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Performance analysis of a manufacturing system using Petri net

Performance analysis of a manufacturing system using Petri net. 2001. 08. 25. MAILAB 이 기 창. Introduction. Characteristics of current industrial context(Berrah) An unstable and exacting demand A more acute competition Partnerships based on design of products as well as production

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Performance analysis of a manufacturing system using Petri net

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  1. Performance analysis of a manufacturing system using Petri net 2001. 08. 25. MAILAB 이 기 창

  2. Introduction • Characteristics of current industrial context(Berrah) • An unstable and exacting demand • A more acute competition • Partnerships based on design of products as well as production -> Importance of the vision and continuous improvement based on performance analysis • A model to control a system(Dyson) • Mechanism of performance measure • Target • Resource • Control procedure

  3. Conceptual performance management framework • Enterprise model (description) • Performance measure (evaluation) • Factors of improvement (decision making) • Action plans (launching) Strategy Development Objectives Description Enterprise model Evaluation and Analysis Item Resource Activity Petri net

  4. Achieving manufacturing business integration through the combined formalism of CIMOSA and Petri nets Marcos Wilson C. Aguiar* and John M. Edwards** *Arthur D. Little, Brazil **MSI Research Institute, Dep. of Manufacturing Engineering, Loughborough University of Technology, UK. International Journal of Production Research, 1999, Vol.37, No. 8, 1767-1786

  5. Enterprise integration • Need a single set of models used to enable modeling and simulation • Enterprise integration • Engineering enterprises as complex systems that operate in an even more complex environment • Achieving coordination among system components • Two types of support of particular importance • Knowledge capture (model building) • Knowledge manipulation (model execution)

  6. Outline of SEW-OSA • CIMOSA • A general architecture for enterprise modeling that can be used to derive a specific architecture for a particular enterprise • A modeling framework, a modeling language, integrating infrastructure • SEW-OSA(Systems Engineering Workbench – Open Systems Architecture) • Produced by MSI(Manufacturing Systems Integration) Research Institute at Loughborough University • Combines CIMOSA, generalized stochastic Petri nets, predicate-action Petri nets, object-oriented design, CIM-BIOSYS(CIM Building Integrated Open SYStems) integrating infrastructure • The principal formalism is CIMOSA

  7. SEW-OSA – a Conceptual View

  8. SEW-OSA • Model building capability • Associates business process and object-oriented descriptions in order to produce a complete business model • CIMOSA constructs : Domain process / business process / enterprise activity • Predicate-action Petri nets : functional transformation of enterprise activity • Model execution capability • Simulation : GSPN(Generalized stochastic Petri net) • Probability distribution defined for each time interval • Rapid prototyping • Supports configuration of the physical system by supporting gradual replacement of its emulated components by physical ones

  9. Overall Methodology for Modeling and Simulation

  10. From CIMOSA models to Petri nets • Business model is converted by SEW-OSA to GSPN automatically. • GSPN representation is used so that simulation can be performed and performance parameters obtained. CIMOSA Petri net

  11. From CIMOSA models to Petri nets CIMOSA Petri net

  12. Example of a Petri net for a fragment of a context diagram

  13. Analysis and Simulation • ARP • Petri net software developed by the LCMI/UFSC • Analysis : invariant analysis, qualitative analysis, analysis of state • Simulation : executing Petri net step by step • Performance evaluation • Case study • SMT(Surface Mount Technology) PCB assembly line at UK PCB assembly company

  14. Analysis and Simulation • Case study (cont’d) • Parameters monitored • Manufacturing lead time • Levels of work-in-progress • Levels of utilization of various resources • Issues of importance • Identification of critical resource constraints • Control over operations for which execution time can vary • Impact that certain configuration decisions can have upon manufacturing lead time • Results • Performance parameters as a function of operating rate (inspection, checking, assembly)

  15. Summary • Showed how CIMOSA models can be used to analyze and simulate issues that are relevant to design decisions • Demonstrated how Petri nets could be used in conjunction with CIMOSA • By a detailing mapping between behavioral modeling construct of the CIMOSA and GSPN • Explained a set of tools that allow system developer to use CIMOSA models for simulation and rapid prototyping

  16. A study on the decision support framework for the formulation of manufacturing strategies using Petri net Kichang Lee MAILAB

  17. Objective • To support modeling a manufacturing system • Using both process and information model • To analyze the modeled manufacturing system • Using analytical method • To evaluate a system configuration • Using both logistics and financial measure • To propose a decision support function • By comparing alternative system configurations

  18. Decision support framework • Assumptions • The transportation time between activities is zero. • Raw and purchase materials are always available. • Item input interval, activity processing time and demand arrival interval follow an exponential distribution. • Alternative routing is selected based on predefined probability. • Resource is allocated based on predefined probability • Manufacturing system consists of items, resources and activity objects. • Three modules of the framework • System modeling module • Transformation module • Performance analysis module

  19. System modeling module • Three classes comprising a system • Item object : item group, item master • Resource object : resource type, functionality and availability • Activity object : business process or enterprise activity in CIM-OSA construct

  20. A 1 Transformation module • Single activity and corresponding Petri net T3 P2 P4 Resource Module Activity Item a Item b P1 P3 P5 T1 T2 Processing Module Resource k Demand Module

  21. Transformation module

  22. Transformation module

  23. A 1 A 2 A 3 A 1 A 2 A 3 & & Transformation module A2 A1 A3 CO-PRODUCE A1 A3 A2 ASSEMBLY

  24. Transformation module • Transformed Petri net (GSPN)

  25. Transformation module • Resource sharing • Each Petri net is constructed for each end item. • Separate Petri nets interact with one another by shared resources • The firing rate of the resource module represents the rate of the event that a shared resource is allocated to another Petri net. • Notations for representing resource sharing

  26. Transformation module • Deduction of the firing rate of resource module k Total processing time Processing time of processing module k Time interval that is not allocated to processing module k firing rate of resource module k

  27. Properties of Transformed Petri net • Satisfy the conditions for GSPN to have steady state probability • Firing rates should not depend on time parameters. • The GSPN should be bounded. • The GSPN should be dead-lock free. • The GSPN should be reversible.

  28. Performance analysis module • Procedure of performance analysis • Performance is computed based on steady state analysis for the Petri nets. • From the steady state probability, production throughput can be obtained. • From production quantity and activity usage information, the manufacturing cost for each item can be estimated. • Direct cost • Direct material cost = unit material cost  throughput  operating period • Direct resource cost = unit resource cost  throughput  operating period • Indirect cost • Indirect cost = activity setup cost (charged per activity) + activity usage cost (charged per activity usage time)

  29. Example • The example company • The company manufactures batteries in material handling devices and various kinds of carts. • The manufacturing process consists of casting, plate, cell assembly and battery assembly. • The end items are grouped into material handling batteries(MHB), personal cart batteries(PCB), equipment batteries(EQB), according to the final usage type • Six scenarios • Scenario 1 : All end items and subassemblies are produced in the company. • Scenario 2 : MHB cells are outsourced. • Scenario 3 : PCB cells are outsourced. • Scenario 4 : EQB cells are outsourced. • Scenario 5 : A cell assembly resource is added. • Scenario 6 : A battery assembly resource is added.

  30. IDEF3 model

  31. Petri net for MHB

  32. Experimental results • The time consumed to compute the steady state probability of one separated Petri net is 15 seconds in average. • In case of a single combined Petri net, the steady state could not be obtained due to system memory limitation. • Production throughput for each system scenario

  33. Experimental results Cost analysis for MHB Cost analysis for PCB

  34. Experimental results Cost analysis for EQB Total profit for each scenario

  35. Conclusion • The research provides a framework under which a manufacturing system is modeled and analyzed in the performance perspective. • Object model to represent objects and to describe business process in general manufacturing environment is presented. • A procedure to transform a process model into GSPN is formally defined. • To reduce computational complexity, Petri nets are separately constructed for each end item using resource sharing representation. • The proposed methodology could be used to support strategic and operational design decisions for outsourcing, product mix, capacity allocation, bottleneck management, scenario comparison, etc.

  36. References • L. Berrah, G. Mauris, A. Haurat, L. Foulloy, “Global vision and performance indicators for an industrial improvement approach”, Computers in Industry, 2000, Vol. 43, 211-225. • R.G. Dyson, “Strategy, performance and operational research”, Journal of the Operational Research Society, 2000, Vol. 51, 5-11. • K. Santarek, I.M. Buseif, “Modeling and design of flexible manufacturing systems using SADT and Petri net tools”, Journal of Materials Processing Technology, 1998, Vol. 76, 212-218 • M. Jeng, X. Xie and W.Y. Hung, “Markovian timed Petri nets for performance analysis of semiconductor manufacturing systems”, IEEE Transactions on Systems, Man, and Cybernetics-Part B, 2000, Vol. 30, No. 5, 757-771

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