Potentials of Petri nets for Availability Modeling and Analysis

1. Potentials of Petri nets for Availability Modeling and Analysis

2. Outline • Introduction • Availability Modeling • Analysis and Prediction • Software Tool: REALIST • Large and Complex Systems • Application Example • Summary & Conclusions

3. Introduction

4. Motivation Availability Modeling and Analysis ProductionProcess Structure & States Operations Functions Availability Costs Maintenance & Logistics Reliability Dependencies • Numerous interactions, extremely complex system description

5. Motivation • Prediction of operational availability • Decision between alternatives: • Operation strategy • Production process • System configurations • Reliability demands • Maintenance strategy • Logistics concepts • Necessary: Powerful methods for availability analysis and prediction

6. Availability Modeling

7. Availability Modeling and Analysis Availability Modeling and Analysis Modeling Analysis & Prediction

8. Overview and Comparison of Modeling Methods Modeling methods Combinatorial models Queue oriented models State-space oriented models B 1 B 2 B 3 B n • Markov state graphs • Petri nets • Reliability block diagram • Fault tree • Queues B 4 machine failure machine is intact and is working machine under repair machine is intact but shut down quality control loading unloading rework component ok durability spare parts depot component failure and under repair Time to repair

9. Extended Stochastic Petri Net (ESPN) • Statical elements • Places (States, Objects) • Transitions (Time & Logic) • Arcs (Relations, Structure) • Dynamical description • Marking • Activation (or deactivation) • Switching • Initial marking • Sequence of activating (or deactivating) and switching results in marking changes component operable lifetime τin,L spare partsdepot τin,R componentsfailedandunderrepair time torepair Few basic elements: great flexibility in modeling

10. Extended Coloured Stochastic Petri Net (ECSPN) 1`(0,0, 2) [X_1 = 1 AND X_Sys = 0] passive Extensions • Markings with complex information(„Colour“ = Data type) • Activation condition and switching rule are colour dependent • Special elements and switching processes • State behaviour with ageing • Queuing discipline • Degree of renewal • Operational costs active 0 1`(AgeDis(tr1), m) 1`(k, m) Π = 3 p1 tr2 p2 Comp Comp Cost_P, 400 Passivation Cost_OP, 1200 1`(k, m) 1`(k, m) AgeEn = k AgeEn = k Wb Wb Lifetimepassive Lifetimeactive failed / negotiable AgeIn AgeIn t t | p 1`(AgeFire, m) 1`(AgeFire, m) tr1 p3 Comp tr3 Priority = m Priority = m Set(X_1 = 0) Set(X_1 = 0) 1`(k, m) Spare parts depot Maintenance personnel Wb Time torepair 3`(2) + 2`(4) 1`(2) AgeMem t 1`(sp) 1`(mp) p4 SP tr4 [sp = 1 AND mp = 2] p5 MP Cost_R, 580 1`(0,2*k, m) Set(X_1 = 1) active 1`(0,0, 2) rp1/p1 Comp Cost_OP, 1200

11. Extended Coloured Stochastic Petri Net Reliability Block Diagram Conjoint System Modeling (CSM) • Hybrid system model • ECSPN state space oriented • Reliability structure is not directly representable • System state complex • Reliability Block Diagram (RBD) favorable for reliability structure ConjointSystem Model • Presentation of various aspects using the optimal modeling technique in each case

12. Hierarchy of Modeling Methods Conjoint System Model (CSM) Extended Coloured Stochastic Petri Nets (ECSPN) Extended Stochastic Petri Nets (ESPN) Fault Tree Reliability block diagram (RBD) Queue (Q) Petri nets Markov state graphs (MG) Combinatorial models Queue oriented models State-space oriented models

13. CSM/ECSPN – Modeling capability General • Concurrency/Synchronization • Chronological sequences • Competition • Logic conditions • Queuing behavior • Timed/Stochastic system behavior • Dynamic changing system behavior • Fuzzy input data

14. CSM/ECSPN – Modeling capability LHC-Operation • Operation schedule • Mission profile • Operation • Material flow • Information flow • Production structure • Queuing behavior • Priorities • Production dependencies Production Beam Generation & Experiments • Reliability structure • System and component states • Constant failure rates • Time-dependent failure rates • Dynamic changing failure behavior • Aging • Several operative states* • Failure dependencies • System & Reliability LHC systems & components * with time-dependent failure or transition rates

15. CSM/ECSPN – Modeling capability • Functional states • Functional sequences • Functional logics • Functional dependencies • Functions Monitoring & Protection System • Corrective and preventive maintenance • Inspections and sensor-based condition monitoring • Time-dependent transition rates • Degree of renewal* • Spare part logistics • Limited maintenance capacities • Maintenance dependencies Maintenance & Logistics Maintenance & Logistics • Duration-based costs • Number-based costs • Variable Costs/Revenues Costs Budget constraints * with time-dependent failure or transition rates

16. Aspects of modeling System Model - Close to Reality User/Operator Production Process System Level Functions Comprehensive stochastic system model Cost level Component Level Maintenance Level Logistics Level External Resources

17. Analysis and Prediction

18. Dependability Characteristics Inherent Characteristics • Operation schedule • Production process • Reliability structure • Functions • Availability • Reliability • Reparability/Maintainability • Inspectability Operational Characteristics • Operability • Productivity • Availability • Reliability • Functionality • Reparability/Maintainability • Inspectability • Maintenance Delay Time • Logistic Delay Time • Level of Service User/Operator Production Process System Level Functions Component Level Maintenance Level Logistics Level Evaluation underoperatingconditions(withdependencies) Independent processes, structures, componentsandstates External Resources Input Information Output Information

19. Software Tool: REALIST

20. Modelling and Simulation Package REALIST* Manyfold Applications Numerous Analysis Options Versatile Modeling Aspects ProductionProcess Structureand States Functions Operations Modelling Analysis Reliability REALIST Modeling andSimulation Package Costs High Level Petri Net Monte CarloSimulation Availability Costs Reliability Maintenance & Logistics C(t) Dependencies R(t) A(t) Modeling and Analysis of complex technical systems “without” limitations! *) REALIST = Reliability, Availability, Logistics and Inventory Simulation Tool

21. Modeling and Simulation Package REALIST • Management of simulation projects • Automated implementation of simulation projects • Analysis and processing of result data • Creation of the system model as ESPN, ECSPN or CSM • Modularisation the presentation in pages Comfortable development and efficient analysis of a system model

22. Large and Complex Systems

23. Complexity of the Model Measures to support modeling: • Decomposition • Application of sub-models • Application of extended sub-models • Conjoint modeling • Generic model design (automatic generation) Measures to reduce simulation time: • Parallelization • Focusing

24. Application Examples

25. Range of Application From single component up to comprehensive system

26. Application Example – Production system Boundary conditions: • 9 different product variants • Entire manufacturing process (15 process steps)including quality control and rework • Reliability based on concurrent failure modes • Maintenance process including preventive and corrective actions • Several cost drivers e.g. material, energy, personnel, … Main analysis objectives: • Different maintenance strategies and costs • Probability of shortfall for the production unit target (based on availability) Production system: band saw blade fabrication

27. System Model – Production system Entire model Reliability model of machine A • 3 concurrent failure modes • Initiation/administration of repair process

28. 50 41.28 40 30 20 13.88 10 5.96 3.69 2.89 2.64 2.56 3 0 0 9 12 18 24 36 optimized strategy Results – Production system Main analysis results: • Maintenance strategy • Probability of shortfall for the production unit target (based on availability) Shortfall probability for contracted production volume of 7000 units/year Production system: band saw blade fabrication • Maintenance strategy and costs: • Strategy “24” PMs: 562,170 €/year • Strategy “36” PMs: 567,910 €/year • “Optimized Strategy”: 557,200 €/year Numberofexperiments/year Shortfall Probabiliy [%] Maximum Budget constraints Number of PM‘s per year

29. Summary & Conclusions

30. Summary & Conclusions • Presented powerful modeling methods are able to consider various modeling aspects • Conjoint system model based on Petri net yields the maximum modeling power and is able to consider manifold dependencies and reciprocal effects • Analyzed operational parameters are an integral base for the development of availability (predictions, comparisons, optimizations, …) • Large systems require support in modeling and analysis • Availability modeling and analysis based on Petri nets offers a great potential for CERN

31. peter.zeiler@ima.uni-stuttgart.de Thankyouforyourattention!