Aghdas Badiee - PhD candidate ofindustrial engineering ofIranian university of science and technology, Tehran, Iran
Hossein Hazrati—Marangaloo - PhD candidate ofindustrial engineering ofIranian university of science and technology, Tehran, Iran
Mehdi Ghazanfari - Professor of industrial engineering of Iranian university of science and technology, Tehran, Iran

Manufacturing of high quality products is of utmost importance to any plant’s survival in today’s highly competitive market. As product and process quality are interrelated, high quality processes may result in high quality products. Achieving a minimal number of nonconformities, in any process, needs to eliminate the variation sources, which may have an impact on the quality of the final products. In this paper an applied knowledge discovery framework is introduced to deal with identifying root causes ofnonconformities. In the proposed framework nonconformities are addressed using two characteristics: importance and frequency. Importance shows how the nonconformity may affect the final product. In addition, frequency indicates how often the nonconformity is detected. These characters are addressed using a modified concentration index. The modified concentration index is meant to help the Decision Maker to implement the proper policy. The applicability and effectiveness of the proposed framework is demonstrated through various simulated studies. The findings indicate that the proposed methodology is applicable to different industries and also can map the manufacturing condition precisely.

Quality; Nonconformity; Concentration Index; Knowledge Discovery