Optimize your profitability with our asset performance management software.

This distinction is crucial for strategic maintenance planning:

• Reliability is the measure of how long an asset can run without failure (best measured by mean time between failure or MTBF). It speaks to the asset’s inherent quality and the effectiveness of your proactive maintenance.
• Availability is the percentage of time the asset is ready and capable of running when it is scheduled to. It accounts for both unplanned downtime (failures) and planned downtime (scheduled preventive maintenance). You can have highly reliable assets that are still unavailable if they’re stuck waiting for a scheduled shutdown.

Risk is a core component of APM. APM systems don’t treat all assets equally; they prioritize them by criticality and the consequence of failure. APM uses asset risk management to identify, rank and create mitigation strategies for potential failures, ensuring maintenance resources are focused on the equipment that poses the biggest threat to safety, production or the environment.

APM focuses on metrics that directly impact operational profit and reliability. The three most common KPIs APM seeks to enhance are:

• Overall equipment effectiveness (OEE): A combined measure of availability, performance, and quality.
• MTBF: Increasing this metric shows your maintenance is successfully preventing failures and extending asset reliability.
• Asset availability: Ensuring assets are ready and capable of running when needed, directly reducing unplanned downtime.

APM software operates on a continuous cycle: collect, analyze, act and optimize.

• Collect: It integrates data from disparate sources like IIoT sensors (vibration, temperature), SCADA systems, historians and the existing CMMS/EAM maintenance logs.
• Analyze: It uses advanced predictive analytics, AI and machine learning to find patterns in the data and calculate an asset’s “health score.”
• Act: Based on the predicted time to failure, the system automatically creates a corrective work order in the CMMS before the asset breaks down.
• Optimize: The system continuously feeds results back into the models. It assesses the outcome of the maintenance action (i.e., did the asset run longer after the repair?) and uses this new historical data to refine predictive algorithms and improve asset strategies, making future maintenance even more precise and cost-effective.

Integrating total cost of ownership (TCO) data with real-time performance metrics gives you the strongest basis for capital planning. TCO includes the original purchase price, installation, energy costs and the entire history of maintenance and repair expenses. When you combine TCO with metrics like MTBF, you can definitively prove:

• Whether the cost of continued maintenance is exceeding the price of replacement
• Which asset models offer the best financial return, informing your future purchasing decisions