Belhadi, A. and Zkik, K. and Cherrafi, A. and Yusof, S.M. and El fezazi, S. (2019) Understanding Big Data Analytics for Manufacturing Processes: Insights from Literature Review and Multiple Case Studies. Computers and Industrial Engineering, 137.

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Today, we are undoubtedly in the era of data. Big Data Analytics (BDA) is no longer a perspective for all level of the organization. This is of special interest in the manufacturing process with their high capital intensity, time constraints and given the huge amount of data already captured. However, there is a paucity in past literature on BDA to develop better understanding of the capabilities and strategic implications to extract value from BDA. In that vein, the central aim of this paper is to develop a novel model that summarizes the main capabilities of BDA in the context of manufacturing process. This is carried out by relying on the findings of a review of the ongoing research along with a multiple case studies within a leading phosphate derivatives manufacturer to point out the capabilities of BDA in manufacturing processes and outline recommendations to advance research in the field. The findings will help companies to understand the big data analytics capabilities and its potential implications for their manufacturing processes and support them seeking to design more effective BDA-enabler infrastructure. © 2019 Elsevier Ltd

Item Type: Article
Uncontrolled Keywords: Advanced Analytics; Big data; Competitive intelligence; Industrial research; Manufacture, Capital intensity; Literature reviews; Manufacturing process; Multiple-case study; Time constraints, Data Analytics
Subjects: Computer Science
Divisions: SCIENTIFIC PRODUCTION > Computer Science
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:45

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