Publication Type : Conference Proceedings
Publisher : International Conference on E-business and supply chain competitiveness, EBSCC 2016. Indian Institute of Technology.
Source : International Conference on E-business and supply chain competitiveness, EBSCC 2016. Indian Institute of Technology, Kharagpur, IITK , p. 439, 2016.
Campus : Coimbatore
School : School of Engineering
Department : Mechanical Engineering
Year : 2016
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.
Cite this Research Publication : Tharun Thomas, Priya Harikumar, and Dr. Saleeshya P.G., “An ISM based model for finding the root causes of eight forms of wastes in lean manufacturing”, International Conference on E-business and supply chain competitiveness, EBSCC 2016. Indian Institute of Technology, Kharagpur, IITK , p. 439, 2016.