Decreasing the development time is a significant mean for a company operating in the technical area to lower the development cost. Effort invested into developing a given product can be used to derive following variants of the same product by applying a scaling method. Common scaling methods are created in a means of a geometrical scaling without the option of a flexible change of geometry, while maintaining the concept in the main. Therefore a method is proposed for deriving a knowledge based engineering system which ensures the beforehand mentioned characteristics of the scaling process.

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When using product-service systems as a business model, new product development challenges and opportunities arise. Due to the possibility of customizing the product fleet depending on the user-scenarios, more product variants are possible and often necessary. Therefore, this paper presents an approach for the automated functionality and design optimization for user scenario specific use cases. The approach combines an optimization framework with a functional simulation model and a generative design approach CAD model. This results in a robust and simultaneously flexible design environment.

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In product development, user-scenarios are a way of tailoring requirements to defined customer groups. Furthermore, a product design often involves multiple conflicting objectives that are analyzed within an iterative process. The models typically used for the analysis often do not accurately reflect the real-world representation. This can be alleviated by finding robust product designs. While usually uncertainties due to manufacturing tolerances are investigated, we additionally consider uncertainties in the user-scenario. Therefore, we present a robustness evaluation in a multi-objective numerical optimization in product development. For this, we consider manufacturing tolerances using an adjusted Latin Hypercube Sampling as well as deviations in the user-scenario by means of a Gaussian distribution. In the case study, we present the robust development of a customer specific coffee machine, where we show the robustness evaluation and the impact of the proposed adjustments. The advantage of the presented process is a product design tailored to the customer's requirements under specified uncertainties. In addition, this enables a time benefit in the product development due to the automated analysis used in the optimization.