Predictive and prescriptive analytics – using AI and ML – are transforming asset management. A key aspect of APM 4.0, these technologies are alerting businesses to faults before they occur and presenting maintenance teams with actions that optimize asset performance
The global asset performance management (APM) market is set to grow from US$2.5bn in 2021 to US$4bn by 2026 as industry 4.0 brings new technologies and a transformative approach to industrial productivity.
APM is evolving along with industry, and APM 4.0 is a step change in the way a company conducts maintenance. Using cyber-physical systems to fundamentally change the way a business works, it enables proactive asset performance management through predictive alerts and prescriptive analytics that make the most of artificial intelligence (AI), machine learning (ML) and big data analytics technologies.
Digital transformation of APM
Traditionally APM focused on reliability engineering methods, but APM 4.0 integrates information technology (IT) with operational technology (OT) and connects the asset to the person in the different stages of the asset lifecycle through various layers of technology.
It digitally transforms APM from an asset-orientated approach to a system that holistically connects engineering, operations and performance, creating a single integrated digital thread across the whole asset lifecycle, and laying the groundwork for predictive alerts and prescriptive analytics.
Companies will be able to implement strategies to avoid unplanned downtime while also deciding what preventative or corrective strategy is best for less vital machinery. This will lower costs, reduce unplanned downtime, and optimize labor and equipment usage.
Powerful predictive indicators and alerts
An essential part of APM 4.0 is data-driven decision making which creates performance indicators that are truly leading in that they can adjust and improve performance in real time, and in certain situations prevent a fault from ever occurring.
This is because a variety of sensors and mobile devices provide decision makers with real-time data on the condition, performance, and safety of their assets, which enables more precise decisions.
In stark contrast to the widely used, and typically lagging, indicators that report failures only after they occur, AI and ML use sensor data to accurately predict – by more than 95% – performance degradation and component failure before it happens.
This information is used to set alerts with specific, predefined prescriptive actions that enable maintenance engineers to prevent malfunctions and minimize potential damage.
Prescriptive analytics and actions
As predictive analytics has advanced, we’ve been able to see further into the future, but it’s this use of prescriptive analytics that allows us to maximize the benefits of APM 4.0. This is because in addition to telling you what is likely to happen, these solutions also analyze the best response using big data analytics and ML.
Each triggered alert is linked to prescriptive actions that consist of four attributes: criticality, urgency, action and spare part management, and provide guidance as to what actions should be taken to ensure asset reliability. This rule-based logic is also used to help optimize maintenance and performance thanks to the access to, and analysis of, real-time data.
APM 4.0 provides tangible business benefits
We’ve seen businesses achieve a 25% reduction in unplanned downtime, a 20% increase in asset availability and up to 30% improvements in asset utilization through the use of APM 4.0 solutions.
One case in point is US-based Duke Energy, which was able to avoid catastrophic failures through the use of APM 4.0 that would have caused over US$10m in damages. In another example, Southern Company – one of the US’ largest utilities – implemented a centralized monitoring center to look after its coal, gas and nuclear power generation assets. It deployed more than 10,000 predictive models to monitor its critical equipment and just one single early warning catch of a hairline fracture in a turbine blade was estimated to save the organization US$7.5m.
Ascend Performance Materials also exemplifies a company that gained real business value for APM 4.0. Its goal was to transform its 1950s-era plant into a modern manufacturing facility capable of leveraging industrial data to help prevent shutdowns.
Using this technology, it was able to eliminate manual input of data and visualize the overall manufacturing process across teams, improving communication and knowledge sharing and saving over US$2m in potential plant closures.
Over in the petrochemicals sector, Thailand’s SCG Chemicals used an APM 4.0 solution to prevent unplanned downtime from shutting its value chain. This raised plant reliability from 98% to 100% and delivered significant cost-savings.
Improve the way you manage asset performance
APM 4.0 provide many opportunities to improve the way we manage asset performance, as these examples show. But while some companies are already – or close to – achieving APM 4.0, others may not quite be sure where they should begin their journey.
Technology providers are here to support your APM strategy development, and are keen to highlight the benefits APM 4.0 can bring to your business. This technology is transforming asset management, and can transform your business too.