Scenario Building of Replacement Decisions and Strategy
Our approach makes it easy to compare the effects when the life span of an asset or an asset group shortens or expands. When the life span is shortened, asset are replaced earlier and higher investment backlog may show-up.
When we assume the lifespan can be stretched to its maximum, asset replacements are pushed further into the future and a much lower replacement backlog will be shown at the probe date.
We can assign a minimum, economic and maximum life span to each individual asset so we can simulate multiple business scenarios with specific hypotheses for any range of asset groups, even up to an individual asset.
Besides building scenarios for life span modifications, scenarios can be built for different depreciation techniques, for different expected changes in costs such as for energy, personnel, materials, service costs or multiple maintenance or failure scenarios. Business scenarios with any mix of such hypotheses can be developed and applied to the same Asset Register in order to support knowledge-based decision-making.
Scenario Building of Maintenance Decisions and Strategy
Based on costs, budgets, replacement and innovation strategy, but of course also based on the risk and/or value matrix, which is by definition aligned with corporate objectives, the optimal maintenance policy can be determined by carrying out prognosis analyses for all fixed assets in use.
In this example we define a budget of EUR 2 million for 10 years to come. Asset wills now be replaced based on the calculated priority, and we see that the highest priority assets will be replaced first during the budget period. After the budget period, assets are replaced based on their assumed life span periods.
Other examples of analysis algorithms: