IoT Sources is always on the lookout for successful IoT case studies and practical IoT use cases. Predictive maintenance is a core initiative for every company in the oil and gas and chemical processing industries. As such, when we find a good predictive maintenance case study, we feel compelled to bring it to the forefront. Texmark is one such company that has used IoT-based solutions to build an excellent predictive maintenance model. With their model, Texmark has increased their mean time between failures and can more quickly identify causes of the failures. In addition to helping the company anticipate and prevent asset failures before they happen, Texmark expects to realize a 50 percent reduction in planned maintenance costs. With the next phase of their Refinery of the Future project they plan to integrate advanced video analytics, connected worker, and complete lifecycle asset management.

The chemical processing industry, as is the closely related oil and gas refining sector, are extremely capital-intensive businesses, with huge inventories of physical assets and facilities, from pumps to pipelines connected to units, streams, and fluid systems.

While these plants lead the way with the latest technologies, they are usually slow in adopting digital approaches to monitoring operations, due to concerns about disrupting safety procedures. Texmark Chemicals sought to change this mindset, setting out on an ambitious quest to build the “Refinery of the Future” — a highly intelligent, integrated, and automated assembly of systems and people.

Read the full case study on RT Insights

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