# ISA Interchange

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# How Much Does Rework/Repair Really Cost?

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Production cost is fairly easy to determine, or is it? Determine the number of operations, the cost of labor and the cost of material. But not every unit is perfect. Some units require rework. Some units are scrapped. What is the cost of production fallout? How does that cost affect the bottom line? Let’s look at a simplified scenario to find out.

Scenario: A discrete manufacturing company has a production line with a takt time of 60 seconds to meet delivery requirements (i.e., one product is required off the line every 60 seconds). The actual throughput for the line varies from a product every 55 to 70 seconds, and the line is currently averaging 68 seconds (the latter two values are well above the required takt time). The production line has a first pass yield (FPY) of 75% (i.e., 25% of products require extra work to be usable). It also has a scrap rate of 10% (10% of production cannot be used and is written off), meaning that 90 out of 100 units processed by manufacturing will actually be sold (the 10% scrap is part of the 25% that requires extra work).

Let’s assume there are five production operations in manufacturing the product, a total direct labor cost of \$50, and a total material cost of \$25 (both per unit of production). To make it easy to follow, we will assume each operation consumes approximately 20% of the total cost of labor and material (\$75), making the cost of each operation \$15.

With the original FPY being 75%, the 25% requiring rework/repair (the fallout) have additional costs not counted in the original \$75 per unit price. Assuming a nominal labor cost of \$20/hr for production labor (this rate will vary significantly depending on the industry) and a nominal duration of an additional 3 hours of labor per unit (isolating the defective unit, moving it to and from repair, analyzing and repairing/reworking the unit, and retesting to accept the unit back into production), each unit in the fallout costs an additional \$60 (\$20 x 3 hrs), not including the extra material used to repair/rework the unit. Out of 100 production units processed, 25 units will have an additional \$60 per unit for a total cost of \$1500 (\$60 x 25 units) that now must be shared by the full 100 units for the production run (\$15 per unit). This brings the total cost per unit for the production run from \$75 to \$90.

We also need to factor in the cost of the units that will be scrapped (10% of total units). Out of 100 units that started production, 10 (part of the original fallout of 25%) will be scrapped. However, approximately the same labor costs will apply to these scrapped units as they will still be handled, analyzed, and tested, meaning the units are being scrapped at the \$90 per unit rate for a scrap cost of \$900 for the 10 scrapped units. This cost is now added to the cost of making the 90 units that are sold—an additional \$10 per unit sold (\$900 / 90) for a total cost of \$100 per unit sold (\$90 + \$10). This is a significant increase from the original \$75 per unit and it does not include the cost of material that may have been used during rework/repair operations. In this example, the cost of the rework/repair and the scrap adds just under 34% (\$100 final unit cost / \$75 original unit cost ´ 100 = 1.333% difference or a 33.333% increase) to the cost of units sold. That is only if the repair/rework does not add additional material costs. This additional cost is a direct drain on the company’s profit and is frequently unaccounted for in production costing (hidden in the cost of operations overhead).

The costing is simplified in this example. Rework/repair costs are a lot more complicated because they depend on where in the process the production unit was scrapped, the labor and material consumed by the production unit before it was rejected, and any additional material consumed during the rework/repair process.

Another important aspect of manufacturing operations is the concept that the costs of rework/repair/scrap must be spread out only over the units sold. To recover the cost of poor quality, a company must either lower its profit margin per unit sold or increase its sales price per unit. In this scope of cost analysis, the key performance indicator (KPI) of total cost per 100 units sold can be used. In this KPI, the total fallout would be reflected as “how many units must be started to achieve a production output of 100 units completed” (and sold). The cost of rework/repair (25% in the example) and the cost of the scrapped units (10%) would be included in the cost of producing the 100 units that were actually sold to a customer. In this example, the number of units started would be 110 as only 10 units are scrapped. The additional 15 units (25 units needing rework/repair, less the 10 scrapped units) will still be completed and sold, but as discussed, there will be additional costs.

Looking back at the original analysis, if the cost of production (including repair, rework and scrap) is \$100 per unit, then the cost per 100 can also be stated as \$1,000 per 100 units. In order to monitor significant changes, it may be necessary to change the “per unit” quantity. If a product has a low unit cost, differences may only be recognized in larger “per unit” volumes (“cost per unit,” “cost per 100” or “cost per 1000”). Using this KPI is only of value when compared to the same KPI from additional production runs of the same product over time.

Now you know.

For more detailed discussions on manufacturing analysis, check out Vokey's latest book from ISA:

###### Grant Vokey
Grant Vokey is the principal consultant for Vokey Consulting. With 20 years of diverse manufacturing operations experience and 15 years of integrating information technology (IT) systems into the manufacturing floor, he has developed a strong understanding of how manufacturing companies work and the information needed to operate at world-class levels. Grant’s experience, coupled with continuous training and 10 years as a Certified Operations Manager, has also provided him with an excellent understanding of industry best practices and best-in-class utilization of manufacturing execution systems (MES). Using this knowledge, he has been a subject matter expert for developing industry-leading MES applications/solutions, a program manager for multiple MES programs, and a lead consultant on implementations of MES in various verticals (electronics, industrial equipment, automotive manufacturing, and metal fabrication). Grant is the author of CoE: The Key to Data-Driven Manufacturing and the coauthor of the book MES: An Operations Management Approach, Second Edition.