Barriers for the Implementation of Industry 4.0 in Storage Drive Manufacturing Industry

IF 2.5 Q2 ENGINEERING, INDUSTRIAL
Thurein Lin, Jirapan Liangrokapart
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引用次数: 0

Abstract

Employing advanced technology in manufacturing will improve productivity and resource efficiency as well as reduce long term operating cost. Storage drive manufacturers focus on the advanced technology adoption as a way to reduce their operating cost. Despite many benefits of Industry 4.0, integration and implementation are not easily achievable. This research aims to identify the barriers of Industry 4.0 implementation in storage drive industry in the context of hard disk drive (HDD) and solid-state drive (SSD) manufacturing and to suggest guidelines to overcome the barriers. Starting from extensive literature review, followed by expert justification, 15 barriers for the implementation of Industry 4.0 in storage drive manufacturing industry were identified. The fuzzy AHP approach was used to prioritise the barriers. The study found that for both HDD and SSD industries, ‘economic’ criteria is the priority followed by ‘technology’ and ‘organisation’ criteria. The result suggests that decision makers should find avenues to overcome these three barriers before implementing Industry 4.0 in the storage drive manufacturing industry. Getting sufficient financial fund for capital investment, being technological-oriented organisation and getting strong management support for new technology are the main guideline for the industry. The research methodology in this study could be applied in other manufacturing industries to identify barriers and plan for strategic actions before the intelligent manufacturing implementation.

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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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