Predictive Maintenance Value for Process Industries

PM

Process industries are undergoing digital transformation building and integrating Minimum Viable Products (MVPs) in their strategic path to enabling business models, services, customer experience, operations, and workplaces re-imagination. What I notice across process industry segment is application of industrial internet concepts in creating predictive maintenance models that are yielding advantages including – greater machine availability, superior process quality, easier to plan service intervals, longer machine service life, safer and more sustainable operation, lower service efforts and decreased costs. I am highlighting few aspects demonstrating thought leadership in this space.

  • Companies are sponsoring proof of concepts and pilots for creating models to monetize predictive maintenance. As Predictive Maintenance and Condition Based Monitoring directly impact equipment uptime, by offering Predictive Maintenance as a service, the manufacturer can guarantee equipment uptime to their customers for a fees, i.e. selling value-added services which promise recurring revenue.
  • Process manufacturing is leveraging integrated utilities to reducing electricity consumption with just-in-time energy management with a dynamic platform delivering energy performance improvement with ‘as-a-service’ through edge connectivity of various assets, data acquisition and gateway, cloud-based technology, and analytics. Also include tracking people movement and asset utilization.
  • SRP performance monitoring center using Industrial Internet is another classic example. Since starting the GE Digital’s SmartSignal program in 2012 and through to 2016, SRP identified more than 1,900 issues, of which 800 were “catches” – a problem that the plant was not previously aware of and, with the new alerts, was able to take corrective action. With time and improved training of the algorithms, the rate at which the company identifies true issues and catches has improved.
  • One use case of specific interest to Food and Pharma industry’s glass packaging quality control and improvement is Wi-NEXT IIoT that drives major changes in glass container quality improvement reducing non-conforming products by 7%, which equals 5% extra line productivity, better process control, and higher customer satisfaction
  • Lastly sustainable business models of predictive maintenance includes – bundling within basic service agreement framework, a freemium offering during warranty with downstream revenue potential, offer value added service with pay-per-use model, and gain-sharing with partner ecosystem.

Process manufacturing winners are those who identify best in class practices for developing business models for predictive maintenance of equipment. Win-win scenarios for manufacturers arise from enabling collaboration of experts in this space to exchange ideas, spot trends and drive innovations.

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