Abstract
In wake of customization and individualization of products, the compendium of designed products produced by each manufacturer is ever-increasing. With such an increase in numbers and variants of products complexity soars. However, with this increase an unprecedented rise in implicit knowledge stored in this historic product data comes hand in hand. This paper aims at reducing the complexity within product design and manufacturing by making this implicit knowledge available to engineers. To that end, a toolchain is introduced to support product data formalization which consists of a feature extractor to map CAD model features to a reference data base and similarity assessment to facilitate comparison, understanding and automatic reference model extension. That approach is validated with a car axle assembly in production planning to automate manufacturing sequence deduction from a product model and the implicit knowledge stored in its predecessors and corresponding manufacturing sequences.
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