Using dynamic cellular manufacturing to simplify scheduling in cell based production systems

Previous research has shown that the formation of temporary, logical manufacturing cells in a job shop, overcomes problems of high setup frequency typically found in job shops. In addition, this form of cellular configuration is more flexible than tranditional, group technology based cellular configurations. This research demonstrates that an added benefit of a dynamic cellular configuration is that it simplifies production scheduling, eliminating the need for more complex dispatching rules. In particular, it eliminates the need for further setup reduction when scheduling parts from the same family. Improvements in performance when employing setup reduction are shown to occur only when the premium associated with intra-family setup reduction is very high, and are attributable to reductions in flow time variance.

[1]  Farzad Mahmoodi,et al.  A comprehensive analysis of group scheduling heuristics in a job shop cell , 1993 .

[2]  T. J. Greene,et al.  A review of cellular manufacturing assumptions, advantages and design techniques , 1984 .

[3]  Barbara B. Flynn Repetitive lots: The use of a sequence-dependent set-up time scheduling procedure in group technology and traditional shops , 1987 .

[4]  Bruce W. Schmeiser,et al.  Batch Size Effects in the Analysis of Simulation Output , 1982, Oper. Res..

[5]  Nancy Lea Hyer,et al.  Research issues in cellular manufacturing , 1987 .

[6]  Nancy Lea Hyer,et al.  Cellular manufacturing in the U.S. industry: a survey of users , 1989 .

[7]  John M. Charnes,et al.  Cellular Versus Functional Layouts Under a Variety of Shop Operating Conditions , 1993 .

[8]  Claude Dennis Pegden Introduction to SIMAN , 1988, WSC '88.

[9]  Vijay R. Kannan,et al.  Cellular manufacturing using virtual cells , 1996 .

[10]  Nallan C. Suresh,et al.  Coping with the Loss of Pooling Synergy in Cellular Manufacturing Systems , 1994 .

[11]  Farzad Mahmoodi,et al.  Dynamic Group Scheduling Heuristics in a Flow-through Cell Environment* , 1992 .

[12]  Nallan C. Suresh Partitioning Work Centers for Group Technology: Analytical Extension and Shop-Level Simulation Investigation* , 1992 .

[13]  J. Kleijnen Statistical tools for simulation practitioners , 1986 .

[14]  Lawrence D. Fredendall,et al.  Load smoothing by the planning and order review/release systems: A simulation experiment , 1991 .

[15]  Charles T. Mosier,et al.  Analysis of group technology scheduling heuristics , 1984 .

[16]  F. Robert Jacobs,et al.  REPETITIVE LOTS: FLOW-TIME REDUCTIONS THROUGH SEQUENCING AND DYNAMIC BATCH SIZING , 1988 .

[17]  John S. Morris,et al.  A simulation analysis of factors influencing the attractiveness of group technology cellular layouts , 1990 .

[18]  Lee W. Schruben,et al.  Optimal Tests for Initialization Bias in Simulation Output , 1983, Oper. Res..

[19]  Kenneth R. Baker,et al.  Sequencing Rules and Due-Date Assignments in a Job Shop , 1984 .

[20]  J. Filliben The Probability Plot Correlation Coefficient Test for Normality , 1975 .

[21]  F. Robert Jacobs,et al.  Applications and Implementation: AN EXPERIMENTAL COMPARISON OF CELLULAR (GROUP TECHNOLOGY) LAYOUT WITH PROCESS LAYOUT , 1987 .

[22]  G. Arthur Mihram Blockinq in simular experimental designs , 1974 .