Title: Analysis of drivers enabling integration of big data analytics with Industry 4.0 in automotive component manufacturing scenario

Authors: Vigneshvaran Regupathy; S. Vinodh

Addresses: Department of Production Engineering, National Institute of Technology Tiruchirappalli, Tamil Nadu, India ' Department of Production Engineering, National Institute of Technology Tiruchirappalli, Tamil Nadu, India

Abstract: Industry 4.0 (I4.0) is associated with technical advancement; yet numerous I4.0 technologies rely significantly on data and interdependence for their operation. The data is accessible in multiple formats; businesses that effectively utilise this data can fully leverage the benefits of Industry 4.0 manufacturing. Big data and I4.0 technologies are interdependent. The interdependent nature of big data renders its integration a more complex and involved procedure. The main objective of this study is to identify the enablers of big data analytics within I4.0 context. The complex characteristics of big data necessitated the utilisation of a multi-criteria decision-making approach to evaluate and prioritise the enablers according to their significance. Sixteen enablers are identified and evaluated with fuzzy TOPSIS approach. Key enablers such as data management, enhanced technical infrastructure, and real-time processing are identified as the most significant facilitators for the integration of big data in the I4.0 production environment.

Keywords: drivers; enablers; big data analytics; integration; Industry 4.0; fuzzy TOPSIS; internet of things; IoT; cyber physical system; CPS.

DOI: 10.1504/IJAOM.2025.148400

International Journal of Advanced Operations Management, 2025 Vol.16 No.3, pp.336 - 350

Received: 22 Nov 2024
Accepted: 07 Jun 2025
Published online: 03 Sep 2025 *

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