Connectionist learning procedures
Artificial Intelligence
The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
Quality Engineering Using Robust Design
Quality Engineering Using Robust Design
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Optimization of a multi-response problem in Taguchi's dynamic system
Computers and Industrial Engineering
Design and Analysis of Experiments
Design and Analysis of Experiments
Use of response surface methodology and exponential desirability functions to paper feeder design
WSEAS TRANSACTIONS on SYSTEMS
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Data mining can be viewed as a power tool or technique to help process engineers understand their process know-how. The potential intelligence behind manufacturing processes should hold the information about process improvement or product development. Namely, mining such manufacturing intelligence will have positive contributions to aid the competition capability of enterprise. In this study, we proposed a data mining technique based on artificial neural networks (ANNs) to mine the manufacturing intelligence for achieving the issue of parameter optimization. The rationality and feasibility of the proposed procedure can also be demonstrated well according to the illustrative example in this study.