Introducing new parts into existing cellular manufacturing systems based on a novel similarity coefficient

Over the last three decades, designing cellular manufacturing systems (CMS) still centres on assigning machines to machine cells and parts to part families. This task ends after assigning these part families to the appropriate machine cells. In the past, testing CMS was evaluated according to the efficiency of clustering, but actual testing of CMS after installation is still unexplored. Introducing one or more new parts (products) into CMS without any changes in the installation of the cells during processing of the current parts is a new concept to be considered and evaluated. Transferring these systems from traditional ideologues to advanced ideologues (agile systems) is highly desired. This concept can be considered as part (product) flexibility in CMS. To address this concept, a new similarity coefficient between the new part and the existing manufacturing cell will be created. New productivity and flexibility measurements in CMS will also be suggested. A new strategy for accepting a new part into CMS will be proposed based on machine utilization and flexibility in the cells, cell utilization and flexibility in the system, product flexibility (system flexibility), and similarity of this part with existing manufacturing cells. A complete analytical example will be presented.

[1]  Y. Won,et al.  Multiple criteria clustering algorithm for solving the group technology problem with multiple process routings , 1997 .

[2]  Stefano Tonchia,et al.  Manufacturing flexibility: A literature review , 1998 .

[3]  R. S. Lashkari,et al.  A heuristic procedure for determining manufacturing families from design-based grouping for flexible manufacturing systems , 1986 .

[4]  Jacob Jen-Gwo Chen,et al.  Fuzzy-set-based machine-cell formation in cellular manufacturing , 1996, J. Intell. Manuf..

[5]  R. S. Lashkari,et al.  Machine grouping problem in cellular manufacturing systems ― an integer programming approach , 1989 .

[6]  P. Waghodekar,et al.  Machine-component cell formation in group technology: MACE , 1984 .

[7]  J. Miltenburg,et al.  A comparative evaluation of nine well-known algorithms for solving the cell formation problem in group technology , 1991 .

[8]  Hamid R. Parsaei,et al.  Part family formation based on alternative routes during machine failure , 1998 .

[9]  Donald Gerwin,et al.  Management of advanced manufacturing technology , 1992 .

[10]  Bhaba R. Sarker,et al.  Measures of grouping efficiency in cellular manufacturing systems , 2001, Eur. J. Oper. Res..

[11]  Chuen-Lung Chen,et al.  A tabu search approach to the cell formation problem , 1997 .

[12]  Yi Xu,et al.  Designing multi-product lines: job routing in cellular manufacturing systems , 2000 .

[13]  Marius M. Solomon,et al.  The formation of subfamilies for machine loading of flow-line cells , 1995 .

[14]  K. S. Ravichandran,et al.  The Role of Fuzzy and Genetic Algorithms in Part Family Formation and Sequence Optimisation for Flexible Manufacturing Systems , 2002 .

[15]  M Soleymanpour,et al.  A transiently chaotic neural network approach to the design of cellular manufacturing , 2002 .

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

[17]  Tom M. Cavalier,et al.  Design of Cellular Manufacturing Systems , 1992 .

[18]  Keith Case,et al.  Component grouping for cell formation using resource elements , 1996 .

[19]  David F. Rogers,et al.  Similarity and distance measures for cellular manufacturing. Part II. An extension and comparison , 1993 .

[20]  A. Kusiak The generalized group technology concept , 1987 .

[21]  K. S. Ravichandran,et al.  A New Approach to Fuzzy Part-Family Formation in Cellular Manufacturing Systems , 2001 .

[22]  Ming Zhou,et al.  Formation of independent flow-line cells based on operation requirements and machine capabilities , 1998 .

[23]  M. Chandrasekharan,et al.  Grouping efficacy: a quantitative criterion for goodness of block diagonal forms of binary matrices in group technology , 1990 .

[24]  R. Meenakshi Sundaram,et al.  Formation of part families to design cells with alternative routing considerations , 1992 .

[25]  John Grznar,et al.  Part family formation for variety reduction in flexible manufacturing systems , 1997 .

[26]  Asoo J. Vakharia,et al.  Cell formation in group technology: review, evaluation and directions for future research , 1998 .

[27]  Asoo J. Vakharia,et al.  Redesigning a Cellular Manufacturing System to Handle Long-Term Demand Changes: A Methodology and Investigation* , 1993 .

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

[29]  Asoo J. Vakharia,et al.  Designing a Cellular Manufacturing System: A Materials Flow Approach Based on Operation Sequences , 1990 .

[30]  Yong Yin,et al.  A dissimilarity measure for solving the cell formation problem in cellular manufacturing , 2001 .

[31]  Inyong Ham,et al.  Multiobjective cluster analysis for part family formations , 1986 .

[32]  Hamid Seifoddini,et al.  Comparative study of similarity coefficients and clustering algorithms in cellular manufacturing , 1994 .

[33]  Gürsel A. Süer,et al.  A configuration-based clustering algorithm for family formation , 1996 .

[34]  Yong Yin,et al.  Manufacturing cells' design in consideration of various production factors , 2002 .

[35]  John A. Buzacott,et al.  Stochastic models of manufacturing systems , 1993 .

[36]  R. S. Lashkari,et al.  Simultaneous grouping of parts and machines in cellular manufacturing systems—an integer programming approach , 1991 .

[37]  Layek Abdel-Malek,et al.  Design and implementation of flexible manufacturing solutions in agile enterprises , 2000 .

[38]  C. Mosier An experiment investigating the application of clustering procedures and similarity coefficients to the GT machine cell formation problem , 1989 .

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

[40]  C. L. Ang On the performance of hybrid multi-cell flexible manufacturing systems , 1995 .

[41]  Ying-Chin Ho,et al.  Solving cell formation problems in a manufacturing environment with flexible processing and routeing capabilities , 1996 .

[42]  John McAuley,et al.  Machine grouping for efficient production , 1972 .

[43]  Allan S. Carrie,et al.  Numerical taxonomy applied to group technology and plant layout , 1973 .

[44]  Richard C. Cobb,et al.  Capability based formulation and solution of multiple objective cell formation problems using simulated annealing , 2001 .

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

[46]  B. Sarker,et al.  A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems , 2000 .

[47]  Hamid Seifoddini,et al.  Part-family formation for cellular manufacturing: A case study at Harnischfeger , 1999 .

[48]  S. Ng Worst-case analysis of an algorithm for cellular manufacturing , 1993 .

[49]  K. Y. Tam,et al.  An operation sequence based similarity coefficient for part families formations , 1990 .

[50]  O. Felix Offodile Application of similarity coefficient method to parts coding and classification analysis in group technology , 1991 .

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

[52]  Sung-Lyong Kang,et al.  A work load-oriented heuristic methodology for manufacturing cell formation allowing reallocation of operations , 1993 .

[53]  S. Viswanathan A new approach for solving the P-median problem in group technology , 1996 .

[54]  R. Lashkari,et al.  A mathematical programming approach to joint cell formation and operation allocation in cellular manufacturing , 1995 .

[55]  T. T. Narendran,et al.  CASE: A clustering algorithm for cell formation with sequence data , 1998 .

[56]  Andrew Kusiak,et al.  EXGT-S: A knowledge based system for group technology , 1988 .

[57]  Ming Zhou,et al.  Formation of general GT cells: an operation-based approach , 1998 .