Lean holistic fuzzy methodology employing cross-functional worker teams for new product development projects: A real case study from high-tech industry


YILMAZ Ö. F. , ÖZÇELİK G. , YENİ F. B.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol.282, no.3, pp.989-1010, 2020 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 282 Issue: 3
  • Publication Date: 2020
  • Doi Number: 10.1016/j.ejor.2019.09.048
  • Title of Journal : EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
  • Page Numbers: pp.989-1010

Abstract

This paper addresses a lean holistic fuzzy methodology for the new product development (NPD) projects to cope with the uncertainties encountered in the projects by placing an emphasis on the cross-functional worker teams along with utility workers' impact on the lead time and total operational cost. To this end, the fuzzy design structure matrix (FDSM), the fuzzy value stream mapping (FVSM), and a novel fuzzy optimization model are combined and employed sequentially for visualizing all processes, decreasing lead time and operational cost, and determining the improvement points. While the whole methodology focuses on reducing the lead time by creating the worker teams, the fuzzy optimization model aims to decrease the total operational costs. The study is conducted in a startup, which has begun to reorganize its NPD projects according to lean principles by implementing the proposed methodology. The effectiveness of the methodology to reduce the lead time and the operational cost is shown in the results based on the data taken from the startup. To analyze the impact of parameters on the total operational cost in terms of the total number of workers (w.r.t. normal and utility) and the lead time as well, the computational experiments are carried out through a set of parameter values and a-cut levels. According to the results, the proposed methodology leads to a decrease in both the lead time and the total operational cost thanks to employing the utility worker concept. (C) 2019 Elsevier B.V. All rights reserved.