Businesses rely on their plant and capital equipment to be in good working order for effective and continuous operations. Since equipment downtime causes lost production and a potential loss in revenue, then business managers will look for strategies that will minimise that downtime. These strategies will often rely to some extent on the availability of spare parts. But which spare parts?
Generally there is a choice of three strategies. First, to provide a full spares inventory to cover any need in the event of equipment failure – the just in case approach. Second, to provide the minimum spares inventory now and buy any shortfall only when the equipment fails – the conservative approach. Third, to provide that list of spares inventory that just matches the demand for spares – the optimum approach.
The just in case strategy is very effective in minimising equipment downtime by ensuring there are no delays in waiting for spares. However, this approach can be very expensive, especially given the high cost of repairable spares. Also, the spares inventory is often highly under-utilised, and may require additional costs for periodic maintenance. For example, ball bearings need to be replaced after a period of elapsed time, and electronic or sensing equipment often needs recalibration. The just in case strategy therefore has a bias which emphasises production and reflects a “production at all costs” philosophy that is common in many business environments.
The conservative approach minimises the cost of spares, but at the risk of increased equipment downtime and lost production. Not many organisations will tolerate lost production and therefore prefer the just in case over the conservative approach, even though it may be significantly more expensive over the life of the plant or capital equipment.
Ideally, we would use an optimum approach for a balanced trade-off between the cost of spares and the cost of lost production from equipment downtime. However, this approach is typically never used. Reasons vary, but the most common seems to be because of the complexity of the optimisation problem in conjunction with the “production at all costs” philosophy which underlies a preference for the just in case approach.
Wouldn’t it be nice then, if there was a tool we could use to help determine the optimum spares solution for our operations? Fortunately, such tools do exist in the form of steady state optimisation tools. These are traditionally based on an algorithm that has its origin dating back to the 1960’s, although with many improvements over that time.
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