Autor: Thomas Barth

Enterprises of the manufacturing industry have to come to precise decisions about technical and operational aspects of the product particularly in the knowledge-intensive, early phases of the product lifecycle because of increasing pressure concerning cost and competition. This can be supported by efficient reuse of the knowledge captured in product data of historical projects. At the same time, intern IT-systems as well as those of the partners in collaborative environments have to be included. Support of knowledge-intensive processes by similarity analysis in product- and process-data in heterogeneous environments is subject of this article.

Small and medium enterprises (SME) in the automotive supplier industry are facing rising demands concerning cost and quality of the parts or assemblies they are manufacturing for their cus-tomers. Additionally, the “time-to-market” has to be reduced. Applying traditional methods for rationalization is not sufficient to cope with these requirements. Furthermore, flexible, open, and efficient business processes and technologies are required in the early stages of the product life cycle. In this contribution, the potential of solution approaches based on collaborative, virtual product and process design and optimization is introduced. An example of a metal forming process in automotive supplier industry is used to demonstrate the feasibility of the approach.