How to generate an optimal maintenance strategy using our platform's optimisation engines. Background and common questions included.
How to optimise planned maintenance strategies using modla (PMO).
There are only three steps to running a basic strategy optimisation with our platform:
Choose the appropriate asset class.
Customize the asset's specific inputs including conditional and environmental considerations. Consequences of failure specific to your business can be imported including monetised risk values.
Select and run a strategy optimisation analysis, then download the report.
Strategy optimisation is fast and simple with our platform
What is planned maintenance (PM) strategy optimisation?
Maintenance strategy optimisation is the process of identifying a collection of maintenance tasks that produce the best value to the business within the constraints of the optimisation. An optimisation is a mathematical process, usually iterative that tries to maximise or minimise a function. In this case, we are trying to maximise the asset life, while minimising the associated cost and risk.
Optimal strategies can either represent an unconstrained or constrained solution. An unconstrained solution represents the best possible strategy period. In contrast, a constrained solution represents the best possible strategy given the constraints of cost, resources and materials while accounting for unknown variables. This is akin to making the best possible decision at the time given the available information.
Maintenance strategy optimisation stems from the idea that not all maintenance tasks are cost-beneficial or add value. Maintenance programs can be value additive as well as a value sink e.g. over or under maintaining assets. To determine an optimal maintenance level, the following high-level points are considered:
The probability of failure of each component and its associated failure modes.
The consequences of those failures.
The costs of inspection, intervening and corrective tasks.
The effect of different maintenance tasks on the asset.
Life extension and reduction mechanisms stemming from tasks and events.
The effectiveness of tasks and their probability of detecting probable failures.
Each of the above items can be broken down into more detail e.g. costs into materials/labour/parts etc. Each task is tested against each interval it can be performed at (based on a planning calendar). The optimum task and interval combination identifies the best balance between cost and the life of the asset. The combination of tasks that achieve this optimum forms the strategy for that particular asset.
Consider the effect of each asset’s unique operational and environmental context.
Consider the variances between assets and what makes them unique.
Do not try to apply a universal maintenance strategy or criticality based strategy. The needs of each asset are dependent on too many factors to lump them into buckets.
Many maintenance strategies are the remnants of Original Equipment Manufacturer (OEM) recommended strategies. Typically, OEM recommended strategies satisfy warranty conditions and thus over maintain assets. These programs are conservative and are not necessarily optimal from a cost-benefit perspective.
An optimum maintenance strategy for an asset can be any combination of sub-strategies and technologies at the mode level. These include run to failure strategies, inspections, condition monitoring, time-based replacements, condition-based inspections and Predictive Maintenance (PdM) technologies etc. Depending on the perceived risk, strategies can vary drastically between assets of the same type and even within the same specific asset.
An optimum maintenance strategy is "optimal for your business and specific asset" so what's optimal for you may not be for others.
Consider both the cost and the resulting life of an asset. Spending a little more to double an asset's life may be worth it.
What measures or attributes does modla consider when optimising a strategy?
Our solvers consider a broad range of inputs which are constantly expanding. Our solvers perform a constrained strategy optimisation which ties directly to the provided inputs. The optimisation considers two distinct lines of information:
Asset related information, including:
Conditional inputs, and
Business-related information, including
Cost inputs (materials, resources, time, monetised risk and benefits, and
Business applicability (plans/tasks, planning calendars, maintenance effectiveness etc.)
With our platform businesses can customise these inputs asset by asset or on bulk.
What are the benefits of an optimal maintenance strategy?
Maintenance departments constitute a significant resource commitment in terms of monetary and material resources as well as personnel.
Optimised maintenance strategies can release resources from non-value-adding tasks.
Maintenance strategy optimisation unlocks additional value by recognising the fact that not all assets are alike, and value lies in their differences.
Optimising can be done over any time frame. It means the process can recommend strategies applicable to the whole life of an asset, or just for the next year or two.
As assets age and their condition deteriorate, the applicability of various maintenance activities change. An optimisation can consider these evolving attributes to recommend tailored strategies to produce optimum value to the business.
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