS Varianta 1
Varianta 2 1916 Tratament termic MD318
1909 Strunjire completa 1/2 OK 300 1916 Control final CTC_STT
1909 Strunjire completa 1/2 OK 300
1909 Gaurire (inele W33) G 40_OS
1909 Ajustare (inele W33) AJ_GA_OS
1909 Control CTC_STR
1909 Tratament termic EBNER
Varianta 1
1909 Tratament termic MD318
1909 Control final CTC_STT
Grinding of B1,1 machines Grinding of B1,2 machines
1790 Rectificare Finis plan R 236 2024 Rectificare Ebos plan R 236
Varianta 1 Rectificare Finis plan R 242 Varianta 1 Rectificare Ebos plan R 242
1790 Rectificare Ebos exterior SL 631 2024 Rectificare Finis plan R 236
Varianta 1 Rectificare Ebos exterior 3183 Varianta 1 Rectificare Finis plan R242
1790 Rectificare Ebos cdr LZ 259 2024 Rectificare Ebos guler exterior SASL 200
Varianta 1 Rectificare Ebos cdr MRS 650 Varianta 1 Rectificare Ebos guler exterior SASL 5AD
1790 Detensionare AIA 350 2024 Rectificare Ebos interior SIW5B_E
1790 Rectificare Semifinis exterior SASL 5AD Varianta 1 Rectificare Ebos interior SWaIGL 450CNC
Varianta 1 Rectificare Semifinis exterior SASL 200 2024 Rectificare Ebos cdr AGL315_E
1790 Rectificare Finis cdr LZ 259 Varianta 1 Rectificare Ebos cdr SAW 6
Varianta 1 Rectificare Finis cdr MRS 650 Varianta 2 Rectificare Ebos cdr AFCC 450
1790 Rectificare Superfinis cdr LZ 259 2024 Detensionare AIA 350
Varianta 1 Rectificare Superfinis cdr 6ASCE 2024 Rectificare Finis guler exterior AGL315_G
Varianta 2 Rectificare Superfinis cdr MRS 650 Varianta 1 Rectificare Finis guler exterior AFCC 450
1790 Rectificare Finis exterior SASL 5AD 2024 Rectificare Finis interior SIW5B_E
Varianta 1 Rectificare Finis exterior SASL 200 Varianta 1 Rectificare Finis interior SWaIGL 450CNC
1790 Rectificare Rodaj plan R 236 2024 Rectificare Finis guler mare MA464_E
Varianta 1 Rectificare Rodaj plan R 242 Varianta 1 Rectificare Finis guler mare MRG 140
1790 Demagnetizare DEMAG_1 Varianta 2 Strunjire dura ECOCA MT312/500
1790 Spalare MA 654 2024 Rectificare Finis guler mic MA464_E
1790 Control final CTC_REC Varianta 1 Rectificare Finis guler mic MRG 140
Varianta 2 Strunjire dura ECOCA MT312/500
2024 Rectificare Finis cdr AGL315_E
Varianta 1 Rectificare Finis cdr SAW 4
2024 Rectificare Superfinis cdr PRI 300
2024 Rectificare Slefuire plana DISC_PE
2024 Demagnetizare DEMAG_1
2024 Spalare MA 654
2024 Control final CTC_REC

Annex 2
88
Figure A2. 3 Turning of B2 Data

Figure A2. 4 Grinding of B2 Data
Turning of B2,1 Machines Turning of B2,2 Machines
8408 Strunjire ebos plan/cdr L.KH.OSC 9212 Strunjire finis int.+eb. Pl+ext SHS28_OS
8408 Strunjire finis plan/ext./raza ext. L.KH.OSC 9212 Strunjire cdr+deg.+raze(prin int.) CNC_OCAR
8408 Strunjire finis plan/cdr/raze ext./int. L.KH.OSC 9212 Frezare laterala FR. X53K
8408 Strunjire canal W33 / raza int. KH300_W3 9212 Ajustare AJ_GA_OS
8408 Gaurire (inele W33) G 40_OS Varianta 1
8408 Ajustare (inele W33) AJ_GA_OS 9212 Strunjire plan/interior MK6751
Varianta 1 9212 Strunjire plan/exterior MK6751
8408 Strunjire finis plan/int. TRC-100 9212 Strunjire cdr+deg.+raze(prin int.) CNC_OCAR
8408 Strunjire finis plan/ext. TRC-100 9212 Frezare laterala FR. X53K
8408 Strunjire ebos cdr+finis cdr MK 248 9212 Ajustare AJ_GA_OS
8408 Strunjire canal W33 KH300_W3 9212 Marcare PAY63_OS
8408 Strunjire raze int./ext.(intoarcere) KH300_W3 9212 Control strunjire CTC_STR
8408 Gaurire (inele W33) G 40_OS 9212 Tratament termic EBNER
8408 Ajustare (inele W33) AJ_GA_OS Varianta 1
Varianta 2 9212 Tratament termic MD318
8408 Strunjire completa 1/2 OK 300 9212 Control final CTC_STT
8408 Strunjire completa 1/2 OK 300
8408 Gaurire (inele W33) G 40_OS
8408 Ajustare (inele W33) AJ_GA_OS
8408 Control CTC_STR
8408 Tratament termic EBNER
Varianta 1
8408 Tratament termic MD318
8408 Control final CTC_STT
Grinding of B2,1 Machines Grinding of B2,2 Machines
7202 Rectificare Ebos plan R 242 7263 Rectificare Ebos plan R 236
Varianta 1 Rectificare Ebos plan R 236 Varianta 1 Rectificare Ebos plan R 242
7202 Rectificare Ebos exterior SL 631 7263 Rectificare Finis plan R 236
Varianta 1 Rectificare Ebos exterior 3183 Varianta 1 Rectificare Finis plan R 242
7202 Rectificare Ebos cdr LZ 259 7263 Rectificare Ebos guler exterior SASL 200
Varianta 1 Rectificare Ebos cdr MRS 650 Varianta 1 Rectificare Ebos guler exterior 3183
7202 Detensionare AIA 350 7263 Rectificare Ebos interior SIW5B_E
7202 Rectificare Finis plan R 242 Varianta 1 Rectificare Ebos interior SWaIGL 450CNC
Varianta 1 Rectificare Finis plan ICHIKAWA 7263 Rectificare Ebos cdr AGL315_E
7202 Rectificare Semifinis exterior 3183 Varianta 1 Rectificare Ebos cdr SAW 6
Varianta 1 Rectificare Semifinis exterior SL 631 7263 Detensionare AIA 350
7202 Rectificare Finis cdr LZ 259 7263 Rectificare Finis guler exterior AGL315_G
Varianta 1 Rectificare Finis cdr MRS 650 Varianta 1 Rectificare Finis guler exterior AFCC 450
7202 Rectificare Superfinis cdr LZ 259 7263 Rectificare Finis interior SIW5B_E
Varianta 1 Rectificare Superfinis cdr 6ASCE Varianta 1 Rectificare Finis interior SWaIGL 450CNC
Varianta 2 Rectificare Superfinis cdr MRS 650 7263 Rectificare Finis guler mare MA464_E
7202 Rectificare Finis exterior 3183 Varianta 1 Rectificare Finis guler mare MRG 140
Varianta 1 Rectificare Finis exterior SL 631 Varianta 2 Strunjire dura MT 312/500
7202 Rectificare Rodaj plan R 242 7263 Rectificare Finis guler mic MA464_E
Varianta 1 Rectificare Rodaj plan R 236 Varianta 1 Rectificare Finis guler mic MRG 140
7202 Demagnetizare DEMAG_1 Varianta 2 Strunjire dura MT 312/500
7202 Spalare MA 654 7263 Rectificare Finis cdr AGL315_E
7202 Control final CTC_REC Varianta 1 Rectificare Finis cdr SAW 4 CNC
7263 Rectificare Superfinis cdr PRI 300
7263 Rectificare Slefuire plana DISC_PE
7263 Demagnetizare DEMAG_1
7263 Spalare MA 654
7263 Control final CTC_REC