When implementing engineering changes (EC) in companies many information about ECs and associated processes is stored and forgotten. However, an extraction of information about correlations in past ECs can have advantageous. In the decision phase of ECs, it is very crucial to identify the relevant stakeholders and to know which further parts could be affected by the proposed EC in order to create a good basis for decision. Especially for ECs in complex products, which can affect the whole product lifecycle it is an important and difficult task. This paper presents an approach of how information about past EC processes can be extracted by knowledge discovery in database (KDD) methods in order to support the EC coordinator. The EC coordinator gets recommendations based on past interrelations of EC data and for probably relevant stakeholders and affected parts. Here the data mining technique association rule is applied. The approach was developed while using a real and large database of approximately 53,000 past ECs of a car manufacturer. A preliminary test has been conducted and the feasibility of the approach was proven as well as first positive results.     «

When implementing engineering changes (EC) in companies many information about ECs and associated processes is stored and forgotten. However, an extraction of information about correlations in past ECs can have advantageous. In the decision phase of ECs, it is very crucial to identify the relevant stakeholders and to know which further parts could be affected by the proposed EC in order to create a good basis for decision. Especially for ECs in complex products, which can affect the whole p...     »