A Solution to the Recall Problem using Rough Set Theory

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Transcript A Solution to the Recall Problem using Rough Set Theory

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