Continuous Online Monitoring as the Foundation of a Condition-Based Maintenance Strategy
The shift from Time-Based Maintenance towards Condition-Based Maintenance (CBM) is succinctly illustrated by the P-F curve below, showing the importance of detecting potential failure at the earliest time possible. In other words, extending the P-F interval gives us more options in deploying the optimal maintenance strategy to meet the business goals.
While improving reliability is a key goal for industries like Power, sustaining management support in the transition towards a Reliability-Centered Maintenance strategy is also contingent upon reducing the total cost of reliability. Often, older assets require additional investments in instrumentation to support continuous monitoring, which tends to run up initial costs of a CBM program. Hence, a pragmatic approach is about balancing or optimizing the total cost across the three maintenance strategies (predictive, preventive, reactive) throughout the reliability journey, as shown below:
Implementing this strategy is a matter of understanding where the gaps are in current maintenance processes, and subsequently, how much to invest in closing these gaps. The November 8th webinar on Asset Reliability Best Practices (Part 1) introduced the process framework (shown below) for deploying CBM in the Power industry. In our next webinar, we delve into the sub-process of “Monitoring System and Component Health”, which is perhaps the most important capability gap to be addressed.
This webinar will explain how the predictive capabilities of a CBM program typically evolves along a 4-stage maturity model. To learn more about this maturity model, along with industry examples, we encourage you to watch this informative session. Watch the on-demand webinar now!
Sree Hameed is currently the Global Marketing Manager for Food, Beverage & Consumer Goods industry at AVEVA. In his 25-year career, he has helped companies adopt a variety of transformational technologies in the areas of production automation, manufacturing operations, supply chain management, product lifecycle management, and operational risk management. Sree also serves as an advisor to the Center for Intelligent Supply Networks at the University of Texas at Dallas.