Computer-Aided Design & Applications, 9(2), 2012, 121-131 © 2012 CAD Solutions, LLC, http://www.cadanda.com 121 Decisional Model for KBE Implementation in a Commercial CAD Software Yannick Bodein 12 , Bertrand Rose 2 and Emmanuel Caillaud 2 1 Tata Technologies Limited Europe, yannick.bodein@tatatechnologies.com 2 LGECO lab - University of Strasbourg- INSA, bertrand.rose@unistra.fr , emmanuel.caillaud@unistra.fr ABSTRACT CAD tools are becoming increasingly powerful today. They provide users with more efficiency and improve the overall performance of design activities. CAD software publishers include specific tools that are dedicated to knowledge management in order to achieve this design performance and significant savings. The use of these tools and certain functions is nevertheless context-oriented. A decisional model for the use of knowledgeware has therefore been developed here, and the application of knowledgeware in different industrial cases is discussed. Keywords: knowledge based engineering, knowledgeware, automation, CATIA V5. DOI: 10.3722/cadaps.2012.121-131 1 INTRODUCTION Reductions in costs and lead-time , as well as quality improvements are now a core consideration of most companies. Multiple action levers enable these improvements: capitalization and reuse of knowledge and know-how, corporate rules, standards formalization and rationalization. The ability to force the application of these rules on all stakeholders, along with repetitive design phase automation, allow firms to act early in the design process in order to optimize innovation capacities. These improvements become real assets for a company as soon as they are deployed with tools and methodologies allowing for a quick Return On Investment (ROI). Some significant gains can therefore be made through:  The optimization of the design process (to have as few customization tasks as possible);  Improved flexibility in order to design more complex products faster,  Collaborative work, with stakeholders with different skills;  Product life-cycle management. In order to make these improvements, the company has to set up an environment in which innovation is promoted and the low value-added tasks automated. This is typically the case in the automotive industry, where the pressure for cost and lead-time reduction is even heavier than in other sectors. We therefore focused our research on this domain. This environment is characterized by 3 performance drivers:  Capitalization and reuse of existing knowledge,  Standardization of functions and components through the company (methodology),  Capitalization and deployment of the company’s standards (training and methodology).