Effects of routing flexibility, sequencing flexibility and scheduling decision rules on the performance of a flexible manufacturing system

This paper focuses on a simulation-based experimental study of the interaction among routing flexibility, sequencing flexibility and part sequencing rules in a typical flexible manufacturing system (FMS). Two scenarios are considered for experimentation. Three routing flexibility levels, five sequencing flexibility levels and four scheduling rules for part sequencing decision are considered for detailed investigation. The performance of the FMS is evaluated using various measures related to flow time and tardiness of parts. The simulation results are subjected to statistical analysis. The analysis of results reveals that deterioration in system performance can be minimized substantially by incorporating either routing flexibility or sequencing flexibility or both. However, the benefits of either of these flexibilities diminish at higher flexibility levels. Part sequencing rules such as earliest due date and earliest operation due date provide better performance for all the measures at higher flexibility levels.

[1]  Vinod Kumar,et al.  Entropic measures of manufacturing flexibility , 1987 .

[2]  A. Claudio Garavelli.  Performance analysis of a batch production system with limited flexibility , 2001 .

[3]  Felix T.S. Chan,et al.  Flexibility performance: Taguchi's method study of physical system and operating control parameters of FMS , 2007 .

[4]  Kathryn E. Stecke,et al.  Classification of flexible manufacturing systems , 2011 .

[5]  Safiye Turgay,et al.  Agent-based FMS control , 2009 .

[6]  Naiqi Wu.  Flexibility to Manufacturing Process Reengineering for Mass Customization , 2005 .

[7]  Suresh P. Sethi,et al.  Flexibility in manufacturing: A survey , 1990 .

[8]  Richard H. Weston,et al.  A resource-based modelling approach to support responsive manufacturing systems , 2009 .

[9]  Jiyin Liu,et al.  A new classification scheme for flexible manufacturing systems , 1993 .

[10]  F. F. Chen,et al.  An Intelligent Decision Support System for Part Launching in a Flexible Manufacturing System , 2001 .

[11]  Santosh Kumar,et al.  An expert enhanced coloured fuzzy Petri net approach to reconfigurable manufacturing systems involving information delays , 2005 .

[12]  C. Saygin,et al.  Real-Time Manipulation of Alternative Routeings in Flexible Manufacturing Systems: A Simulation Study , 2001 .

[13]  G. K. Hutchinson,et al.  Flexible process plans: their value in flexible automation , 1994 .

[14]  Reuven Katz,et al.  Design principles of reconfigurable machines , 2007 .

[15]  Faizul Huq,et al.  The impact of machine flexibility on the performance of flexible manufacturing systems , 2001 .

[16]  F. F. Chen,et al.  Holonic Concept Based Methodology for Part Routeing on Flexible Manufacturing Systems , 2000 .

[17]  Hoda A. ElMaraghy,et al.  Flexible and reconfigurable manufacturing systems paradigms , 2005 .

[18]  Robert M. O'Keefe,et al.  Interaction between dispatching and next station selection rules in a dedicated flexible manufacturing system , 1992 .

[19]  Felix T.S. Chan,et al.  Impact of operation flexibility and dispatching rules on the performance of a flexible manufacturing system , 2004 .

[20]  Paolo Renna,et al.  Capacity reconfiguration management in reconfigurable manufacturing systems , 2010 .

[21]  Hoda A. ElMaraghy,et al.  Optimal configuration selection for Reconfigurable Manufacturing Systems , 2007 .

[22]  Jun Li,et al.  Improved net rewriting system-based approach to model reconfiguration of reconfigurable manufacturing systems , 2008 .

[23]  Manoj Kumar Tiwari,et al.  Operation allocation in automated manufacturing system using GA-based approach with multifidelity models , 2010 .

[24]  M. Kannan,et al.  A feature-based generic setup planning for configuration synthesis of reconfigurable machine tools , 2009 .

[25]  Yash P. Gupta,et al.  Flexibility of manufacturing systems: Concepts and measurements , 1989 .

[26]  Waguih ElMaraghy,et al.  Investigating optimal capacity scalability scheduling in a reconfigurable manufacturing system , 2007 .

[27]  Z. M. Bi,et al.  Development of reconfigurable machines , 2008 .

[28]  Ram Rachamadugu,et al.  Scheduling with Sequencing Flexibility , 1993 .

[29]  Mahmoud Houshmand,et al.  Production planning and performance optimization of reconfigurable manufacturing systems using genetic algorithm , 2011 .

[30]  Hing Kai Chan,et al.  The State of the Art in Simulation Study on FMS Scheduling: A Comprehensive Survey , 2002 .

[31]  James J. Solberg,et al.  Effectiveness of flexible routing control , 1991 .

[32]  Miryam Barad,et al.  Impact of some flexibility factors in FMSs–a performance evaluation approach , 1992 .

[33]  Hoda A. ElMaraghy,et al.  Real-time scheduling with deadlock avoidance in flexible manufacturing systems , 2003 .

[34]  Felix T.S. Chan,et al.  Effects of Dispatching and Routeing Decisions on the Performance of a Flexible Manufacturing System , 2003 .

[35]  T. Karthikeyan,et al.  Scheduling decisions in FMS using a heuristic approach , 2003 .

[36]  Robert J. Vokurka,et al.  A review of empirical research on manufacturing flexibility , 2000 .

[37]  P. K. Jain,et al.  Cell formation in the presence of reconfigurable machines , 2007 .

[38]  C. Saygin,et al.  Integrating Flexible Process Plans with Scheduling in Flexible Manufacturing Systems , 1999 .

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

[40]  Kathryn E. Stecke,et al.  Design, planning, scheduling, and control problems of flexible manufacturing systems , 1985 .