选择(遗传算法)
多准则决策分析
计算机科学
背景(考古学)
专家意见
集合(抽象数据类型)
项目管理
六西格玛
过程管理
运筹学
精益制造
管理科学
运营管理
业务
系统工程
人工智能
工程类
医学
生物
古生物学
重症监护医学
程序设计语言
作者
Dounia Skalli,Anass Cherrafi,Abdelkabir Charkaoui,Andrea Chiarini,Jamal El Baz,Nadia Hamani
标识
DOI:10.1080/14783363.2024.2315427
摘要
Manufacturers are adopting Lean Six Sigma4.0 (LSS4.0) to improve their operations. However, poor project selection results in substantial losses. The aim of this study is to provide a framework for LSS4.0 project selection in an industrial context using the Best-Worst-Method (BWM)-based 'multi-criteria decision making' (MCDM) technique. First, 25 project selection criteria were pre-selected using a literature review and expert opinions. All criteria were then grouped into six different dimensions, closely related to the LSS4.0 principles, based on expert opinion and similarity with literature findings. To finalize the selection, a rigorous evaluation is undertaken using corrected item-total correlation (CIMTC) and importance index analysis methods, resulting in a final set of 22 project selection criteria, prioritized using BWM. The practical applicability of this method is demonstrated by a case study in a Moroccan manufacturing context. Operational and technical feasibility, strategic orientation, finance and business development emerged as top priorities. This research can help senior managers make informed choices about projects and recognize potential in uncertain scenarios.
科研通智能强力驱动
Strongly Powered by AbleSci AI