Business analytics specialist SAS Software is rolling out a new Predictive Asset Maintenance (PAM) offering built atop its Service Intelligence Architecture data integration server. SAS PAM promises ‘optimized, sustainable maintenance strategies’ and improved equipment performance and availability. PAM leverages near-real-time monitoring and alerts generated by predictive models to ‘proactively address’ potential performance issues before they cause downtime or increase the length of planned shutdowns.
SAS is to leverage its predictive data mining capabilities to drive ‘continuously improved’ reliability and equipment efficiency. Analytics also identifies what is really affecting equipment performance from the hundreds or thousands of sensor tags and other measurements.
SAS’ ‘maintenance-centric’ data model captures data from legacy and modern MES, ERP, CMMS systems. PAM then transforms and cleanses the data for consumption by a wide range of stakeholders. The PAM data model is claimed to overcome the barriers imposed by ‘siloed’ operational systems. PAM’s automatic engine continuously monitors asset health, testing new sensor or condition data against defined rules and thresholds. These are then analyzed using SAS’ JMP front end. PAM is designed for use by both operations and maintenance workers and senior-level managers responsible for quality, productivity and supply chain costs.
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