Rethinking Asset Performance Management

Author photo: Peter Reynolds
By Peter Reynolds
ARC Report Abstract

Executive Overview

Owner-operators have long suspected that poor asset performance is hampering their overall business performance. When assets don’t perform up to expectations or have the anticipated reliability, profit margins suffer, and operational excellence becomes elusive. ARC Advisory Group recently surveyed 365 industry practitioners and conducted in-depth interviews with several subject matter experts to gain a better understanding of how industry leaders are implementing asset performance management (APM) initiatives and compare the effectiveness of the different approaches.

The objective of APM is to improve the reliability and availability of physical assets while minimizing risk and operating costs.  APM tools typically include condition monitoring, predictive maintenance, and asset integrity management; and often involve technologies such as asset health monitoring and data collection, visualization, and analytics. While both maintenance and operations groups have a major impact on overall asset performance, historically, the emphasis for APM has been on maintenance-focused enterprise asset management (EAM) and inspections.

New digital technologies can augment many maintenance, reliability, and operational processes to an unprecedented degree.  New commoditized computing resources in the Cloud and at the network edge and artificial intelligence (AI), digital twins, and augmented reality are changing how people work. Approaches such as the Industrial Internet of Things (IIoT) and Industry 4.0 have helped pave the way for digital transformation across a broad swath of industrial sectors.  These new approaches have made their way into APM initiatives or programs to improve maintenance and reliability work processes and overall operational and business performance.

Key findings from this research include:

  • Approximately two-thirds of all industry respondents surveyed either: 1. don’t practice reliability centered maintenance (22 percent), 2. don’t believe that RCM provides ROI or improves reliability (27 percent), or that 3. assets fail randomly despite RCM efforts (18 percent).
  • Operations has as much impact on plant asset performance as the maintenance organization does.
  • Leaders believe the maintenance group has been the custodian of the reliability process but are re-thinking asset performance strategy through digitalization to provide operations groups with better tools and enhance collaboration for APM.
  • Successful asset performance management requires close cooperation between the maintenance, reliability, process engineering, and operations functions in an industrial facility.  Operational performance as well as asset performance must be considered.  New digitalization tools can help make that cooperation easier.

From Digitization to Digitalization

ARC is aware of the confusion many in industry have about the distinction (if any) between the terms “digitization” and “digitalization.”

One way to look at it is that “digitization” involves creating digital versions of previously analog data such as by creating digital maintenance work orders to replace paper-based work orders.  Replacing analog operational technology with digital technology, such as the transition from analog field instrumentation and control systems to digital instrumentation and control systems, would be another example.

Digitization focuses on technology and infrastructure and typically impacts a relatively small number of stakeholders within a company.

Digitalization, in turn, involves making use of digital data and technologies to improve a business or work process. For example, utilizing data from a digital work order to improve maintenance work processes and execution, or using digital twins to improve asset performance. In other words, digitalization utilizes digital technologies and data to improve the way people work, collaborate, and get things done within a plant or across a company.  Digital technologies and the digitalization of data and work processes offer  tremendous potential to help industrial organizations improve the performance of their human and industrial assets.

However, when it comes to asset performance management, many companies today tend to focus their efforts on the technology without considering the full organizational impact.  ARC research shows that only a small percentage of industrial organizations consider themselves ready to digitalize APM.  Many others are not prepared to scale up the pilot programs currently in progress. ARC research also indicates that barriers to organizational accountability, culture, and employee change management impede digitalization. These barriers are reflected in the following APM benchmarking categories discussed in this report:

  • Maintenance tools and approaches
  • Benefits and value of APM
  • Features of an APM system
  • Advance warning systems
  • Maintenance program tools


APM Benchmarking Research Survey and Methodology 

The goal of this research was to gain a better understanding of how today’s industry leaders are implementing asset performance management initiatives and compare the effectiveness of the different approaches.  In March and April 2019, ARC Advisory Group conducted research to analyze and benchmark the current industry state and emerging best practices in APM. This research was designed to answer fundamental questions about digitalization and asset performance, APM tools, and the benefits of different maintenance and reliability strategies.

Armed with a few key questions, ARC launched a global web survey of 365 experts from North America, Europe, Latin America, Middle East, Africa, and Asia-Pacific.  ARC then had in-depth discussions with a handful of subject matter experts (SMEs) across several industries.  The research identified some compelling reasons for industrial organizations to rethink their current asset performance management approaches.

asset performance management APM%20Survey%20Demographics.JPG

ARC analyzed and compared responses from 75 engineering SMEs, 124 maintenance and reliability SMEs, 52 operations leaders, and 72 technical managers or general management. Industries represented include energy, engineering & construction, food & beverage, chemicals, metals & mining, pharmaceutical, and several other industry segments.

Maintenance Tools and Approaches

Calendar-based Maintenance Most Utilized Approach

ARC asked survey respondents to describe their current maintenance practices.  Not surprisingly, the results varied quite a bit.

Calendar-based maintenance is the most utilized maintenance approach.  In the (heavy process) refining and petrochemical industries, maintenance is driven by the turnaround schedule for major equipment. Most of these companies had a five-year turnaround cycle target.  Most assets and related spare equipment are serviced based on the original equipment manufacturer (OEM) service schedule. (Users appear to lack the confidence needed to deviate from the OEM’s recommendations).

Condition-based maintenance (CBM) also scored quite high.  This is consistent with the adoption of common tools and objectives of reliability-centered maintenance (RCM), which provides a process for determining the most effective maintenance strategy. The RCM philosophy employs preventive maintenance (PM), predictive maintenance (PdM), real-time monitoring (RTM), run-to-failure (reactive), and proactive maintenance techniques in an integrated manner to increase the probability that an asset or component will function as designed over its lifecycle with a minimum of maintenance.  For many respondents, the asset-criticality analysis process drives the maintenance strategy and approach. For example, run to failure might be perfectly acceptable for a chiller that runs periodically and is not critical to production.

While the “predictive” category scored surprisingly high, we observed that a variety of strategies and technologies are used with a wide range of abilities to predict failures.  These drive confidence (or lack of confidence) to change a work process.

Increasing Asset Availability Most Valued Benefit of APM

We asked users how their company values the benefits of APM.  While “higher availability” scored highest, care must be taken when interpreting this metric.  We also noted some differences when comparing continuous process industries to discrete and batch processing industries.

Process industry experts consider “availability to plan” to be a much more meaningful target than attempting to achieve higher availability for each asset (the objective of RCM).  Availability to plan is most often used in the process industries because of built-in redundancies.  Stated simply by asset owners, availability to plan means: “It needs to run when it is supposed to run.” 

In the batch and discrete manufacturing industries, overall equipment effectiveness (OEE) is the key metric. OEE identifies the percentage of manufacturing time that is truly productive. For example, an OEE score of 100 percent means you are manufacturing only good parts, as fast as possible, with no down time. In the language of OEE, that means 100 percent quality (only good parts), 100 percent performance (as fast as possible), and 100 percent availability (no stop time).

Current Systems Do Not Provide Adequate Warning

The process industry generally accepts that advance warning of impending breakdowns is the most important functionality of APM systems.  Yet, when we inquired about how much advance notice they typically receive, the response was surprisingly poor.  Fifty-nine percent of users on average receive less than one week notice of impending failure.  While not yet fully mature, new IIoT-enabled remote monitoring and predictive analytics technologies have the potential to significantly reduce the time needed to identify and alert the appropriate personnel about impending failures.  

In leading plants, systems generate these warnings so that - depending on the work process - operators can first make the necessary adjustments to the process, maintenance can then (if needed) make the necessary asset repairs/replacement, or – if the best choice financially – the asset is simply left to fail.

Many consider a maintenance work order to be an appropriate mechanism to inform other departments.  Leaders are moving toward digitalization and improving decision making by taking action in a time frame that can make a difference. Unfortunately, many believe that creating a work order within enterprise asset management systems (EAM) constitutes adequate notification, which is not always the case.

Maintenance Program Tools and Operations

Root cause analysis (RCA), the most common maintenance program tool cited, is an essential component of reliability programs.  Sixty-two percent of survey participants use condition-based monitoring (CBM) and leaders are looking to new tools, Industrial IoT, Industry 4.0, and data science to understand the problem better. However, many do not appear to be using the right techniques to determine failures or considering the potential effectiveness of current technology.  According to one oil industry executive, “We use condition based-monitoring, but I am not sure this is proactive or provides ample early detection. We have tools that tell us the damage and degradation, however; we can only observe the effect, and not the ability to predict the failure. Newer tools and software have a much better analytical presence.”

Less than half of the respondents use operator-driven reliability (ODR).  Many believe the low adoption of ODR has been because these programs have been subjugated by reliability engineering.  ODR is seen as an extension of RCM practices into the operator work process, leaving operators without a clear view of its purpose.  Many believe this approach has its limitations.  These have impacted industry adoption.  Some expressed concern that companies have not been using the right tools to improve asset performance. Many tools have been handed down or thrown at the problem without regard to how to make it better or understanding how ODR can improve the situation.  ODR’s limited adoption reflects the conflict of opinion over which function in the organization has the biggest impact on asset performance.

Survey data suggests that operations have as much impact on asset performance as maintenance does. Some leaders further assert that the process engineers will play a greater role with the accelerated adoption of emerging advanced tools.  A good APM program toolset should provide a clear understanding of the data patterns combining process and asset and assign these to the role with the accountability and the extensive knowledge of the process.

Most analytical software tools help asset experts better understand the asset-related problem.  But these solutions don’t address the operator work process and how this can be improved in a meaningful way.

Table of Contents

  • Executive Overview
  • From Digitization to Digitalization
  • APM Benchmarking Research Survey and Methodology
  • Maintenance Tools and Approaches
  • How Effective Is Reliability-centered Maintenance?
  • Key Finding:  The Process Impact Must Be Understood
  • Case Study:  Digitalization Helps Saras Refinery Improve Asset Performance
  • Recommendations


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