Dissimilarity Maximization Method for Real-time Routing of Parts in Random Flexible Manufacturing Systems

This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is not known prior to production and off-line scheduling is not possible, is selected for the simulation study. A software environment that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to implement the DMM concept. In addition to DMM, the simulation study uses two priority rules for routing (i.e., machine) selection and seven priority rules for selecting parts awaiting service at machine buffers. The results show (1) DMM outperforms the other two routing selection rules on production rate regardless of the part selection rule used, and (2) its performance is highly dependent on the part selection rules it is combined with.

[1]  Kathryn E. Stecke,et al.  On the robustness of using balanced part mix ratios to determine cyclic part input sequences into flexible flow systems , 1996 .

[2]  George Chryssolouris,et al.  Manufacturing Systems: Theory and Practice , 1992 .

[3]  H. Cho PETRI NET MODELS FOR MESSAGE MANIPULATION AND EVENT MONITORING IN AN FMS CELL , 1998 .

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

[5]  F. Fred Choobineh,et al.  A framework for the design of cellular manufacturing systems , 1988 .

[6]  Yuehwern Yih,et al.  A learning-based methodology for dynamic scheduling in distributed manufacturing systems , 1995 .

[7]  Albert Jones,et al.  A hybrid approach for real-time sequencing and scheduling , 1995 .

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

[9]  Ram Rachamadugu,et al.  Classification and review of FMS scheduling procedures , 1994 .

[10]  Jean-Pierre Kruth,et al.  Opportunistic process planning: a knowledge based technique for CAPP applications , 1994 .

[11]  Viliam Makis,et al.  Scheduling of the optimal tool replacement times in a flexible manufacturing system , 2001 .

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

[13]  Henri Pierreval,et al.  Manufacturing cell design with flexible routings capability in presence of unreliable machines , 1999 .

[14]  A. S. Carrie,et al.  Work scheduling in FMS under tool availability constraints , 1986 .

[15]  Der-Chiang Li,et al.  Using an Unsupervized Neural Network and Decision Tree as Knowledge Acquisition Tools for Fms Scheduling , 1997, Int. J. Syst. Sci..

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

[17]  Maher Lahmar,et al.  An Evaluative Study of Operation Grouping Policies in an FMS , 2003 .

[18]  Jim Duggan,et al.  Shop Floor Control Systems , 1991 .

[19]  Tarun Gupta Design of manufacturing cells for flexible environment considering alternative routeing , 1993 .

[20]  Hyunbo Cho,et al.  A Formal Approach to Integrating Computer-Aided Process Planning and Shop Floor Control , 1994 .

[21]  Michal Tzur,et al.  Design of flexible assembly line to minimize equipment cost , 2000 .

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

[23]  Ralf W. Seifert,et al.  Cooperative dispatching - exploiting the flexibility of an FMS by means of incremental optimization , 2001, Eur. J. Oper. Res..

[24]  Philippe Solot,et al.  A concept for planning and scheduling in an FMS , 1990 .

[25]  L. C. Leung,et al.  Concurrent part assignment and tool allocation in FMS with material handling considerations , 1993 .

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

[27]  Yu Haibin,et al.  A neural-based approach to production scheduling , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[28]  Taho Yang,et al.  A genetic algorithm for facility layout design in flexible manufacturing systems , 1998 .

[29]  Christophe Caux,et al.  Cell formation with alternative process plans and machine capacity constraints: A new combined approach , 2000 .

[30]  Brett A. Peters,et al.  A comparison of setup strategies for printed circuit board assembly , 1998 .

[31]  Felix T.S. Chan,et al.  Evaluations of operational control rules in scheduling a flexible manufacturing system , 1999 .

[32]  Robert E. Young,et al.  The design of flexible manufacturing systems , 1993 .

[33]  Andrew W. Shogan,et al.  Modelling and solving an FMS part selection problem , 1989 .

[34]  Kripa Shanker,et al.  A loading and dispatching problem in a random flexible manufacturing system , 1985 .

[35]  C. Saygin,et al.  On Scheduling Approaches of Flexible Manufacturing Systems: Gap Between Theory and Practice , 1995 .

[36]  Kathryn E. Stecke,et al.  Loading and control policies for a flexible manufacturing system , 1981 .

[37]  Tarun Gupta,et al.  Production data based similarity coefficient for machine-component grouping decisions in the design of a cellular manufacturing system , 1990 .

[38]  Jen-Ming Chen,et al.  A Genetic-Based Vision System for Cross-Functional Integration in Flexible Manufacturing: A Tutorial and Application , 1997 .

[39]  G. K. Hutchinson,et al.  The effect of process flexibility on productivity for classes of similar job shops , 1998 .

[40]  Farzad Mahmoodi,et al.  The Effects of Scheduling Rules and Routing Flexibility on the Performance of a Random Flexible Manufacturing System , 1999 .

[41]  F. Frank Chen,et al.  Concurrent design of manufacturing cell and control functions: A neural network approach , 1995 .

[42]  F. Frank Chen,et al.  The state of the art in intelligent real-time FMS control: a comprehensive survey , 1996, J. Intell. Manuf..

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

[44]  Jean-Pierre Kruth,et al.  A CAPP System for Nonlinear Process Plans , 1992 .

[45]  A. Kusiak,et al.  Similarity coefficient algorithms for solving the group technology problem , 1992 .

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

[47]  A. Márkus,et al.  Process planning with genetic algorithms on results of knowledge-based reasoning , 1996 .

[48]  Lee Luong A cellular similarity coefficient algorithm for the design of manufacturing cells , 1993 .

[49]  Rudolf Albrecht Systems: Theory and Practice , 1998, Advances in Computing Science.

[50]  S. Sahu,et al.  A genetic algorithm for facility layout , 1995 .

[51]  Hideo Fujimoto,et al.  Applications of genetic algorithm and simulation to dispatching rule-based FMS scheduling , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.