Analysis of lean practices in manufacturing industries: an ISM approach

Q3 Engineering

International Journal of Six Sigma and Competitive Advantage Pub Date : 2019-03-19 DOI:10.1504/IJSSCA.2019.10020041

M. Chand, Suraj, O. P. Mishra

引用次数: 1

Abstract

The role of lean manufacturing (LM) has increased with an increase competition in global market. A customer wants to buy a product at the lowest possible price without compromising quality. To overcome this problem, the role of lean manufacturing has been introduced. Lean manufacturing is capable for waste reduction without compromising both quality and productivity. To fulfil this purpose, 13 practices of LM have been identified through literature review and expert opinions from academics and industry experts. To identify the cross impact of LM practices, an interpretive structural modelling (ISM) approach have been utilised to find interrelation between these LM practices using MICMAC analysis. Results of this analysis are highly beneficial towards the implementation in industries getting lean.

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制造业精益实践分析:ISM方法

随着全球市场竞争的加剧，精益制造(LM)的作用越来越大。顾客希望以尽可能低的价格购买产品，同时不影响质量。为了克服这个问题，精益生产的作用已经被引入。精益生产能够在不影响质量和生产力的情况下减少浪费。为了实现这一目的，通过文献综述和学术界和行业专家的专家意见，确定了13种LM实践。为了确定LM实践的交叉影响，使用解释结构建模(ISM)方法使用MICMAC分析来发现这些LM实践之间的相互关系。这一分析结果对精益行业的实施是非常有益的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Six Sigma and Competitive Advantage Engineering-Industrial and Manufacturing Engineering

CiteScore

2.00

自引率

0.00%

发文量

期刊介绍： Today, Six Sigma is recognised in many world class organisations as an effective means of achieving and maintaining operational excellence and competitive advantage. Six Sigma has proved to be successful in many manufacturing and service organisations to drive out variability from processes, improve process effectiveness and product/service quality, reduce defect rate, enhance customer satisfaction, etc. IJSSCA publishes papers that address Six Sigma issues from the perspectives of customers, industrial engineers, business managers, management consultants, industrial statisticians and Six Sigma practitioners.