OptNeTol: Integrated, optimization-based parameter and tolerance design

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The usage of optimization methods for optimal tolerance allocation significantly contributes to the development of least-cost and high-quality products. By formulating suitable optimization problems and solving them with the aid of powerful algorithms, nominal dimensions and tolerance values can be allocated in a way that the cost potential is fully exploited while ensuring that the stringent requirements on robustness, function and aesthetics are fulfilled. In this way, optimization-based methods successively replace purely qualitative approaches, such as simple rules of thumb or well-known theorems like "define tolerances as wide as possible, but as tight as necessary", and thereby create an undisputed competitive advantage.In the preceding funding phase, an important basis for the productive use of tolerance optimization in the industrial environment was established. However, it cannot effectively contribute to answering practice-relevant questions yet. This is mainly due to the deficits of efficient, valid optimization methods, the missing link between the interdisciplinary methods and their lack of focus on practical problems.Therefore, the aim of this research project is to enable the product developer to assign cost-optimal part dimensions and tolerances to practically relevant application cases. This implies that the obstacles to the practical application of the interdisciplinary and at the same time highly specialized methods of nominal dimension and tolerance optimization are largely eliminated. In this context, innovative methods of nominal dimension and tolerance optimization are developed addressing aspects that have not been considered so far, but are absolutely necessary for practical use, such as geometrical tolerances or the handling of missing or uncertain cost information. However, since the optimization problems can only be solved by powerful, sampling-based optimization algorithms, the focus of this research project is also on the development and combination of methods to significantly increase the efficiency in the determination of valid optimization results, such as adaptive sampling and surrogate modelling, including statistical tolerance analysis methods. Finally, the individually developed methods will be linked in a software prototype based on a common, interdisciplinary knowledge base and their applicability will be evaluated in user studies. This ensures that product developers without in-depth knowledge of optimization are supported in defining and solving practical problems as automatically as possible. Thus, currently open research gaps preventing the change from an expert tool for mere tolerance optimization to an integrated, optimization-aided tolerance management are finally closed.