Abstract
PurposeThe purpose of this paper is to evaluate the impact of lean criteria on leanness as well as prioritize them, taking the relationships between dimensions into consideration for manufacturing enterprises.Design/methodology/approachThis study considers leanness over quality, cost, delivery and innovation (QCDI) performance dimensions. Twenty eight criteria related with these dimensions were determined that are focused on manufacturing organizations and then fuzzy analytic network process (ANP) approach was used to determine the influence value of each criterion on leanness.FindingsThe existing literature shows a lack of studies on systematically measuring the impact of lean criteria on leanness. To fill the gap, this paper presents a fuzzy ANP approach. Firstly interactions between the performance dimensions were configured. Then, according to the relationship, weights were obtained while taking the network structure that allows dynamic multidirectional relationships for interdependencies among performance dimensions into consideration. This provides a more accurate approach for determining the impact value on leanness performance in real-life decision-making environments.Research limitations/implicationsThe limitation of this study is that only manufacturing enterprises have been considered. Different criteria may need to be developed for service organizations.Practical implicationsThis study gives a real insight to lean practitioners in the manufacturing system. Due to the fact it is difficult to achieve all the criteria at the same time for a company, this study is significant for manufacturers, indicating which criteria should primarily be focused on in order to achieve leanness.Originality/valueApplying fuzzy ANP on interrelated QCDI performance dimensions to evaluate the impact of lean criteria on leanness is the novelty of this study in the related literature. The fuzzy ANP approach is thought to be a more suitable approach to obtain more realistic and accurate results with the power to cope with ambiguity. This study provides a systematic measurement of the influence of lean criteria, also considering interdependencies between performance dimensions. Another contribution of this study is adding innovation to the performance dimensions that are commonly known as quality, cost and delivery to assess leanness in a comprehensive manner.
Subject
Industrial and Manufacturing Engineering,Strategy and Management,Computer Science Applications,Control and Systems Engineering,Software
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