Lean tool selection in a die casting unit: a fuzzy-based decision support heuristic
Lean manufacturing philosophy asks for elimination of wastes hidden in the manufacturing system by focusing on product value stream and eliminating non-value adding activities through continuous improvement efforts. Value stream mapping methodology is subjected to principles of continuous improvemen...
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Published in: | International journal of production research Vol. 44; no. 7; pp. 1399 - 1429 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
London
Taylor & Francis Group
01-04-2006
Washington, DC Taylor & Francis Taylor & Francis LLC |
Subjects: | |
Online Access: | Get full text |
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Summary: | Lean manufacturing philosophy asks for elimination of wastes hidden in the manufacturing system by focusing on product value stream and eliminating non-value adding activities through continuous improvement efforts. Value stream mapping methodology is subjected to principles of continuous improvement in order to improve the productivity of the process and quality of the product. It provides various tools for data collection and analysis, and identifies the wastes occurring in different stages of manufacturing process. The role of value stream mapping is very important in the identification and subsequently reduction of the wastes. To select the detailed mapping tools for the identification of waste at micro level is a complex decision making problem. In this paper, a case study related to a die casting unit has been taken. A hierarchy related to the decision problem has been developed to select the value stream mapping tools. Here, a fuzzy logic based multi-preference, multi-criteria, and multi-person decision making heuristic has been developed to solve a problem pertaining to above case study. The proposed methodology enjoys logical support from existing decision making tools and pertinently maps the inside details of the underlying problem. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0020-7543 1366-588X |
DOI: | 10.1080/00207540500272980 |