Analysing Engineering Knowledge in CAD-models and Spread Sheets using Graph Theory and Filtering

As the era of Knowledge Based Engineering (KBE) and design automation has evolved a big effort has been put to automate CAD-models to quick and accurately respond to changes of customer specifications. The automated knowledge in these KBE-systems is represented as sets of rules, sets that are continuously growing. Parallel to KBE-systems knowledge is also automated in spread sheets (were the cells can be viewed as rules in a KBE system).These spread sheets also tend to grow in number and complexity. The vision of reusing corporate knowledge through automating it in computer systems are now threaten by the fact that the complexity makes it hard to grasp and manage what was automated. Complexity management and graph theory are scientific fields addressing these types of problems. This paper describes how engineering knowledge stored in CAD-models and spread sheets can be analysed through the application of graph theory, visualization and filtering. Information models of CAD-models and spread sheets are developed and applied to a real industrial case to generate and analyse the content