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Intelligent industrial assets drive sustainable service supply chains
Journal of Supply Chain Management, Logistics and Procurement,
2
(3),
225-232
(2020)
Abstract
With the rise of the Industrial Internet of Things (IIoT), industrial organisations are capitalising on its promise of boosting operational productivity while reducing cost and risk. More specifically, service and repair supply chains are harnessing machine data to develop a profitable business model that can sustain future disruption. This paper discusses how leading industrial companies are using the intelligence from machines, cloud computing and IIoT to enable predictive maintenance in their supply chains.
Keywords: Industrial Internet of Things (IIoT); operational productivity; service and repair supply chains; machine data; cloud computing
The full article is available to subscribers to the journal.
Author's Biography
Gerald Jackson is Vice President of Digital Product Management for GE Digital. Gerald brings together disruptive technologies of IIOT, edge-to-cloud computing, and machine learning and artificial intelligence (ML/AI) with deep operations, manufacturing and supply chain experience. He has executive responsibility for GE Digital’s Operations Performance Management (OPM) and Supply Chain Management (SCM) product portfolios. Prior to joining GE Digital, Gerald spent 20+ years in operations and supply chain transformation roles at GE, Accenture, Microsoft, and Google. His industry expertise includes high tech, consumer goods, government, retail, chemicals and industrial equipment. His areas of focus in recent years are e2e Supply Chain Optimization, Analytics, and Smart Manufacturing. Gerald is a Lean Six Sigma Master Black Belt and holds a degree in Industrial Engineering from Rensselaer Polytechnic Institute. Gerald is based in Seattle and is an active mentor, speaker, and adviser in the industry.
Citation
Jackson, Gerald (2020, March 1). Intelligent industrial assets drive sustainable service supply chains. In the Journal of Supply Chain Management, Logistics and Procurement, Volume 2, Issue 3. https://doi.org/10.69554/HVXN1655.
© Henry Stewart
Publications LLP
Publications LLP