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 becomes whether the money spent 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, increasing costs and squandering precious maintenance resources (time, tools, parts and labor).
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.
How can an EAM solution help
Management and/or mitigation of risk due to failure of critical assets is the foundation of asset management. Identifying risk and establishing controls is essential to transform an organization’s asset management approach from reactive to predictive. Predictive Asset Analytics can proactively address potential safety risks and compliance issues by analyzing both historical and current data from multiple sources like SCADA (Supervisory Control and Data Acquisition), online monitoring systems, and non-operational data (industry standards, operational practices) to build predictive models. One can use these models to generate risk scores which, in turn, can help you understand the implications of events and the necessary action.
Choosing the right asset management software is the key to maximize value and efficiency. IBM Maximo Asset Health Insights, for instance, can access multiple data sources in real time to predict asset failure, which can help mitigate downtime and reduce your maintenance costs. Use Maximo to detect anomalies and failure patterns and identify assets or processes that are at the highest risk for failure.
Technological advancements like the Internet of Things (IoT) also 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. IoT can be integrated with work management to create closed loop reporting, alerts and work requests. Motors@Work IoT application, for instance, associates near real-time energy data with motor system design plus operational and DoE metrics as the basis for condition monitoring alerts.
As a long standing and trusted partner of IBM, ValuD (through AME, our Maximo services company) has been providing implementation and support services for IBM Maximo since 4.0. Motors@Work is a scalable, cloud based solution that provides the information and intelligence that will save you energy, reduce maintenance costs, and improve motor-driven system asset performance. The out-of-the-box solution integrates seamlessly with existing asset management systems like IBM Maximo, leveraging current technology investments.
To learn more on how ValuD can help leverage Maximo and IoT for your asset management strategy, contact us at email@example.com.
 Bever K, Enterprise Systems Integration: Opportunities & Obstacles Developing Plant Asset Management Systems March 13, 2000 (Presented at National Manufacturing Week, Chicago, Illinois)