OM in the News: A Primer on Predictive Maintenance

“Nearly everyone in manufacturing, from equipment manufacturers to processing plants, commonly face the challenge of keeping their fleet, machinery, and other assets working efficiently, while also reducing the cost of maintenance and time-sensitive repairs,” writes Industry Week (Dec. 6, 2018).  So it is crucial to identify the cause of potential faults or failures before they have an opportunity to occur. Emerging technologies such as the Industrial Internet of Things, data analytics, and cloud data storage are enabling more vehicles, industrial equipment, and assembly robots to send condition-based data to a centralized server, making fault detection easier, more practical, and more direct. By proactively identifying potential issues, companies can deploy their maintenance services more effectively and improve equipment up-time.

Using AI to identify anomalous behavior, the information derived from the equipment sensors can be turned into meaningful and actionable insights for proactive maintenance of assets, thereby preventing incidents that result in asset downtime or accidents. Known as predictive maintenance (a topic we have added to Chapter 17 in our new edition, due out Jan. 1st), this added intelligence enables organizations to forecast when or if functional equipment will fail so that its maintenance and repair can be scheduled before the failure occurs. As industrial customers become increasingly aware of the growing maintenance costs and downtime caused by the unexpected machinery failures, predictive maintenance solutions are gaining even more traction.

Predictive maintenance is also a step ahead of preventive maintenance. As maintenance work is scheduled at preset intervals, maintenance technicians are informed of the likelihood of parts and components failing during the next work cycle and can take action to minimize downtime. In addition to the advantages of controlling repair costs, avoiding warranty costs for failure recovery, reducing unplanned downtime and eliminating the causes of failure, predictive maintenance employs non-intrusive testing techniques to evaluate and compute asset performance trends.

Classroom discussion questions:

1. How do preventive maintenance and predictive maintenance differ?
2. What technologies are allowing predictive maintenance to spread?