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Manufacturing wastes analysis in lean environment: an integrated ISM-fuzzy MICMAC approach

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Abstract

Value stream mapping (VSM) is an important improvement initiative in the lean environment that can be used to boost manufacturing performance by eliminating wastes (Ws). In this study, authors have identified manufacturing related critical wastes for enhancing the manufacturing competitiveness with the help of industry experts and literature. For the effective VSM implementation, these wastes have categorised into three groups named as; seven deadly waste; knowledge waste and administrative waste. The goal of present work is to understand the mutual interaction between these wastes and to identify the ‘driving wastes’ (i.e. which influence the other wastes) and the ‘dependent wastes’ (i.e. which are influenced by others). The research theme has divided into three segments; (1) identified the wastes from literature and industry experts, and conducted interviews with experts through a questionnaire in the form of waste relationship matrix (2) prepared an ISM based framework and finally, (3) cluster analysis has done through fuzzy MICMAC. Interpretive structural modeling has been used to analyse the relationships among these manufacturing wastes. Fuzzy MICMAC (cross-impact matrix multiplication applied to classification) has been used to find out driving and the dependence power of identified waste. To determine the driving and the dependence power of various wastes the final results of interpretive structural modeling are used as input to the fuzzy MICMAC analysis. The finding of this study reveals that overproduction (W4) and unclear customer (W11) are a matter of concern and need maximum attention for enhancing manufacturing performance. The enterprises and the decision-makers can be benefited from this model to identify which manufacturing wastes are performing as the most deleterious.

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Acknowledgements

The authors would like to thank experts from industry and academia for giving their valuable opinion regards wastes identification under VSM. Finally, authors thank anonymous reviewers for their comments and suggestions on the earlier version of this article.

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  1. Department of Mechanical Engineering, Maulana Azad National Institute of Technology, Bhopal, M.P., 462003, India

    Lakhan Patidar, Vimlesh Kumar Soni & Pradeep Kumar Soni

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  1. Lakhan Patidar
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  2. Vimlesh Kumar Soni
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Correspondence to Lakhan Patidar.

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Patidar, L., Soni, V.K. & Soni, P.K. Manufacturing wastes analysis in lean environment: an integrated ISM-fuzzy MICMAC approach. Int J Syst Assur Eng Manag 8 (Suppl 2), 1783–1809 (2017). https://doi.org/10.1007/s13198-017-0669-6

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