Package Frame

In this paper, we focus on techniques for incremen-tal constraint-based connguration with discrete and continuous variables. We show how to formalize constraint knowledge using compatibility and activity constraints (Mittal 1990) and how this knowledge is used for reasoning within an intelligent CAD system. Most technical as opposed to spatial constraint connguration systems use algorithms for solving discrete problems (Haselboeck 1994). We claim that connguration is both discrete and continuous in nature and that new methods for handling both constraints in a uniied way must be integrated in connguration systems. Visualization of the globally consistent connguration problem space allows for a systematic exploration of the space in an interactive fashion (Haroud 1995). Knowledge maintenance in connguration systems must be simpliied, because connguration knowledge of todays products evolves over the whole product life cycle. The knowledge representation in deductive rule-based systems as often used in intelligent CAD systems will always be context dependent; maintenance problems resulting from this context dependency are often insur-mountable. We have identiied the context independence of constraint-based knowledge representation as an important feature for facilitating the incremental development and maintenance of large evolving knowledge bases (Faltings & Weigel 1994).