An efficient semi-analytical simulation for availability evaluation of discrete production lines with unreliable machines

This paper presents a semi-analytical simulation which combines analytical model and Monte Carlo technique to simulate the operation of discrete production lines. The purpose is to rapidly evaluate the availability for lines with unreliable machines and finite buffers in the design phase. Firstly, description of production line and availability definition are exhibited. Then, an output and inventory model is proposed to calculate the system output based on the failure data. With the help of Monte Carlo technique, the availability of the whole line in different system parameters can be obtained by iterating this analytical algorithm. Compared with real-time simulation, this semi-analytical simulation can remarkably reduce the computational load to failure number level without losing accuracy. Finally, numerical examples are carried out, and the results indicate that the proposed method is flexible and efficient by comparing with other four methods.

[1]  Binbin Xu,et al.  An integrated simulation and stochastic Kriging method for reliability-related performance prediction of transfer lines , 2016 .

[2]  Stanley B. Gershwin,et al.  Modelling and analysis of Markovian continuous flow systems with a finite buffer , 2011, Ann. Oper. Res..

[3]  Ryspek Usubamatov,et al.  Mathematical models for productivity and availability of automated lines , 2013 .

[4]  John D. Perkins,et al.  The Availability of a System of Two Unreliable Machines Connected by an Intermediate Storage Tank , 1983 .

[5]  Jianping Chen,et al.  An Exact Method for the Analysis of a Two-Machine Manufacturing System with a Finite Buffer Subject to Time-Dependent Failure , 2015 .

[6]  Jingshan Li,et al.  Comparisons of two-machine line models in throughput analysis , 2006 .

[7]  Ali Gharbi,et al.  Availability modelling and analysis of multi-product flexible transfer lines subject to random failures , 2010 .

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

[9]  Lifeng Xi,et al.  An improved decomposition method for evaluating the performance of transfer lines with unreliable machines and finite buffers , 2012 .

[10]  Stefan Helber,et al.  Performance Analysis of Flow Lines with Non-Linear Flow of Material , 1999 .

[11]  Gerrit K. Janssens,et al.  Buffer allocation and required availability in a transfer line with unreliable machines , 2001 .

[12]  Carl E. Betterton,et al.  Production rate of synchronous transfer lines using Monte Carlo simulation , 2012 .

[13]  Ali Gharbi,et al.  Availability and throughput of unreliable, unbuffered production lines with non-homogeneous deterministic processing times , 2008 .

[14]  N. Viswanadham,et al.  Reliability analysis of flexible manufacturing systems , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[15]  Mahmoud A. El-Sharief,et al.  SIMULATION MODELING OF AUTOMATIC PRODUCTION LINES WITH INTERMEDIATE BUFFERS , 2013 .

[16]  Matías Urenda Moris,et al.  Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[17]  Justyna Patalas-Maliszewska,et al.  Throughput Analysis of Automatic Production Lines Based on Simulation Methods , 2015, IDEAL.

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

[19]  Asbjoern M. Bonvik.  Performance analysis of manufacturing systems under hybrid control policies , 1996 .

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

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

[22]  Ali Gharbi,et al.  Simulation based throughput assessment of non-homogeneous transfer lines , 2009 .

[23]  Tarikere T. Niranjan,et al.  A simulation-based methodology to analyse production line disruptions , 2013 .

[24]  Ryspek Usubamatov,et al.  Mathematical models for the productivity rate of automated lines with different failure rates for stations and mechanisms , 2016 .

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