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Intelligent analytics for industrial manufacturing

By 4Manufacturing(R) 25/06/2020

QA engineers often need to understand why a particular problem keeps happening

Field engineers and service teams often lack data and digital insights needed to assess, troubleshoot, and determine work scope for the large industrial assets in performing corrective and preventative maintenance activities. QA engineers many times need to understand why a particular problem in the part is happening recurrently or why parts from suppliers don’t stack up well in the assemblies due to mismatch. The root cause is usually hidden in design, manufacturing processes, supply chain logistics or production planning. But without the right data and digital insights, it's hard to pinpoint. GOAL To collect information in the design, manufacturing, service, supply-chain setup and provide access to and intelligent analytics for industrial manufacturing and performance data, to identify the root cause easier. Such insights can improve not only service and owner/operator productivity, but also provide critical feedback to the design engineering and manufacturing operations teams for continuous improvement.

Read the full case study: https://www.iotone.com/casestu...

Thank you to www.iotone.com for sharing the case study. 

Production Efficiency Factory floor & Production systems Quality Management Flexible manufacturing IIoT & Connectivity Continuous Improvement Value Chain Integration Predictive Maintenance Data Analytics AI & ML