Purpose It is difficult for anyone to implement all the lean tools simultaneously. One of the core issues is identifying critical criteria for the successful implementation of lean manufacturing (LM) and evaluating them. The purpose of this paper is to analyze the causal relationships of LM criteria in a machine tool manufacturing firm located in national capital region of India using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. Design/methodology/approach The research paper presents a blend of theoretical framework and practical applications. Based on literature review, 17 LM criteria were extracted that were validated by experts. A questionnaire was developed that was answered by experts serving in the XYZ machine tool manufacturing firm. Then, the DEMATEL method was applied to analyze the importance of criteria and the casual relations among the criteria were developed. Findings Using DEMATEL, the lean criteria were divided into cause group and effect group. In this study, information technology, computer-integrated manufacturing, enterprise resource planning, training, fixed position layout, smart processes and automation and concurrent engineering were classified in the cause group. Just in time, value stream mapping, 5-S, single minute exchange of die, visual control, job scheduling, standardized work, cellular manufacturing, poka-yoke, and total quality management were categorized in the effect group. The DEMATEL framework indicates that “training” is the most influencing factor for the lean implementation process in machine tool sector. Originality/value To know the key lean criteria and relationship among them can help many organizations to develop lean competencies. If the authors want to obtain high performance in terms of the effect group factors, it would be necessary to control and pay a great deal of attention to the cause group factors beforehand. This study is perhaps among the first few with focus on segmenting the set of lean criteria into some meaningful portions in order to effectively facilitate its implementation. The paper provides useful insights to the lean production implementers, consultants, and researchers.
