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Abstract: Current design of improved product generations does not exploit use information from previous products systematically. The emerging shift of manufacturing companies from selling products to providing product service systems, the miniaturization of product-embedded sensors, as well as advances in information technology facilitate a product providers access to operation information of current products, which can be used to improve the development and the quality of follower product generations. The paper presents a framework for the acquisition, aggregation and analysis of product use information as well as for the generation and provision of knowledge for the development of improved product generations. The described approach employs knowledge discovery methods like Bayesian Networks and is supported by an IT prototype of a design assistant system. This prototype has been validated in a use case considering the improvement of a rotary spindle for micro machining. [Copyright &y& Elsevier]