From Machines to Insights: GE Predix Leading the Industrial Internet Transformation
Jiarui Zhang ()
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Jiarui Zhang: Xi’an Jiaotong-Liverpool University, International Business School Suzhou
A chapter in Proceedings of the 2025 International Conference on Hybrid Commerce, Human Capital, and Economic Dynamics (ICHCH 2025), 2026, pp 383-392 from Springer
Abstract:
Abstract Facing structural challenges such as data silos, high maintenance costs, legacy equipment integration issues, and linear business models, traditional manufacturing enterprises urgently need digital transformation to maintain competitiveness. Leveraging the Industrial Internet concept introduced by General Electric (GE) in 2012, this study systematically analyzes GE’s Predix platform--a cloud-based PaaS specifically designed for industrial workloads. By examining Predix’s technical architecture, core functionalities, and cross-industry applications through literature reviews and case studies, the research highlights substantial improvements in operational performance, including reductions in unplanned downtime by 20-25%, increases in energy production efficiency by 2.7-4.7%, and significant maintenance-cost savings. The study concludes that Predix’s integration of edge computing, predictive maintenance algorithms, digital twins, and cloud-native microservices provides an effective, replicable framework for intelligent industrial upgrades and sustainable development across capital-intensive sectors. By fostering a comprehensive digital ecosystem, Predix helps enterprises transi-tion toward sustainable, flexible, and responsive manufacturing models, aligning with contemporary Industry 4.0 objectives. It also highlights a replicable frame-work for other capital-intensive industries seeking to implement digital transfor-mation strategies effectively.
Keywords: Industrial Internet; Digital Transformation; Predix Platform; Industry 4.0; Manufacturing Digitization; Digital Twin (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-2-38476-585-0_44
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DOI: 10.2991/978-2-38476-585-0_44
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