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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: 248-370-2242, email: [email protected] 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 Current system inputs Manufacturer reports a problem Product recall issued! Customer reports a problem Current process could be costly! 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