Capital-intensive enterprises have traditionally faced a difficult decision: play it safe or maximize profits? Calendar-based and usage-based asset maintenance are expensive and require production to be stopped and even then only catch 20% of maintenance needs. Wouldn’t it be cheaper to just fix equipment when it breaks?
Unfortunately, no. Unplanned downtime from asset failure can cost 15 times as much as asset maintenance performed during planned manufacturing downtime. While redundant critical equipment allows companies to quickly bring production back online, acquiring and keeping duplicates mothballed costs money. Insight into how much capital is needed to keep downtime to a minimum, without running over budget, is a critical piece of contemporary industry.
Asset optimization is the process of finding the best use of assets for a company. Asset optimization seeks to find the balance between efficiency and reliability. For instance, what if instead of running one piece of equipment at 100% capacity and keeping a duplicate in storage, both pieces of equipment ran at 60%? Will that increase or reduce downtime in the long run? Is it worth the headache?
Increasing manufacturing uptime is simple if a company has infinite resources: extensive redundancy and keeping equipment in a narrow operation window are surefire ways to reduce downtime. Unfortunately, this approach is inefficient in terms of capital and any plant practicing such an abundance of caution risks being outmaneuvered by a less cautious competitor.
In the real world, companies have to make a profit. That means taking on the risk of manufacturing downtime. Asset optimization seeks to minimize downtime while maximizing profits by accurately modeling and projecting asset use.
In order to make optimal use of assets, an organization first needs an accurate picture of its assets. Asset management software and asset performance management software track how assets perform over time, providing important information about the most efficient way to use a company’s capital. Accounting for the cost of acquiring the asset in the first place, as well as replacing an asset when it is beyond repair or simply too expensive to maintain, is a helpful first step in understanding the complete picture of an asset’s efficiency.
Asset optimization crosses department lines at most enterprises; how to run a compressor and how much money to set aside for compressors may be decided by different people in different countries. An enterprise needs to be prepared for the amount of coordination required to make efficient use of its resources.
An accurate digital model that can explore different asset configurations enables effective asset optimization. Prescriptive analytics tools are a powerful way to both create these models and to explore hypothetical changes in asset deployment.
A company that has fully embraced asset optimization strategies operates as a much leaner organization. Yet an optimal use of assets in one business environment can become woefully inefficient or problematic when market conditions change. Organizations that aim for asset optimization in their current environment must also consider how and when to adapt should things change.
Human managers and operators may have an instinctive feel for how to make the best use of an asset, but the level of expertise to accurately make such an assessment is high. Furthermore, if different operators have conflicting ideas about how to use an asset, gut senses don’t lend themselves to discussion or compromise. In addition, the best way to use a piece of machinery in one location may not be the most efficient way for a company to make overall use of that equipment.
In order to truly implement asset optimization, companies should invest in a prescriptive analytics tool. Prescriptive analytics uses machine learning and artificial intelligence that has been trained on historical asset performance monitoring data to generate computer models of asset usage.
These models can either be manually tweaked to explore different operating scenarios, or the model can be programmed to find ways of achieving the organizations goals. A prescriptive analytics model instructed to find ways of using assets with lower overhead and higher output may find counterintuitive ways to achieve asset optimization. For instance, it may be more efficient to keep all the machinery running all the time but at a lower rate, or perhaps a company can actually reduce downtime by keeping more equipment idle. A company should be prepared to implement the recommendations of the prescriptive analytics model.
What is asset and facility optimization?
Asset and facility optimization is making the most out of assets or facilities. When an asset is being used optimally, it is providing all of the value possible to an organization. This may mean adjusting usage to reflect market conditions; reducing output when the price for a product is lower may be more optimal than simply producing as much as possible at all times.
What is an asset management plan?
An asset management plan is a complete strategy for an asset that projects how an organization will use a capital investment. It includes the acquisition, use, and liquidation or disposal of an asset.
Predictive Maintenance Takes on Operational Risk