Harness the power of IoT for condition-based and predictive maintenance
Did you know:
- 82% of asset failures occur randomly and do not have an age-related failure pattern 
- On an average, 18%-30% of every dollar spent on maintenance is wasted.
Age-related failure is the basis for preventive maintenance. The older the asset, the higher the frequency of maintenance–this kind of time-based cycle has always been the accepted industry practice. But when time-based maintenance activity is not effective, the question arises as to whether the money spent on such activities is really worth the investment.
Preventive maintenance costs versus asset reliability
ARC Advisory Group’s Enterprise Asset Management and Field Service Management Market Study finds that an average company can reduce its maintenance costs up to 50%. ARC identifies the primary KPIs for asset performance as higher uptime and asset longevity. The argument is that sometimes over-maintaining may do more harm than good by increasing costs and squandering precious maintenance resources.
A study by Oniqua Enterprise Analytics found that 30% of preventive maintenance activities were carried out too frequently while 19% of preventive maintenance activities were a waste of time. With more than three-fourths of your assets having a random (and not age-related) failure pattern, your preventive maintenance activities may not be effective. Companies are challenged to balance maintenance investments versus asset reliability.
Rather than executing maintenance based on a set interval, listening to your assets can provide valuable insight. Monitoring temperature, pressure, vibration, voltage imbalances and other measures can be strong indicators. If any of these conditions are outside of acceptable parameters, then it signals the need for maintenance investigation. This kind of condition-based maintenance is predictive in nature and can help increase asset uptime and reduce asset life cycle costs.
IoT and predictive maintenance
Technological advancements like the Internet of Things (IoT) makes it easier for predictive maintenance activities like condition-based monitoring since it eliminates the need for human-to-human or human-to-computer interaction. Use of a smart meter, for instance, can help you monitor changes in temperature, pressure, airflow, sound, vibrations or motion. IoT applications can take maintenance intelligence to the next level. IoT can be integrated with work management and create closed loop reporting, alerts and work requests.
Prashant Kumar is Practice Manager for M@W & Maximo. He has 10 years’ experience in business consulting and IT management for IBM TRIRIGA and Maximo projects. Prashant leverages his experience as a business analyst, project manager, process consultant, data guru, to provide expertise across Operations and Maintenance modules. He is an IoT enthusiast and loves building solutions to improve efficiency, conserve energy, and reduce costs. Previously he worked with Infosys & IMRB International and has degrees in Electrical Engineering and an MBA. This article originally appeared on Motors@Work, a CFE Media content partner.