Industrial Engineering and Management Applications: Evaluation of Data Integration Tools for Smart Manufacturing

Abstract

This study comprehensively evaluates leading data integration tools for smart manufacturing environments using a hybrid Analytic Hierarchy Process (AHP) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology. As Industry 4.0 drives increased automation and data exchange in manufacturing processes, selecting appropriate data integration tools has become critical yet complex. We assessed seven prominent data integration tools across 24 criteria grouped into six main categories: functionality, vendor-related factors, user experience, cost, reliability, and flexibility. Our data collection was informed by expert interviews, vendor documentation analysis, user reviews, and benchmark testing. The AHP analysis revealed functionality and data integration features as the most crucial criteria (weight: 0.2493), followed by user-related factors (0.1814). The VIKOR method then ranked the tools, with Oracle Data Integrator emerging as the top performer (Q=0.0000), followed by Informatica PowerCenter (Q=0.22391). Our findings highlight the importance of cloud-native solutions and user experience in industrial data integration. This research contributes a robust framework for evaluating data integration tools in imaginative manufacturing contexts and offers insights to guide decision-making in Industry 4.0 initiatives.

Keywords

• Smart manufacturing
• Data integration tools
• Multi-criteria decision making
• Analytic hierarchy process (AHP)
• VIKOR method
• Industrial engineering

References

1. Nguyen, V.T.T., & Vo, T.M.N.. (2024). Industrial engineering and management applications: Evaluation of data integration tools for smart manufacturing. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 29, 255-263.