What Is Asset Performance Management?

Asset Performance Management (APM) is an asset management methodology used by asset intensive industries to maximize asset reliability, availability, and utilization of physical assets. According to Gartner, APM uses a combination of data capture, integration, visualization, and analytics to manage asset reliability. Overall, APM is applicable throughout the asset lifecycle, including investment analysis, design, construction, startup, operations, life extension, and decommissioning. Through each of those asset stages, APM is the cross section of process, people, and technology to ensure the asset is properly managed from an investment perspective.

Regarding technology, APM employs a variety of different software packages, ranging from collecting the right data, to organizing or warehousing that data, to modeling and reporting that data. With the improvement of cloud data storage and computational capacity, software has new abilities which enable owner/operators to do things like conduct more advanced simulations or be notified of failure through multivariate machine learning models.

Case Study Highlight

North American Specialty Chemical Facility Leverages GE APM Upgrade to Drive Culture Change

A North American specialty chemicals company was experiencing a substantial number of failures at one of its largest facilities. The site’s inspection program was predominantly time-based with minimal optimization efforts. This site incurred multiple unplanned unit and plant downtime events, which drove up operational costs and gained attention at the corporate management level. The attention triggered an effort to move from a reactive culture to proactive and shift from time-based programs to condition-based and, ultimately, risk-based. The customer was a long-time user of the GE APM Inspection Data Management Software (IDMS); however, its version of GE APM was an older, highly customized version that would not provide a platform to drive improvement.

Learn how we helped a North American specialty chemical producer improve internal processes and shift site culture by implementing a GE APM Version 4 upgrade.

Why is Asset Performance Management Valuable?

APM’s objectives include maximizing asset reliability, optimizing associated spend and ensuring safety and compliance with regulatory standards. However, while those are lofty and achievable goals, many owner/operators experience challenges from implementing and sustaining successful mechanical integrity programs. In addition to the benefits above, APM can provide:

  • Improved communication between departments and business functions

  • Improved understanding of site risks and strategies to help mitigate them

  • Improved reporting functionality that caters information to specific user groups

Case Study Highlight

Leading Fertilizer Manufacturer Leverages APM Software Migration to Improve MI Program Performance and Meet Compliance

A North American fertilizer manufacturer needed a new IDMS to meet compliance and improve its performance. Pinnacle helped the manufacturer evaluate IDMS options and select Predix APM, a cloud-based version of GE Digital’s APM software. Pinnacle also assisted the manufacturer in upgrading the quality of its data and risk results. The manufacturer was able integrate the new IDMS into its existing business systems and standardize its MI work processes across its sites, improving the visibility of performance data across all levels of the organization, mitigating MI risk, and ensuring compliance across its five facilities.

Learn how we helped a fertilizer manufacturer integrate a new IDMS into its existing business systems to improve MI program performance and meet regulatory compliance.

Asset Performance Management Limitations

When it comes to driving effective APM at an asset intensive facility, there are several challenges that owner/operators face. Specific limitations include:

  • Many APM improvement initiatives occur in parallel, owned by separate champions in the organization, but are drawing on similar data sets.

  • APM plans are typically driven by multiple disparate reliability or risk models and reference multiple risk matrices.

  • Most APM models are conservative due to core assumptions around generic failure frequencies, the calculation of probability for failure, and consequence of failure—particularly around health, safety, and environmental (HSE) risks.

  • Most APM calculations occur on asset-by-asset bases and do not relate to the overall performance of the system, unit, or facility.

  • Many APM models are largely static (do not update when key facility variables change), and they do not help quantify the value of data collection or help with sensitivity analysis of required data for calculations beyond manual iteration of values from the user.

  • In general, APM models cannot be used to optimize an entire system, unit, or facility’s reliability strategy based on availability, cost, and resource constraints.

Observations and Tips for Reliability and Integrity Technologies

Watch the full presentation or download the eBook below.
Watch APM Manager, Steve Flory, discuss common pitfalls themes, including which software packages are available, how they are implemented, and also evergreened.

What Does the Future of Reliability Look Like?

APM has improved significantly in the past several decades, resulting in greater reliability and safety, combined with improved cost management. However, the industry is continuing to see major advancements in data acquisition, warehousing, modeling, and analytics. With these capabilities in mind, we have the opportunity to build off existing APM architecture, to improve reliability further while decreasing total maintenance and inspection spend.

We believe this leap is being made possible through Quantitative Reliability Optimization (QRO). QRO is an approach to reliability modeling which connects every relevant reliability data point at a complex facility to one integrated model, allowing for near real time complex decision making that allows users to do things like:

  • Optimization of all maintenance spend based on short/mid/long term reliability targets.

  • Understand the economic value of every inspection or maintenance activity performed.

  • Understand the economic value of every piece of data that is currently being gathered or possibly gathered in the future.

  • Near real time scenario modeling, including the implications of moving a turnaround, feedstock pricing changes, or various capital projects.

  • Drive effective economic decisions in the event of reliability based operating excursions that may impact equipment reliability.

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