CHALLENGES AND CONCEPTUAL FRAMEWORK TO DEVELOP HEAVY-LOAD MANIPULATORS FOR SMART FACTORIES

Industry 4.0 has been one of the emerging topics in recent years, covering a wide range of concepts and applications as well as political, economic and technological views. Manufacturing is becoming smarter and smarter at all levels, moving toward the concept of Smart Factory (SF), based on the adva...

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Bibliographic Details
Published inInternational Journal of Mechatronics & Applied Mechanics Vol. i; no. 8; pp. 209 - 216
Main Authors Le, Chi Hieu, Le, Dang Thang, Arey, Daniel, Gheorghe, Popan, Chu, A M, Duong, X B, Nguyen, T T, Truong, T T, Prakash, Chander, Zhao, Shi-Tian, Mahmud, Jamaluddin, Gao, James, Packianather, M S
Format Journal Article
LanguageEnglish
Published Bucharest Editura Cefin 30.11.2020
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Summary:Industry 4.0 has been one of the emerging topics in recent years, covering a wide range of concepts and applications as well as political, economic and technological views. Manufacturing is becoming smarter and smarter at all levels, moving toward the concept of Smart Factory (SF), based on the advancements of digital transformation technologies, including Artificial Intelligence (AI) and bigdata analytics, and abilities to learn, configure and execute with cognitive intelligence of smart machines and automation systems. However, the SF adoption in practice, especially in Small and Medium-sized Enterprises (SMEs), is still in the early stage. In addition, there are growing demands of product personalisation, mass-customisation and diversification. Therefore, the involvement of humans is still importantly required in many production processes in SF models, where smart machines, smart manipulators, collaborative robots and Automated guided vehicles (AGVs) are required to co-work with humans, leading to an important concern of safety, reliability, productivity and quality of smart manufacturing systems. In this paper, challenges and a proposed conceptual framework to develop smart heavy-load manipulators are presented, with the focus on the cost-effectiveness and applicability in industrial practices of SF for SMEs.
ISSN:2559-4397
2559-6497
DOI:10.17683/ijomam/issue8.58