Modern asset performance management (APM) is the corrective version of traditional maintenance practices such as inspection, monitoring, and management of physical processes and assets. Historically, maintenance in the asset-intensive industries has included periodic and reactive actions based on the manual assessment data.

With the advent of Enterprise Asset Management (EAM), reliability-centric condition monitoring established altered strategies of asset management. The scope of APM has been dynamic with the emergence of subsequent industrial revolutions, encompassing various organizational aspects ranging from the process, people, and technology with a focus on optimizing asset performance. 

New Approach to APM with Industry 4.0

According to Gartner, asset performance is transforming from merely a maintenance function to the core operational organizational function, primarily due to the advent of Industry 4.0. As per a report by MarketsandMarkets, the global market for APM is likely to grow from $3.3 billion in 2020 to $6.7 billion by 2025.

APM 4.0 is no longer a stand-alone function but, rather a broad collection of processes and technologies that manage the end-to-end lifecycle of connected assets. APM 4.0 is based on the disruptive technologies that are the core of the Industrial Internet of Things I.e. predictive analytics and artificial intelligence. APM today essentially involves condition monitoring, asset integrity, and predictive maintenance.  

Crucial components of an asset performance management solution

Holistic Asset Overview

The essential element of an asset performance system is combining both; IT data and OT data to get a complete picture of asset condition. This comprehensive data along with Industry 4.0 technologies like artificial intelligence and machine learning can form a complete picture of asset condition. The conclusive insights from real-time data can lead to alarms, events, and predictions which can lead to effective decision-making.

Digital Twins for Asset Monitoring

As per a study, unplanned downtimes cost around $50 billion annually in the global manufacturing industry. Poor asset management is one of the biggest causes of operational glitches and unplanned machine failures. Digital Twins is a digital replica of a physical asset that enables remote monitoring and simulation of the operational scenarios. An operational intelligence tool like Eugenie provides a digital ecosystem of digital twins that can detect any operational deviations that can allow the plants to transition from break-fix maintenance to monitoring based actions, empowered by advanced analytics to ensure equipment reliability. 

Eugenie’s digital twin solution ecosystem has empowered industries like oil and gas, manufacturing in improving the efficiency of the assets by preventing unplanned outages and implementing better maintenance strategies. With Eugenie’s robust predictive analytics applied on the assets, the digital twins can portray real-time depiction of asset health, based on the captured sensor data. 

Asset Integrity

APM practices help companies in ensuring asset integrity by monitoring compliance and risk conditions. Implementing proven processes of risk-based monitoring assists decision-makers in preventing EHS and worker safety incidents. The risk and compliance-based practices formed with the real-time field monitoring enable optimum asset operational intelligence. 

Optimum Asset Maintenance

Preventive and predictive maintenance, both involve certain advantages as well as disadvantages. A comprehensive asset maintenance strategy should involve the optimum balance of various maintenance practices to ensure the overall reliability of the assets. Data-based preemptive insights help in formulating actions in case of scenarios such as degrading asset performance. Eugenie’s root cause analysis capability has tremendously helped many customers in establishing effective asset reliability and availability strategies. 

Advantages of APM 4.0

A detailed understanding of the assets can lead to better maintenance strategies and avoidance of incidents that may impact the bottom line. An early alarm of potential degradation of an asset can enable timely action to avoid unforeseen operational incidents. According to Gartner, asset performance management can contribute to solving a myriad of pain points faced by the industrial organizations such as avoiding environmental, health and safety (EH&S) incidents, reduction of operational and inventory costs, and increasing employee productivity. In addition to the operational benefits, better asset awareness can also contribute to solving issues like data silos, data quality, and data governance. 

APM Adoption and best practices

The biggest challenge in APM adoption is the change in operational workflows involving established reactive maintenance processes. Migration from the time-based practices to data-based workflow usually requires systematic change management involving a gradual shift to a data-driven course. 

For extracting the maximum value of the APM solutions, the following industry best practices are recommended.

• Ensuring good data quality of the EAM systems. Before investing in APM, upgrading of EAMs should be initiated.
• Effective Integration of EAM and other legacy systems
• Availability of sustainable and secure OT data through reliable sensor technology
• Collaborative APM models for accommodating cloud technology

If you wish to know more about APM and how you can manage your industrial assets more efficiently, please visit us at www.eugenie.ai or contact us at support@eugneie.ai