The Evolution of Predictive and Prescriptive Analytics

Aug. 14, 2020
How Asset Performance Management 4.0 uses sensor data to maximize profitability.

True digital transformation requires an evolution from an asset-oriented approach to manufacturing to a systems-based approach that holistically connects engineering, operations, and performance—enter Asset Performance Management (APM) 4.0 with predictive alerts and prescriptive analytics.

APM 4.0 creates a single integrated digital thread across the whole asset lifecycle. Two key factors play a pivotal role in the successful operation of this new digital thread. First, there must be connectivity among assets and workers. Second, decisions that are informed by sensors and intelligent data must be able to be executed in real-time. APM 4.0 is focused on delivering critical business results and enable asset excellence by enhancing safety, profitability, and sustainability.

One essential part of APM 4.0 is sensor-based decision making with true lead performance indicators. A variety of sensors and mobile devices provide decision makers with real-time data on the condition, performance, and safety of their assets, enabling more precise decisions. In stark contrast to the widely used and typically lagging indicators that report failures only after they occur, condition monitoring, artificial intelligence, and engineering expert systems use sensor data to predict performance degradations and component failures before they happen.

Industrial equipment necessitates planned shutdowns and scheduled maintenance times for its successful operation. Because of this, the promise of APM 4.0 isn’t to keep assets in a perpetual online state; rather, APM 4.0 empowers you to maximize your return on investment (ROI) by letting you take full advantage of sensor data so you know exactly how each individual asset—from the most critical to the least vital—should be managed and maintained in order to best mitigate risk and capitalize on opportunities.

The complete picture: Analytics and risk management
Predictive and prescriptive analytics that utilize sensor data to make better decisions offer enormous opportunities to improve your asset performance. In order to create a complete APM solution, an asset owner operator (AOO) must complement their predictive and prescriptive analytics with a sound approach to asset risk management, as depicted in the graphic. Furthermore, the AOO needs to assess the asset context and define its criticality based on the impact on its context if it fails.

Traditional APM focuses on reliability engineering methods (e.g., reliability centered maintenance, root cause analysis, failure mode effects and criticality analysis (FMECA), and information technology (IT) such as computerized maintenance management systems, enterprise asset management, enterprise resources planning, and business intelligence). APM 4.0, however, integrates IT with operational technology (OT) and connects the asset to the person in the different stages of the asset lifecycle (engineering, operations, and performance) through several layers of enabling technologies.

APM 4.0 lays the groundwork for predictive analytics and data science and transforms time-series sensor data into powerful predictive indicators. This allows AOOs to avoid asset failures and optimize asset performance.

Shareholders invest in assets because they expect to see a reasonable ROI. The ROI is primarily defined by the operating profit that can be achieved from an asset. However, the ROI is also dependent on the AOO’s license to operate. If the asset’s integrity is challenged and does not comply with safety, quality, or environmental regulations, risks of the asset being shut down by the responsible authorities increase.

APM 4.0 establishes a direct link between the sensor and ROI. It creates meaningful key performance indicators from sensors and enables decision-makers to optimize the performance of the asset. For the first time in history these performance indicators are truly “leading” in that they can change performance before it happens. To date, performance systems have been primarily based on “lagging” indicators (e.g., cost, availability, number of safety incidents). These indicators only report on issues after the fact.

APM 4.0 brings with it the promise of proactive asset management made possible by predictive alerts and prescriptive analytics: lower costs, reduced unplanned downtime, and optimized labor usage and equipment performance. Through predictive alerts and prescriptive analytics, companies will be able to implement preventive asset strategies to avoid unplanned downtime for their most critical assets while also deciding which preventive or corrective asset strategy is the best course of action for their less vital equipment.

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