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Predictive maintenance is one application planned for a new alliance that will bring Internet of Things capability to users of OSI's PI solution.
Petasense and OSIsoft LLC have launched a partnership designed to drive the adoption of Internet of Things (IoT) technologies in process and manufacturing plants. The new venture will enable users of OSI's PI data historian software to retrofit their machinery with Petasense's wireless sensors and machine language analytics to perform predictive maintenance using both asset and process control data.
The partners predict that this approach will help eliminate unplanned downtime, improve safety, and reduce maintenance and equipment repair costs. According to estimates by ControlGlobal.com, predictive maintenance could prevent nearly 80% of production downtime, saving $20 billion/year in the petrochemical industry alone.
“The first step in IoT for many industrial companies and utilities is capturing data from their legacy equipment. Many of these systems are years, if not decades, old and weren’t created with digital [technology] in mind,” said Pat Kennedy, CEO of OSIsoft.
Petasense offers an end-to-end IoT-based predictive maintenance system based on wireless vibration sensos, cloud-based software and machine learning-based data analytics that has been designed to predict the health of rotating machinery such as motors, pumps, and compressors.
By analyzing vibration characteristics, Petasense software can detect problems such as cavitation, bearing wear and misalignment before they result in equipment failure. The software calculates a "machine health" score for equipment in real-time, allowing plant managers to decide whether or not to keep a piece of equipment running.
This predictive maintenance analytics system will connect with OSI's PI, which captures data from sensors, manufacturing equipment, and other devices and transforms it into real-time insights to reduce costs, improve overall productivity and create new services.
“With IIoT it is possible to retrofit machinery with sensors and collect maintenance data at a size and scale that was unimaginable before,” said Arun Santhebennur, cofounder of Petasense. “Any site that uses PI will be able to easily deploy and implement predictive maintenance at an extremely affordable price point,” he adds.
Source: Press Release