Decision-making on the selection of lean tools using fuzzy QFD and FMEA approach in the manufacturing industry

被引:35
|
作者
Reda, Hiluf [1 ,2 ]
Dvivedi, Akshay [1 ]
机构
[1] Indian Inst Technol Roorkee, Dept Mech & Ind Engn, Roorkee 247667, Uttarakhand, India
[2] Debre Berhan Univ, Dept Ind Engn, DBU, Debre Berhan, Ethiopia
关键词
Value stream mapping; Lean manufacturing; Fuzzy logic; FMEA; Fuzzy weighted geometric mean; QFD; FAILURE MODE; RISK-EVALUATION; PERFORMANCE; SYSTEM; CLASSIFICATION; IMPLEMENTATION; MAINTENANCE; MANAGEMENT; REDUCTION; FRAMEWORK;
D O I
10.1016/j.eswa.2021.116416
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Lean manufacturing is a profound system designed to enhance every manufacturing industry's efficiency by reducing waste through internationally recognized tools and techniques. Manufacturing industries strive to adopt lean concepts to maximize their resources like staff, facilities, materials, and schedules to be economically effective. However, managers face difficulty selecting the appropriate lean tools out of the many available LM tools for successful lean implementation. This study suggests an innovative approach to choose suitable lean tools to maximize these essential resources. Herein the Value Stream Mapping and plant layout are considered for waste identification. Fuzzy QFD and FMEA prioritize the crucial resources concerning the defined wastes and determine the risk associated with each failure mode's sub-element for lean application. It saves time by analyzing only the most critical resources for a successful lean implementation since its focus only on the most important resources. The applicability of the proposed approach is demonstrated through a case study of an Ethiopian shoe manufacturing firm. With the aid of future state plant layout and value stream map, total cycle time is reduced by 56.3%, lead-time is reduced by 69.7%, materials transportation distance and transportation activities are reduced by more than 75%, and workers required are reduced from 202 to 200.
引用
收藏
页数:12
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