In part one of this series on the evolution of maintenance, we explored the many ways the Ekho software for operational performance management (OPM) can enhance your preventive maintenance strategy and allow for more informed decision-making through streamlined data collection and automatic tracking of reliability KPIs.
We also discussed how traditional reactive and preventive maintenance methods — although seemingly outdated — are still acceptable to use if the priority and cost of the assets are relatively low or when more advanced technologies are simply not available.
In part two of this series, we will discuss how a preventive maintenance program can be extended to incorporate condition-based maintenance (CBM) and how the right OPM software can support this approach.
CBM is a proactive approach that monitors equipment condition and spots upcoming failures, so maintenance can be scheduled when needed (and not before), reducing unnecessary maintenance and associated costs.
For example, as equipment ages, rotating machinery can develop greater vibration, affecting performance, durability, and safety. Vibration may worsen before a breakdown or hazardous situation emerges. Analyzing vibration can detect problems early, preventing additional issues or harm.
CBM also uses visual checks, spot readings, and automated tests with sensors or specialized tools to detect an issue or a decline in performance — indicated by things like wear, usage, and number of incidents. This information helps maintenance teams plan the best time to perform maintenance — ideally well before a failure occurs or performance takes a hit. And since CBM is non-invasive, measurements can be taken without shutting down the machine or altering the way it operates.
Another advantage of CBM is its extended P-F (Potential Failure) interval when compared to traditional preventive maintenance, as shown in the diagram below. This interval marks the time between the point where a potential failure is detectable (P) and the moment when that failure would likely occur (F).
This means more time to get the right parts for maintenance, reducing the Mean Time To Repair (MTTR). The result? Downtime is minimized, and operations can resume.
Benefits of CBM:
How Does Ekho OPM Software Optimize CBM?
Ekho OPM helps teams leverage CBM, taking performance and availability information and seamlessly integrating these metrics with data on the condition and health of the assets.
Here’s how Ekho OPM software contributes to an effective CBM approach:
Real-Time Monitoring and Alerts: Ekho OPM software continuously monitors equipment and machinery in real-time, collecting data from sensors and other data sources. It then automatically generates alerts and notifications when certain thresholds or conditions are met, enabling maintenance teams to respond faster to potential issues.
Optimized Work Orders: Ekho OPM generates work orders based on real-time conditions, helping ensure that maintenance occurs only when an asset needs it. This reduces unnecessary maintenance tasks and streamlines the overall maintenance process.
Downtime Reduction: By detecting potential issues early and empowering teams with the information they need to approach maintenance more proactively, Ekho OPM helps reduce unplanned downtime. This leads to increased equipment availability and improved Overall Equipment Effectiveness (OEE).
Performance Benchmarking: Ekho OPM provides benchmarking capabilities, allowing manufacturers to compare the performance of different assets or production lines. This helps identify underperforming areas requiring attention — and highlights things that are working well.
Continuous Improvement: Ekho OPM facilitates continuous improvement by collecting data on maintenance activities and their outcomes. This data can be analyzed to refine and enhance the CBM strategy over time, leading to more efficient maintenance practices.
Data Integration and Analytics: Ekho OPM integrates data from various sources, such as sensors, historical maintenance records, and process data. By analyzing this integrated data, the software can identify patterns, trends, and anomalies that might indicate impending equipment degradation or failures. From here, teams can move from a condition-based maintenance strategy toward a predictive maintenance strategy – the subject of our next article in this series.
An ongoing journey toward improved maintenance strategies in industrial manufacturing is vital for sustained success in the marketplace. And finding the right OPM software that allows for customized and continued advancement of these strategies is key. By leveraging the capabilities of Ekho OPM software, a CBM program can effectively reduce unnecessary maintenance and labor, as well as associated costs. As manufacturing processes advance, embracing these innovative tools becomes crucial for ensuring equipment availability, operational efficiency, and a future of sustained success.
Stay tuned for part three of our “Evolution of Maintenance” series where we delve into Predictive Maintenance and describe how you can establish a basic predictive approach by using CBM data and trending, and how you can move to a more advanced strategy leveraging cloud technologies, machine learning, and predictive analytics to further enhance your maintenance strategy.