Lessons from social network analysis to Industry 4.0. (January 2018)

• Record Type: Journal Article
• Authors: Omar, Yamila M.; Minoufekr, Meysam; Plapper, Peter
• Is Part Of: Manufacturing letters. Volume 15:Part B(2018)
• Page Start: 97
• Page End: 100
• Publication Date: 2018-01
• Subjects: 00-01 -- 99-00; Complex networks -- Smart manufacturing -- Industry 4.0; Manufacturing industries -- Periodicals; Production engineering -- Periodicals; Manufacturing industries; Periodicals; 670
• DOI: 10.1016/j.mfglet.2017.12.006
• Languages: English
• ISSNs: 2213-8463

Abstract

Abstract: With the advent of Industry 4.0, a growing number of sensors within modern production lines generate high volumes of data. This data can be used to optimize the manufacturing industry in terms of complex network topology metrics commonly used in the analysis of social and communication networks. In this work, several such metrics are presented along with their appropriate interpretation in the field of manufacturing. Furthermore, the assumptions under which such metrics are defined are assessed in order to determine their suitability. Finally, their potential application to identify performance limiting resources, allocate maintenance resources and guarantee quality assurance are discussed.