Rejection Analysis of Cast Wheel by CRISP-DM and Machine Learning


The pandemic, global competition, customer demand for high-quality products, a wide variety of products, shortened delivery times, and declining profit margins have all had a huge impact on the manufacturing industry. In response to these needs, various industrial engineering and quality management strategies have been formulated, such as ISO 9000, Enterprise resource planning, Business process reengineering, lean management, etc. A new paradigm in this area of manufacturing strategies is CRISP-DM. The project’s work focuses on improving the quality and productivity of manufacturing company through CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology and address the Rejection analysis, which provides a framework for identifying, quantifying, and eliminating sources of variation during manufacturing and provide planned control measures to reduce wheel waste in the casting wheel production plant, improve and maintain the production performance of the wheel workshop.

Published in:

International Journal of Engineering Science and Computing


S. Vijay Shandilya

Akshay Kulkarni

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