A.I. equipment tackles health monitoring and predictive maintenance
Mike Edwards
Features AI artificial intelligence cloud
New cloud-based, IoT-enabled equipment health monitoring and predictive maintenance systems are the first of many exciting AI-based (artificial intelligence) smart manufacturing applications to combine embedded human knowledge and advanced engineering automation to address long-term production challenges facing automotive, industrial, biopharma, and oil and gas manufacturing.
These include:
- Machine downtime due to unexpected equipment failure caused by excessive vibration, heat, and usage.
- High replacement cost of parts due to a lack of real-time health insights that predict component failure.
- Long repair times due to a lack of preparedness caused by unexpected shutdowns.
- Inefficient, antiquated maintenance programs that drive up costs.
- Siloed data that create huge inefficiencies across the factory due to a lack of plant wide or region-wide equipment health status that assess equipment health
https://youtu.be/tnkHizpnYW4
A new technology solution that was recently described in a white paper is GrandView Asset Performance Management (APM), which integrates AI-powered fault detection, classification and predictive maintenance smart manufacturing applications on the Cloud and powered by the Metatron IoT platform. (See view demo above)
GrandView addresses some of the big issue facing manufacturers by providing:
- Factory-wide equipment health insights
- Real-time monitoring and prediction
- Data driven maintenance strategy
- Global visibility for all stakeholders at all levels of operation
By detecting, and analyzing real-time streaming and historical data, leveraging powerful predictive analytics, GrandView saves manufacturers time and expense by reducing two of the leading losses for the manufacturing industry: equipment failure, and downtime.
To read more of this white paper from BIStel, download it here
Print this page
