An object-oriented approach to the concurrent engineering of electronics assemblies
Computers in Industry
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Simplified test cost assumptions lead to unrealistic EMS job bids. By including all important variables affecting test costs, the Test Cost Analysis model closes the gap between predicted production costs and reality.We can think of the rapidly growing electronics manufacturing services (EMS) industry as an electronics manufacturing supermarket. Like their food store counterparts, EMS providers are usually geographically convenient to their major customers, original equipment manufacturers (OEMs). They provide a smorgasbord of goods and services ranging from circuit design through final product assembly and shipping of printed circuit boards-all on a fast-turnaround basis. And, like supermarkets, EMS companies are highly competitive and differentiate themselves primarily on intangibles such as quality of service, turnaround time, and the like.The economic model of the EMS provider is also strikingly similar to the supermarket's: Profitability depends on high volumes shipped at relatively low gross margins. Historically, EMS profit has hovered in the neighborhood of 5% to 10% (source: J.C. Bradford Co., "Electronics Manufacturing Services," presented at Assembly Marketing Research Council of the Institute for Interconnecting and Packaging Electronics Circuits, June 1996). Operating this close to zero or even negative profitability allows an EMS sales department little room for error in pricing and quoting jobs for customers.Most of the EMS job-pricing formula depends on tangible costs such as parts, labor, and overhead consisting of the amortized operating cost of the surface mount technology (SMT) assembly line. In circuit-board manufacturing, however, ill-defined quality criteria and an imprecise understanding of test costs often result in a gap between the job cost estimate and the actual production cost. For example, an EMS provider might base quotations on a rule-of-thumb test cost model that divides tester labor cost by raw board test time. But this formula fails to account for factors such as assembly yield, arriving at the same test cost whether assembly yield is 95% or 0. In reality, total test costs are far higher when manufacturing yields are low than when they are high. In short, this estimation method gambles that nothing will go wrong-never a safe assumption. On the other hand, if test costs are treated too conservatively-that is, if the estimate of test cost is too high-the bid may be uncompetitive.Clearly, estimators need an accurate and consistent method of forecasting board test costs to prevent inaccurate job costing. To that end, the Test Cost Analysis (TCA) model presented here includes more variables than typical EMS test cost models yet is simple and straightforward to use.