In the oil and gas, mining and infrastructure sectors as well as many others, making informed decisions about strategic asset optimisation is at the core of keeping the future bright – and lucrative. Pinpointing where assets are in their lifecycle and what needs to be planned for enables businesses to form suitable maintenance strategies, understand the future needs of the market and most critically – be ready for the changes that digital transformation brings.

The goal of strategic asset optimisation is to get the most of assets and processes, and in doing so, improve reliability, safety, productivity and reduce maintenance costs. Understanding the requirements of an asset and where it is in its expected lifecycle is the first step to building an effective plan.

Karsten Guster, managing director of Australian asset management firm Crystalise, said that longevity is a key concern when asset planning: “All decisions need to be tied back to the lifecycle and how long the asset is expected to last. Will you be making the same decisions in two years that you will in 15? Fifteen years is a lot of progress and you will need to adapt to the market.”

“Adjusting to change is all about lifecycle management of an asset. What is important today may not have been important yesterday or may not be important in the future. Training operators, for instance, could become more or less important. We also need to understand which assets are more essential. It’s the same as when we look at athletes training for a new sport, they will focus on different muscles and diets depending on if they are a sprinter or a marathon runner.”

He continues: “Plans change based on the available technology that needs to be integrated into a long-term plan. For instance, we have customers looking at remotely controlled vehicles or talking about going away from diesel to electrical, so that means that their assets are changing”

With an in-depth understanding of its assets, both in terms of its current operating needs and changes expected in the future, businesses can ensure that they have maintenance strategies that suit the operating lifecycle. Identifying asset requirements and critical spares help to streamline maintenance and protect organisations from downtime, taking an important step away from reactive maintenance towards predictive maintenance.

Reliability modelling and analysis is another tool that allows organisations to make informed decisions about maintenance schedules and understand the reliability of assets; ensuring reliability is central to ensuring productivity, safety and reducing the risk of asset failure costs. Effective applications of reliability tools and processes will identify your assets threats and vulnerabilities as well as identifying areas where you could be over maintaining or gold plating unnecessarily.

“A strategic asset optimisation plan is really determining an organisation’s maintenance requirements for a particular asset and how they can achieve the most efficient, effective way of managing these assets,” Guster explains. “We really drive them back to basics to understand how their asset facility was designed and built, the challenges at the time, and adjusting to meet the requirements of today.”

“For some things you might need to maintain yearly, monthly, or every five years and so on. You can assess which items needs to be maintained if you want to extend that facility, but unless you understand the asset, you don’t really know how to optimise towards the end its lifecycle. We use whatever information is valuable from the control operation systems to support decisions into optimising the maintenance.”

Understanding what needs to be done and when is key to protecting investment and keeping stakeholders happy. This also extends to contracting strategies, which determines the level of management, operation and maintenance required at different stages of a process and allocates risk to those best qualified to deal with it in order to ensure that operations run smoothly and safely.

With this strategy in place, businesses can be prepared for “what if” situations and make decisions based on overall lifecycle costs.