Modeling and Performance Evaluation of a Multistage Serial Manufacturing System Considering Rework and Product Polymorphism

doi:10.3901/JME.2017.18.191

Abstract

Abstract: Modeling and performance evaluation of a multistage serial manufacturing system with consideration of rework and products polymorphism is focused. In addition to considering equipment failure, the impacts of products rework and scrap, processing differences resulting from products polymorphism are emphasized. To solve the problem that the system model cannot accurately describe the complex state change resulting from the conversion of internal product flows, which is formulated by traditional methods based on Markov model or queuing network, a modular modeling approach based on extended stochastic Petri nets (ESPN) is presented. The state space is got by building the embedded Markov chain based on the ESPN model. Relative excitation probability distribution of all processing statuses is inferred from station first pass yield. Therefore, the analysis of two-stage serial manufacturing system using Markov chain theory is presented. Furthermore, considering that both sides of system have the impact on the cell model, an overlapping decomposition method is employed for iterative solution of the model of multistage serial manufacturing system, and the performance index of the system are also discussed. An automotive powertrain assembly line is taken as an example to verify the effectiveness of the model and the validity of the analysis method.

Key words: extended-stochastic Petri nets, multistage serial manufacturing system, overlapping decomposition method, performance evaluation, product polymorphism, rework

CLC Number:

TH165

ZHANG Heng, LI Aiping, LIU Xuemei, XU Liyun. Modeling and Performance Evaluation of a Multistage Serial Manufacturing System Considering Rework and Product Polymorphism[J]. Journal of Mechanical Engineering, 2017, 53(18): 191-201.

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