A Solution to the Recall Problem using Rough Set Theory Professor Djamel Bouchaffra (Advisor) Tarek Dakhlallah (Ph.D. Student) Computer Science & Engineering 131 Dodge Hall Phone: ,

Mass production recall solutions Recalls are necessary for a number of reasons, today's heavy industries products are incredibly complex with many interacting electronic systems The development cycles are extremely compressed With such a short gestation period, certain interactions or problems can go undetected in the development process of a new vehicle

Current process Manufacturer reports a problem Customer reports a problem Product recall issued! Current process could be costly! Current system inputs

Proposed concept Rough set theory proposes a formal framework for the automated transformation of data into knowledge This method shows that the principles for learning by examples can be formulated in the basis of this theory An important result from the theory is that it simplifies the search for dominating attributes leading to specific properties, or just rules pending in the data Rough Set Theory has shown its fruitfulness in a variety of data mining areas (information retrieval, decision support, machine learning, and knowledge based systems) Concept is proven in may fields like medical data analysis and aircraft pilot performance evaluation An important result from the theory is that it simplifies the search for dominating attributes leading to specific properties, or just rules pending in the data