During a panel at the SIIA Propelling IoT: Emerging IoT Business Opportunities event in Houston, TX, I shared examples of how the IIoT affects business outcomes in the industrial sector. Anyone who keeps up with the IIoT knows it is often a situation of crawl, walk, run before you start seeing real ROI. But once you are running, it is simple to duplicate that success, whether you are reducing operational cost, increasing yield and quality of products, reducing downtime or improving safety.
The level everyone is trying to reach is prognostics—what are the next best actions to undertake? The people in the field don’t have time to think about this stuff. They just need to know what is failing or when it is going to fail or what maintenance do they need to do next.
Prognostics is key in answering these questions—connecting live machine data with tagged events, labeled data and maintenance data.
With the right data sets, a company can move toward algorithmic spare-part refurbishment while generating mechanical repair or work orders with specific instructions on the repair, all while publishing a maintenance-repair video on a working 3D digital twin. There is a lot of opportunity for oil and gas companies to provide these types of Industrial IoT solutions in their operations, and some of the high-value equipment they can use includes hydraulic fracking units, cat walks, top drives, mud pumps, etc. For petrochemical plants and refineries, some of the equipment includes cracking units, reactors, valves and pumps.
Using artificial intelligence, companies can start turning the ship around on their operations—moving from a reactive mode to a predictive/preventative modes, which enable companies to unlock revenue streams buried in the data.
I recommend having a workshop with the right decision makers and stakeholders within an organization, equipped with a budget and IIoT-value KPIs. Find a business problem to solve first, versus trying to sell a solution that may not fit the business case. Do your homework on the target market, target customer and know your customer and the business problems they are trying to solve. Then bring in subject-matter experts that know the process, the equipment and operations very well.
- Rick Harlow ( Executive vice president of Americas at Flutura Decision Sciences and Analytics)
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