Taxonomy of Manufacturing Flexibility at Manufacturing Companies Using Imperialist Competitive Algorithms, Support Vector Machines and Hierarchical Cluster Analysis

M. Khoobiyan, A. Pooya, A. Tavakkoli, F. Rahimnia

Abstract


Manufacturing flexibility is a multidimensional concept and manufacturing companies act differently in using these dimensions. The purpose of this study is to investigate taxonomy and identify dominant groups of manufacturing flexibility. Dimensions of manufacturing flexibility are extracted by content analysis of literature and expert judgements. Manufacturing flexibility was measured by using a questionnaire developed to survey managers of manufacturing companies. The sample size was set at 379. To identify dominant groups of flexibility based on dimensions of flexibility determined, Hierarchical Cluster Analysis (HCA), Imperialist Competitive Algorithms (ICAs) and Support Vector Machines (SVMs) were used by cluster validity indices. The best algorithm for clustering was SVMs with three clusters, designated as leading delivery-based flexibility, frugal flexibility and sufficient plan-based flexibility.


Keywords


manufacturing flexibility; taxonomy; dominant groups; hierarchical cluster analysis; support vector machines; imperialist competitive algorithm

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References


A. Cingoz, A. A. Akdogan, “Strategic Flexibility, Environmental Dynamism, and Innovation Performance: An Empirical Study”, Procedia - Social and Behavioral Sciences, Vol. 99, No. 1, pp. 582–589, 2013

S. Genchev, G. Willis, “A note on manufacturing flexibility as a firm-specific dynamic capability”, Manufacturing Letters, Vol. 2, No. 3, pp. 100–103, 2014

G. Copani, M. Urgo, “New business models and configuration approachesfor focused-flexibility manufacturing systems”, Procedia CIRP, Vol. 2, No. 5, pp. 10–15, 2012

D. Upton, “The Management of Manufacturing Flexibility”, California Management Review, Vol. 1, No. 1, pp. 72-88, 1994

G. Seebacher, H. Winkler, “Evaluating Flexibility in Discrete Manufacturing Based on Performance and Efficiency”, International Journal of Production Economics, Vol. 153, No. 2, pp. 340–351, 2014

R. J. Vokurka, S. W. O`Leary-Kelly, “A review of empirical research on manufacturing flexibility”, Journal of Operations Management, Vol. 18, No. 2, pp. 485–501, 2000

S. Kara, B. Kayis, “Manufacturing flexibility and variability: an overview”, Journal of Manufacturing Technology Management, Vol. 15, No. 6, pp. 466-478, 2004

A. Oke, “A framework for analysing manufacturing flexibility”, International Journal of Operations and Production Management, Vol. 25, No. 10, pp. 973-996, 2005

J. H. Saleh, G. Mark, N. C. Jordan, “Flexibility: a Multi-Disciplinary Literature Review and a Research Agenda for Designing Flexible Engineering Systems”, Journal of Engineering Design, Vol. 20, No. 3, pp. 307-323, 2009

T. A. Boyle, M. S. Rathje, “An empirical examination of the best practices to ensure manufacturing flexibility Lean alignment”, Journal of Manufacturing Technology Management, Vol. 20, No. 3, pp. 348-366, 2009

Y. P. Gupta, T. M. Somers,“Business strategy, manufacturing flexibility, and organizational performance relationships: a path analysis approach”, Production and Operations Management, Vol. 5, No. 3, pp. 204-233, 1996

S. Gustavsson, “Flexibility and productivity in complex processes”, International Journal of Production Research, Vol. 22, No. 5, pp. 801-808, 1988

K. Boyer, G. K. Leong, P. T. Ward, L. J. Krajewski, “Unlocking the potential of advanced manufacturing technologies”, Journal of Operations Management,Vol. 15, No. 4, pp. 331-347, 1997.

P. Nemetz, Bridging the strategic outcome measurement gap in manufacturing organizations, in Ettlie, J.E., Burstein, M.C, 1990.

F. F. Suarez, M. A. Cusumano, C. H. Fine, “An empirical study of manufacturing flexibility in printed circuit board assembly”, Operations Research, Vol. 44, No. 1, pp. 223-49, 1996.

C. H. Wood, L. P. Ritzman, D. Sharma, Intended and achieved competitive priorities: measures, frequencies and financial impact, in Ettlie, J.E., Burstein, M.cC. and Feigenbaum, A. (Eds), Manufacturing Strategy, Kluwer Academic Publishers, Boston, MA, 1990.

S. H. Chang, R. J. Lin, J. Chen, L. H. Huang, “Manufacturing Flexibility and Manufacturing Proactiveness Empirical Evidence from the Motherboard Industry”, Industrial Management & Data Systems, Vol. 105, No. 8, pp. 1115-1132, 2005.

J. Browne, D. Dubois, K. Rathmil, S. P. Sethi, K. E. Stecke, (1984)Classification of Flexible Manufacturing Systems”, The FMS Magazine, Vol. 2, No. 2, pp. 114-117, 1984.

S. H. Chang, C. L. Yang, H. C. Cheng, C. Sheu, “Manufacturing Flexibility and Business Strategy: An Empirical Study of Small and Medium Sized Firms”, International Journal of Production Economics, Vol. 83, No. 3, pp. 13-26, 2003

C. Gaimon, V. Singhal, “Flexibility and The Choice of Manufacturing Facilities Under Short Product Life Cycles”, European Journal of Operational Research, Vol. 60, No. 2, pp. 211-223, 1992

L. L. Koste, M. K. Malhotra, “A theoretical framework for analyzing the dimensions of manufacturing flexibility”, Journal of Operations Management, Vol. 18, No. 2, pp. 75-93, 1999

P. S. Adler, “Managing Flexible Automation”, California Management Review, Vol. 30, No. 3, pp. 34-56, 1988

R. Mishra, A. P. Pundir, G. Ganapathy, “Assessment of manufacturing flexibility”, A review of research and conceptual Framework, Management Research Review, Vol. 37, No. 8, pp. 750-776, 2014

D. M. Upton, “The management of manufacturing flexibility”, California Management Review, Vol. 2, No. 36, pp. 72-89, 1997

A. D. Toni, S. Tonchia, “Definition and linkages Between Operational and Strategic Flexibilities”, Omega, Vol. 33, No. 4, pp. 525-540, 2005

A. Oke, “Linking manufacturing flexibility to innovation performance in manufacturing plants”, Journal Production Economics, Vol. 143, No. 4, pp. 242–247, 2013

Y. P. Gupta, S. Goyal, “Flexibility of Manufacturing Systems: Concepts and Measurement”, European Journal of Operational Research, Vol. 43, No. 4, pp. 119-135, 1989

R. Beach, A. P. Muhleman, D. H. R. Price, A. Paterson, J. A. Sharp, “Review of Manufacturing Flexibility”, European Journal of Operational Research, Vol. 122, No. 2, pp. 41-57, 2000

R. Narain, R. C. Yadav, J. Sarkis, J. J. Cordeiro, “The strategic Implications of Flexibility in Manufacturing Systems”, International Journal of Agile Management Systems,Vol. 2, No. 3, pp. 202-213, 2000

R. V. Ramesesh, M. D. Jayakumar, “Measurement of manufacturing flexibility: a value based approach”, Journal of Operations Management, Vol. 10, No. 4, pp. 446-69, 1991

A. K. Sethi, S. P. Sethi, “Flexibility in manufacturing: a survey”, International Journal of Flexible Manufacturing Systems, Vol. 2, No. 4, pp. 289-328, 1990

A. Y. Chang, “Prioritising the types of manufacturing flexibility in an uncertain environment”, International Journal of Production Research, Vol. 50, No. 8, 2133–2149, 2012

R. Sawhney, “Interplay between uncertainty and flexibility across the value-chain:Towards a transformation model of manufacturing flexibility”, Journal of Operations Management,Vol. 24, No. 2, pp. 476–493, 2006

C. P. Patel, “Role of manufacturing flexibility in managing duality of formalization and environmental uncertainty in emerging firms”, Journal of Operations Management, Vol. 29, No. 3, pp. 143–162, 2011

L. K. Koste, M. K. Malhotra, S. Sharma, “Measuring dimensions of manufacturing flexibility”, Journal of Operations Management, Vol. 22, No. 3, pp. 171-196, 2004

N. Slack, “Flexibility as A Manufacturing Objective”, International of Operations and Production Management,Vol. 3, No. 3, pp. 5-13, 1983

B. Dreyer, K. Gronhaug, “Uncertainty, flexibility, and sustained competitive advantage”, Journal of Business Research ,Vol. 57, No. 2, pp. 484–494, 2004

G. N. Punj, D. W. Stewart, “Cluster Analysis in marketing redearch: Review and suggestions for application”, Journal of Marketing Research, Vol. 20, No. 2, pp. 134-148, 1983

M. Sattlecker, R. Baker, N. Stone, C. Bessant, “Support vector machine ensembles for breast cancer type prediction from mid-FTIR micro-calcification spectra”, Chemometrics and Intelligent Laboratory Systems, Vol. 107, No. 2, pp. 363-70, 2011

E. Atashpaz-Gargari, C. Lucas, “Imperialist Competitive Algorithm: An Algorithm for Optimization inspired by imperialistic Competition”, IEEE Congress on Evolutionary Computation, Singapore, Vol. 4, No. 3, pp. 4661–67, 2007

A. Kaveh, S. Talatahari, “Optimum design of skeletal structures using imperialist competitive algorithm”, Computers & Structures, Vol. 88, No. 3, pp. 1220-1229, 2010

T. Niknam, E. Taherian Fard, N. Pourjafarian, A. Rousta, “An efficient hybrid algorithm based on modified imperialist competitive algorithm and K-means for data clustering”, Engineering Applications of Artificial Intelligence, Vol. 24, No. 2, pp. 306-317, 2011

C. Lucas, Z. Nasiri-Gheidari, F. Tootoonchian, “Application of an imperialist competitive algorithm to the design of a linear induction motor”, Energy Conversion and Management, Vol. 51, No. 7, pp. 1407- 1411, 2010

A. Khabbazi, E. Atashpaz-Gargari, C. Lucas, “Imperialist competitive algorithm for minimum bit error rate beamforming”, International Journal of Bio-Inspired Computation,Vol. 1, No. 1, pp. 125-133, 2009

J. C. Bezdek, N. R. Pal, “Some new indexes of cluster validity”, IEEE Transactions on Systems, Man, and Cybernetics NPART B: CYBERNETICS , Vol. 28, No. 3, pp. 301-315, 1988

B. Desgraupes, “clusterCrit: Clustering Indices”, R package version,Vol. 1, No. 3, pp. 4-5, 2013. http://CRAN.R-project.org/package=clusterCrit.

K. P. Agrawal, S. Garg, P. Patel, “Performance Measures for Densed and Arbitrary Shaped Clusters”, International Journal of Computer Science & Communication, Vol. 6, No. 2, pp. 338-350, 2015




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