Asset Performance Management: opportunities for improvement

Assuring high quality assets, while having limited workforce is a challenge for many organizations. Luckily, due to promising technology, there are now new opportunities to improve your asset management. With improving asset data quality and the rise of IoT-technologies, we can make a big step to better management of our assets. This article shows the full spectrum of Asset Performance Management and zooms in on the different types of maintenance.

The goal of Asset Performance Management (APM) is to improve the reliability and availability of the assets. This can be achieved by information sharing, integration, monitoring and analytics. There are different topics to reach optimal APM such as, digital twin, asset health, replacement strategies and maintenance. This article focuses on the asset maintenance strategies.

To start, there are different types of asset maintenance. Your most suited strategy depends on the types of failures and the assets you are working with. There are four levels of maturity for asset maintenance that can be distinguished:

1. Reactive Maintenance – Or breakdown maintenance, applies to an organization which focusses on repairs when the asset already failed. The advantages are that you only do the work necessary and minimal amount of planning is needed. On the contrary, you experience unreliability of your assets and relative many failures compared to the market average. Nowadays, this option is only considered when the direct maintenance costs always exceed the risk costs.
2. Preventive maintenance – focusses on the average likelihood of the failing of the assets. This average can be determined based on the lifetime or the usage. This often results in fixed maintenance cycles based on a certain frequency (planned maintenance). This strategy works well when the assets are predictable, and they will rarely experience random failures. It is a generic approach which is based on historical information.
3. Condition-based maintenance – is based on a predefined set of rules determining when maintenance should be applied. Those rules can be based on for example asset characteristics, historical information as well as geographical data in combination with (real-time) sensor data. With the development of IoT and the upcoming 5G, real-time sensor data might bring this condition-based maintenance to a next level. Smart rules can be constructed based on statistical calculations and modelling.
4. Predictive maintenance – uses data and analytics to detect and predict failures before it happens. The advantages of this strategy are an optimized workforce capacity while minimizing the amount of failures and downtime. Its flexibility guarantees quick responses on incidental changes such as weather and usage. With real-time information, changes in schedules occur every moment. This flexibility is a symbol of this modern approach to maintenance.

From the organizational perspective it is often a challenge to find the best suitable level of maintaining your assets while assuring their performance. We find that organizations often struggle to climb to the next level. Various reasons might delay the transition to plan maintenance more efficiently which can be on technological as well as organizational in nature. Technological issues might involve systems that are not integrated or data that is not complete or of low quality. On the other hand, the organization might not be ready, due to contracts with 3rd parties or simply a lack of awareness or acceptance in the organization.

All in all, there are 4 different types of maintenance which have their own best practices. Your organization should look closely to what type best fits and whether your organization is ready for that strategy. New technologies within the IoT-industry and 5G bring new opportunities to better control your assets and improve their performances.

Authors

Stan Braakman

stan.braakman@bearingpoint.com