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This model demonstrates how RISKOptimizer can be used to maximise the efficiency of experimental design. Here we examine a metallic burst cup manufactured by welding a disk onto a ring. The product functions as a seal and a safety device, so it must hold pressure in normal use, and it must separate if the internal pressure exceeds the safety limit. RISKOptimizer is used to find the optimal combination of process settings and design values to minimise scrap and maximise yield. Below is a screen shot of the @RISK/RISKOptimizer model in Microsoft Excel. Click here to download the model. You must have @RISK installed on your computer for the model to function. To download a free trial version of @RISK, click here.
Explanation This model was fabricated to demonstrate the use of the @RISK Monte Carlo simulation capability combined with experimental design. The part under investigation is a metallic burst cup manufactured by welding a disk onto a ring. (See Figure 1) The product functions as a seal and a safety device, so it must hold pressure in normal use, and it must separate if the internal pressure exceeds the safety limit.
The model relates the weld strength to process and design factors, models the variation for each factor, and forecasts the product performance. RISKOptimizer was used to search for the optimal combination of process settings and nominal design values to minimise scrap cost (or maximise yield).
RISKOptimizer and @RISK efficiently found a solution that reduced the annual defect cost to under $1,000.
Using RISKOptimizer and @RISK can save time and resources in a quality improvement and cost reduction effort. The next steps for this problem would be to validate the model and optimised solution through experimentation.
See a working model! Electrical engineers use @RISK to model an electrical circuit and simulate performance. See how @RISK can be used to ensure the quality of experimental design.
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