Address business crisis caused by COVID‐19 with collaborative intelligent manufacturing technologies. Issue 2 (26th June 2020)

• Record Type: Journal Article
• Authors: Shen, Weiming; Yang, Chen; Gao, Liang
• Is Part Of: IET collaborative intelligent manufacturing. Volume 2:Issue 2(2020)
• Page Start: 96
• Page End: 99
• Publication Date: 2020-06-26
• Subjects: job shop scheduling -- production facilities -- production management -- manufacturing industries -- intelligent manufacturing systems -- production engineering computing; address business crisis -- COVID‐19 -- collaborative intelligent manufacturing technologies -- manufacturing industry -- supply chain breakages -- difficult shop floor operations -- resilient collaborative supplier networks -- collaborative planning -- geographically distributed manufacturing plants -- different shop floors -- digital twins technologies; Production management -- Periodicals; Production engineering -- Periodicals; Production management; Production engineering; Electronic journals; Periodicals; 658.5
• DOI: 10.1049/iet-cim.2020.0041
• Languages: English
• ISSNs: 2516-8398

Abstract

Abstract : While COVID‐19 has affected the daily life of almost everyone around the world, it has also caused major disturbances to the global economy and to the operations of many businesses in the manufacturing industry. Reginal lockdowns resulted in supply chain breakages. Workforce shortages caused difficult shop floor operations. This study tries to discuss how collaborative intelligent manufacturing technologies can help to address these challenges through (i) optimal design of resilient collaborative supplier networks; (ii) collaborative planning of manufacturing operations among geographically distributed manufacturing plants; (iii) functional redundancy and dynamic reconfiguration of different shop floors; (iv) dynamic intelligent rescheduling of workforces for factory/shop floor operations; (v) remote testing and maintenance of manufacturing equipment with the support of digital twins technologies. These approaches are expected to be an effective hedge against the impact of COVID‐19 or other natural disasters.