Measuring unscheduled downtime

Process Optimization

The Unknown Cost Variables of Unscheduled Downtime

While reducing Unscheduled Downtime is a major reason plants consider industrial analytics solutions, many factories don't have the full picture when it comes to calculating the total cost of these unforeseen events. The range of costs associated with machine breakdowns is a crucial aspect of ROI.

The rationale for an industrial plant to consider an investment in Industrial Analytics is to reduce Unscheduled Downtime. The International Society of Automation estimates that almost every plant loses at least 5% of production due to downtime and that many lose as much as 20%. The cost to the global processing industry alone is estimated at $20 billion.

It is further estimated that over 80% of plants cannot calculate the cost of Unscheduled Downtime. In fact, many plants underestimate costs by between 200% and 300%. The explanation is simple: It is too difficult to track all the cost components.

Activity-Based Costing (ABC) is the accounting term used for the methodology of accurately assigning all the direct and overhead costs incurred in a production process. The problem with ABC is that it is considered impractical and a “nice-to-have.” Activity-level data is often unavailable and it is too time-consuming to generate.

The result is that when Unscheduled Downtime is calculated, only a few of the obvious variables are considered. The purpose of this document is to outline the various cost elements included in Downtime and to provide tools that can be used to approximate the annual Unscheduled Downtime cost.

The Opportunity Cost of Lost Production

Across all industries, the average Unscheduled Downtime for a plant is 17 days per year. This number varies significantly both across and within industries.

In the processing industries, revenue will change based on fluctuations in commodity prices. The estimate below of the average cost for 5 different industries is a starting point, and should be used only for high-level / back-of-the-envelope calculations.

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Even within industries, it is important to recognize variations in the incidence of Unscheduled Downtime. The following data is from a survey conducted by ARC Advisory of senior executives and engineering, operations and maintenance managers in Oil & Gas. As shown below, although the most common production loss was 3-5% per year, there is a significant range from best performers (<1%) to underperformers (>10%).

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What can we learn from this data? Although industry averages for Unscheduled Downtime are interesting from a benchmarking perspective, averages must be modified to reflect the operating conditions at the plant level.


Source: SKF


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