The robustness of scheduling policies in multi-product manufacturing systems with sequence-dependent setup times and finite buffers

In this paper, a continuous time Markov chain model is introduced to study multi-product manufacturing systems with sequence-dependent setup times and finite buffers under seven scheduling policies, i.e., cyclic, shortest queue, shortest processing time, shortest overall time (including setup time and processing times), longest queue, longest processing time, and longest overall time. In manufacturing environments, optimal solution may not be applicable due to uncertainty and variation in system parameters. Therefore, in this paper, in addition to comparing the system throughput under different policies, we introduce the notion of robustness of scheduling policies. Specifically, a policy that can deliver good and stable performance resilient to variations in system parameters (such as buffer sizes, processing rates, setup times, etc.) is viewed as a “robust” policy. Numerical studies indicate that the cyclic and longest queue policies exhibit robustness in subject to parameter changes. This can provide production engineers a guideline in operation management.

[1]  H. T. Papadopoulos,et al.  Queueing theory in manufacturing systems analysis and design: A classification of models for production and transfer lines , 1996 .

[2]  Hideaki Takagi,et al.  Analysis and Application of Polling Models , 2000, Performance Evaluation.

[3]  Kazuhiro Saitou,et al.  Robust design of flexible manufacturing systems using, colored Petri net and genetic algorithm , 2002, J. Intell. Manuf..

[4]  Yves Dallery,et al.  Manufacturing flow line systems: a review of models and analytical results , 1992, Queueing Syst. Theory Appl..

[5]  Yadati Narahari,et al.  Performance modeling of automated manufacturing systems , 1992 .

[6]  Dennis E. Blumenfeld,et al.  Production system design for quality robustness , 2008 .

[7]  Young Jae Jang Mathematical modeling and analysis of flexible production lines , 2007 .

[8]  Jingshan Li,et al.  Throughput analysis of production systems: recent advances and future topics , 2009 .

[9]  L. Shi,et al.  Performance Modeling of Automated Manufacturing Systems, N. Viswanadham and Y. Narahari, Prentice‐Hall, Englewood Cliffs, U.S.A., 1992. Price: £45.95. ISBN 0‐13‐658824‐7, xvi+592pp. , 1999 .

[10]  John A. Sharp,et al.  A review of manufacturing flexibility , 2000, Eur. J. Oper. Res..

[11]  Ningjian Huang,et al.  Modelling and analysis of a multiple product manufacturing system with split and merge , 2005 .

[12]  Tayfur Altiok,et al.  Decentralized multi-product multi-stage systems with backorders , 2008 .

[13]  Jingshan Li,et al.  Approximating feeder line reliability statistics with partial data collection in assembly systems , 2005, Comput. Ind. Eng..

[14]  Georg N. Krieg,et al.  A decomposition method for multi-product kanban systems with setup times and lost sales , 2002 .

[15]  John A. Buzacott,et al.  Stochastic models of manufacturing systems , 1993 .

[16]  Andrea Matta,et al.  Performance evaluation of linear and non-linear multi-product multi-stage lines with unreliable machines and finite homogeneous buffers , 2008 .

[17]  Tayfur Altiok,et al.  Pull-type manufacturing systems with multiple product types , 2000 .

[18]  Li Zheng,et al.  Multi-product manufacturing systems with sequence-dependent setups: Performance evaluation and system properties , 2011, 2011 IEEE International Conference on Automation Science and Engineering.

[19]  Georg N. Krieg,et al.  Analysis of Multi-Product Kanban Systems with State-Dependent Setups and Lost Sales , 2004, Ann. Oper. Res..

[20]  A. Dasci,et al.  Performance evaluation of a single-stage two-product manufacturing system operating under pull-type control , 2008, Comput. Oper. Res..

[21]  MengChu Zhou,et al.  Modeling, Simulation, and Control of Flexible Manufacturing Systems - A Petri Net Approach , 1999, Series in Intelligent Control and Intelligent Automation.

[22]  Jumpol Vorasayan,et al.  Allocating work in process in a multiple-product CONWIP system with lost sales , 2005 .

[23]  Yun Kang,et al.  Information inaccuracy in inventory systems: stock loss and stockout , 2005 .

[24]  Asoo J. Vakharia,et al.  A robust design methodology for Kanban system design , 1997 .

[25]  J. A. Buzacott,et al.  Flexible manufacturing systems: a review of analytical models , 1986 .

[26]  Dailun Shi,et al.  A survey of manufacturing flexibility: Implications for e-business flexibility , 2003, IBM Syst. J..

[27]  S. David Wu,et al.  Transfer line design with uncertain machine performance information , 2000, IEEE Trans. Robotics Autom..

[28]  Ananth Krishnamurthy,et al.  Performance evaluation of a multi-product system under CONWIP control , 2008 .