COUPLING SAMPLING-BASED TOLERANCE-COST OPTIMIZATION AND SELECTIVE ASSEMBLY - AN INTEGRATED APPROACH FOR OPTIMAL TOLERANCE ALLOCATION

Optimization has gained increased attention in product development and is nowadays profitably used to solve complex design problems. In tolerance design, tolerance-cost optimization is a systematic and efficient approach to allocate part tolerance values in a cost-optimal way. The usage of sampling-based tolerance analysis techniques thereby enables the consideration of machine-specific part tolerance distributions as well as individual batch sizes and thus facilitates a concurrent allocation of tolerances and machines. With the aim to further exploit its potential by embedding assembly aspects, this article presents a novel approach combining tolerance-cost optimization and optimal selective assembly. Based on an initial introduction of its general idea, a global optimization problem is defined to simultaneously identify the best combination of tolerance values, machines with their batch sizes and sorting orders of the individual batches. Subsequently, its solution using metaheuristic optimization algorithms and mixed-integer variables is presented. The theoretical findings are finally confirmed by its exemplary application to a use case indicating that it can reveal hidden cost improvement potentials in tolerance design.