A roadmap for Assembly 4.0: self-configuration of fixed-position assembly islands under Graduation Intelligent Manufacturing System. Issue 15 (2nd August 2020)

• Record Type: Journal Article
• Authors: Guo, Daqiang; Zhong, Ray Y.; Ling, Shiquan; Rong, Yiming; Huang, George Q.
• Is Part Of: International journal of production research. Volume 58:Issue 15(2020)
• Page Start: 4631
• Page End: 4646
• Publication Date: 2020-08-02
• Subjects: Assembly 4.0 -- intelligent manufacturing system -- fixed-position assembly -- self-configuration -- cloud-based services; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2020.1762944
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : The layout of fixed-position assembly islands (FPAI) is widely used for producing fragile or bulky products. With the increasing customised demand and unique operation patterns, manufacturing practitioners are facing challenges on flexible and efficient production arrangement to meet customer demand, which lead to inappropriate assembly islands configuration, frequent setups and long waiting times in FPAI. Industry 4.0 comes with the promise of improved flexibility and efficiency in manufacturing. In the context of Industry 4.0, this paper proposes a 5-layer APICS (a ssembly layer, p erception layer, i nteraction layer, c ognition layer, and s ervice layer) roadmap for transformation and implementation of Assembly 4.0. Following the 5-layer APICS roadmap, a Graduation Intelligent Manufacturing System (GiMS) is presented as the pioneering implementation in FPAI. A graduation-inspired assembly system is designed for FPAI at assembly layer. Internet of Things (IoT) and industrial wearable technologies are deployed for perception, connection, and collaboration among various manufacturing resources at perception and interaction layer. A self-configuration model is proposed at cognition layer for autonomously configuring optimal assembly islands and corresponding production activities to meet customer demand. Cloud-based services are developed for managers and onsite operators to facilitate their decision-making and daily operations at service layer. Finally, a demonstrative case is conducted to verify the feasibility of the proposed methods.