How To Build a Basic Predictive Maintenance Schedule
(Down)time is money for manufacturers. Downtime due to unexpected breakdowns can quickly cripple production, leading to lost revenue and frustrated customers. That’s why predictive maintenance (PdM) is the gold standard in modern manufacturing maintenance approaches.
PdM goes beyond traditional preventive maintenance schedules by leveraging data and analytics to predict equipment failures before they occur. This allows you to schedule maintenance activities only when necessary, maximizing equipment lifespan, minimizing downtime, and reducing overall maintenance costs. But how do you translate the power of PdM into a practical and actionable schedule? Let’s find out.
Leverage manufacturer recommendations and industry standards
A solid foundation for your PdM schedule starts with established knowledge. Equipment manuals typically outline recommended maintenance tasks and frequencies for your specific equipment. These benchmarks are based on equipment runtime specifications, and they offer reliable guidance for understanding standard maintenance intervals.
Industry best practices can offer valuable insights into common failure modes and recommended maintenance strategies. Use this information as a starting point for your schedule.
Integrating PdM data and setting predictive intervals
The true power of PdM lies in its ability to move beyond static time-based schedules. By implementing PdM techniques like vibration analysis, oil analysis, and thermal imaging, you gain real-time insights into the health of your equipment.
This data allows you to identify subtle changes in performance that might indicate an impending failure. Through trend analysis and anomaly detection, you can then predict when maintenance is actually needed, optimizing your schedule and avoiding unnecessary interventions.
It’s worth noting that the industrial Internet of Things (IIoT) is an invaluable resource in creating a PdM program. The ability to network sensors to trigger alerts is the ultimate form of PdM automation.
Schedule development and considerations
With a clear understanding of both manufacturer recommendations and your PdM data, it’s time to translate this information into a workable schedule. A user-friendly, adaptable scheduling tool becomes crucial. Consider implementing a computerized maintenance management system (CMMS) to streamline the process. A CMMS allows you to create, track, and manage your maintenance tasks, ensuring nothing gets overlooked.
When developing your schedule, consider several factors:
- Labor availability and skill sets: Ensure your maintenance team has the capacity and expertise to handle the necessary tasks.
- Lead times for parts and materials: Factor in lead times for any replacement parts or materials needed for maintenance activities to avoid delays.
- Minimizing production disruptions: Strategically schedule maintenance during downtime or slower production periods to minimize disruption to your workflow.
Keep in mind that, by nature, you’re not scheduling the actual services within a PdM schedule. Rather, you’re establishing a matrix for allocating time, expertise, and resources to be available for impending services. The ultimate goal of a PdM schedule is to anticipate equipment needs and meet them accordingly.
Flexible schedules yield reliable outcomes
Creating a successful predictive maintenance schedule requires a blend of established practices and cutting-edge data analysis. By leveraging manufacturer recommendations, industry standards, and the power of PdM data, you can develop a proactive and adaptable schedule to optimize equipment performance, minimize downtime, and keep your manufacturing operation running smoothly.
Remember, a well-defined PdM schedule is an investment in the long-term health and productivity of your equipment. Done right, it leads to more efficient — and more profitable — manufacturing operations.
