In product development, manufacturers react to the high complexity of the customers’ requirements with an increased product variety. Different product characteristics and product applications represent influencing factors on product properties. Costly experiments with prototypes are required to verify an appropriate dimensioning of product properties. This thesis offers methods for the verification of a range of products. Therefore, experiments with a small subset of the product variety and machine learning are used to derive the effects of influencing factors on product properties.
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In product development, manufacturers react to the high complexity of the customers’ requirements with an increased product variety. Different product characteristics and product applications represent influencing factors on product properties. Costly experiments with prototypes are required to verify an appropriate dimensioning of product properties. This thesis offers methods for the verification of a range of products. Therefore, experiments with a small subset of the product variety and mach...
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