Scrutinizing IoT applicability in green warehouse inventory management system based on Mamdani fuzzy inference system: a case study of an automotive semiconductors industrial firm

被引:17
|
作者
El Jaouhari, Asmae [1 ]
El Bhilat, El Mehdi [2 ]
Arif, Jabir [3 ]
机构
[1] Sidi Mohamed Ben Abdellah Univ, Higher Sch Technol, Lab Technol & Ind Serv, Fes, Morocco
[2] Mohammed V Univ, Res Lab Management Org, Rabat, Morocco
[3] Abdelmalek Essaadi Univ, Natl Sch Appl Sci, Lab Modeling & Optimizat Ind Syst & Logist, Tetouan, Morocco
关键词
Green warehouse inventory management; Internet of Things; fuzzy inference system; performance; sustainability; Mamdani; SUPPLY CHAIN; THINGS IOT; IMPERFECT QUALITY; DECISION-MAKING; FAULT-DETECTION; MODEL; SUSTAINABILITY; INTERNET; OPTIMIZATION; FRAMEWORK;
D O I
10.1080/21681015.2022.2142303
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Over the last three decades, sustainability has been increasingly essential and it is a crucial facilitator for building resilient warehouse inventory systems. Uncertainty influences qualitative criteria for evaluating Green Warehouse Inventory Management performance. According to researchers, technological innovations such as the Internet of Things could be used to help warehouse inventory operations achieve long-term sustainability. An Internet of things-based fuzzy set theory model is developed in this paper for dealing with language inaccuracy and uncertainty in human judgment. It is also the first to use the Mamdani Fuzzy Inference System to assess a company's Green Warehouse Inventory Management performance in terms of green metrics. The suggested model reveals that the green delivery dimension has the greatest impact on firm performance, based on data gathered from a case company. Numerous defuzzification approaches have been used to demonstrate the resilience of the proposed FIS model. [GRAPHICS]
引用
收藏
页码:87 / 101
页数:15
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