Efficient Simulation Method for General Assembly Systems With Material Handling Based on Aggregated Event-Scheduling

Performance evaluation of complex manufacturing systems is challenging due to many factors such as system complexity, parameter uncertainties, problem size, just to name a few. In many cases when a system is too complex to model using mathematical formulas, simulation is used as an effective alternative to conduct system analysis. A manufacturing system is a good example of such cases where both system performance and system complexity are greatly impacted by material handling (MH) strategy, management, and operational control. In this paper, we study vehicle general assembly (GA) system with MH, and focus on developing an efficient simulation method for modeling and analysis where traditional simulation methods may suffer from computation intensity. Making use of the partial system decomposability, we introduce an aggregated event-scheduling simulation method with two-level framework. A dividing mechanism with boundary conditions is employed in top-level simulation to divide the global event list into small sizes. A timing-focuses strategy based on max-plus algebra is applied in bottom-level local simulation to further reduce local event lists. With this new method it is possible to mimic real production systems fast and accurately within a reasonable computational time frame. The effectiveness and efficiency of the new simulation method are validated through experimental results.

[1]  Y. Ho,et al.  Models of discrete event dynamic systems , 1990, IEEE Control Systems Magazine.

[2]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[3]  Sameer Kumar,et al.  Capacity design: an application using discrete-event simulation and designed experiments , 2006 .

[4]  Wen-Jing Hsu,et al.  Parallel Discrete Event Simulation: A Survey , 2007 .

[5]  Stanley B. Gershwin,et al.  Manufacturing Systems Engineering , 1993 .

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

[7]  Albert T. Jones,et al.  Enterprise simulation: a hybrid system approach , 2005, Int. J. Comput. Integr. Manuf..

[8]  Abraham Grosfeld-Nir,et al.  A simulation study of pull systems with ascending/descending buffers and stochastic processing times , 2005 .

[9]  Gerald Weigert,et al.  Optimization of manufacturing processes by distributed simulation , 2006 .

[10]  Kenth Lumsden,et al.  Impact of Real‐time Information for Scheduling a Car‐body Shop – A Simulation Study , 1994 .

[11]  Richard M. Fujimoto,et al.  Conservative synchronization of large-scale network simulations , 2004, 18th Workshop on Parallel and Distributed Simulation, 2004. PADS 2004..

[12]  R. Sridharan,et al.  Simulation modeling and analysis of tool sharing and part scheduling decisions in single-stage multimachine flexible manufacturing systems , 2007 .

[13]  Paolo Faraboschi,et al.  An Adaptive Synchronization Technique for Parallel Simulation of Networked Clusters , 2008, ISPASS 2008 - IEEE International Symposium on Performance Analysis of Systems and software.

[14]  B. M. Beamon,et al.  Performance, reliability, and performability of material handling systems , 1998 .

[15]  Mingyuan Chen,et al.  A simulation study of flexible manufacturing systems , 1995 .

[16]  René David,et al.  Discrete event dynamic systems , 1989 .

[17]  Edward J. Williams,et al.  Analysis of conveyor systems within automotive final assembly , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[18]  Felix T.S. Chan,et al.  Using simulation to predict system performance: a case study of an electro‐phoretic deposition plant , 1995 .

[19]  Jeffrey S. Smith,et al.  Survey on the use of simulation for manufacturing system design and operation , 2003 .

[20]  Gilbert Laporte,et al.  Loop based facility planning and material handling , 2002, Eur. J. Oper. Res..

[21]  Robert R. Inman,et al.  EMPIRICAL EVALUATION OF EXPONENTIAL AND INDEPENDENCE ASSUMPTIONS IN QUEUEING MODELS OF MANUFACTURING SYSTEMS , 1999 .

[22]  David W. Bauer,et al.  Optimistic parallel discrete event simulation of the event-based transmission line matrix method , 2007, 2007 Winter Simulation Conference.

[23]  Geoff Buxey,et al.  Simulation studies of conveyor-paced assembly lines with buffer capacity , 1976 .

[24]  Guihai Chen,et al.  CMSA: A Method for Construction and Maintenance of Semantic Annotations , 2005, ISPA Workshops.

[25]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[26]  Satish K. Tripathi,et al.  Parallel and distributed simulation of discrete event systems , 1994 .

[27]  Chao-Bo Yan,et al.  Formulation and a Simulation-Based Algorithm for Line-Side Buffer Assignment Problem in Systems of General Assembly Line With Material Handling , 2010, IEEE Transactions on Automation Science and Engineering.

[28]  Samir Ranjan Das Adaptive protocols for parallel discrete event simulation , 1996, Winter Simulation Conference.

[29]  R.M. Fujimoto,et al.  Parallel and distributed simulation systems , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[30]  Sang Hoon Kong Two-step simulation method for automatic material handling system of semiconductor fab , 2007 .

[31]  Mustafa K. Gurcan,et al.  Minimisation of the update response time in a distributed database system , 2002, Perform. Evaluation.

[32]  Chao-Bo Yan,et al.  Line-side Buffer Assignment in General Assembly Line Systems with Material Handling , 2009 .

[33]  R. Bell,et al.  A knowledge based multi-level modelling system for the design of flexible machining facilities , 1992 .

[34]  James R. Wilson,et al.  Using SLAM to design the material handling system of a flexible manufacturing system , 1986 .

[35]  Moon-Jung Chung,et al.  An overhead reducing technique for Time Warp , 2002, Proceedings. Sixth IEEE International Workshop on Distributed Simulation and Real-Time Applications.

[36]  Jennifer A. Harding,et al.  Simulation: an application of factory design process methodology , 2000, J. Oper. Res. Soc..

[37]  J. Banks,et al.  Discrete-Event System Simulation , 1995 .

[38]  M NicolDavid Parallel discrete-event simulation of FCFS stochastic queueing networks , 1988 .

[39]  S. K. Bhattacharyya,et al.  A Computer Simulation System for the Evaluation of Man Assignments on Car Assembly Tracks , 1993, Simul..

[40]  Qing-Shan Jia,et al.  Event-based optimization for dispatching policies in material handling systems of general assembly lines , 2008, 2008 47th IEEE Conference on Decision and Control.

[41]  Moon-Jung Chung,et al.  An overhead reducing technique for Time Warp , 2005, J. Parallel Distributed Comput..

[42]  David M. Nicol,et al.  Parallel discrete-event simulation of FCFS stochastic queueing networks , 1988, PPEALS '88.

[43]  Asser N. Tantawi,et al.  Approximate Analysis of Fork/Join Synchronization in Parallel Queues , 1988, IEEE Trans. Computers.

[44]  David M. Nicol Principles of conservative parallel simulation , 1996, Winter Simulation Conference.

[45]  J. Quadrat,et al.  A linear-system-theoretic view of discrete-event processes , 1983, The 22nd IEEE Conference on Decision and Control.

[46]  Alexander W. Booth Object-Oriented Modeling for Flexible Manufacturing Systems , 2001 .

[47]  Christos G. Cassandras,et al.  Introduction to Discrete Event Systems , 1999, The Kluwer International Series on Discrete Event Dynamic Systems.

[48]  Youngshin Han,et al.  Full Fabrication Simulation of 300mm Wafer Focused on AMHS (Automated Material Handling Systems) , 2004, AsiaSim.

[49]  Khaled S. El-Kilany,et al.  Generic tool for modelling and simulation of semiconductor intrabay material handling system , 2004 .

[50]  Arun Jayaraman,et al.  A sortation system model , 1997, WSC '97.

[51]  Michael J. Magazine,et al.  Push and pull strategies for controlling multistage production systems , 2000 .

[52]  Chao-Bo Yan,et al.  Efficient simulation for serial production lines based on aggregated event-scheduling , 2008, 2008 IEEE International Conference on Automation Science and Engineering.