The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
Data preparation for data mining
Data preparation for data mining
Data mining solves tough semiconductor manufacturing problems
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining techniques for optimizing inventories for electronic commerce
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining for Design and Manufacturing: Methods and Applications
Data Mining for Design and Manufacturing: Methods and Applications
Quality Engineering Using Robust Design
Quality Engineering Using Robust Design
Neural Networks in Computer Intelligence
Neural Networks in Computer Intelligence
Management for Quality in High Technology Enterprises
Management for Quality in High Technology Enterprises
Methodology of mining massive data sets for improving manufacturing quality/efficiency
Data mining for design and manufacturing
Computers and Industrial Engineering
Applying Data Mining Techniques to Wafer Manufacturing
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Different Kinds of Neural Networks in Control and Monitoring of Hot Rolling Mill
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
Assessing quality performance based on the on-line sensor measurements using neural networks
Computers and Industrial Engineering - 26th International conference on computers and industrial engineering
A survey of data mining and knowledge discovery software tools
ACM SIGKDD Explorations Newsletter
Exploratory Data Mining and Data Cleaning
Exploratory Data Mining and Data Cleaning
Mining Production Data with Neural Network & CART
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
ANN quality diagnostic models for packaging manufacturing: an industrial data mining case study
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
International Journal of Intelligent Systems in Accounting and Finance Management - Intelligent Systems in Operations Management
Online prediction of pulp brightness using fuzzy logic models
Engineering Applications of Artificial Intelligence
The implementation of neural network for semiconductor PECVD process
Expert Systems with Applications: An International Journal
Data mining for yield enhancement in semiconductor manufacturing and an empirical study
Expert Systems with Applications: An International Journal
Review on Application of Data Mining in Product Design and Manufacturing
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04
Data mining approaches for modeling complex electronic circuit design activities
Computers and Industrial Engineering
A classification technique based on radial basis function neural networks
Advances in Engineering Software
Engineering Applications of Artificial Intelligence
A novel manufacturing defect detection method using association rule mining techniques
Expert Systems with Applications: An International Journal
A case-based reasoning system for PCB defect prediction
Expert Systems with Applications: An International Journal
Manufacturing yield improvement by clustering
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Application of data mining for improving yield in wafer fabrication system
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Design quality and robustness with neural networks
IEEE Transactions on Neural Networks
Decision system based on neural networks to optimize the energy efficiency of a petrochemical plant
Expert Systems with Applications: An International Journal
Mining association rules from time series to explain failures in a hot-dip galvanizing steel line
Computers and Industrial Engineering
Mining association rules for the quality improvement of the production process
Expert Systems with Applications: An International Journal
Data mining applied to the cognitive rehabilitation of patients with acquired brain injury
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Exceedance probability estimation for a quality test consisting of multiple measurements
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Smart meter monitoring and data mining techniques for predicting refrigeration system performance
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Many quality improvement (QI) programs including six sigma, design for six sigma, and kaizen require collection and analysis of data to solve quality problems. Due to advances in data collection systems and analysis tools, data mining (DM) has widely been applied for QI in manufacturing. Although a few review papers have recently been published to discuss DM applications in manufacturing, these only cover a small portion of the applications for specific QI problems (quality tasks). In this study, an extensive review covering the literature from 1997 to 2007 and several analyses on selected quality tasks are provided on DM applications in the manufacturing industry. The quality tasks considered are; product/process quality description, predicting quality, classification of quality, and parameter optimisation. The review provides a comprehensive analysis of the literature from various points of view: data handling practices, DM applications for each quality task and for each manufacturing industry, patterns in the use of DM methods, application results, and software used in the applications are analysed. Several summary tables and figures are also provided along with the discussion of the analyses and results. Finally, conclusions and future research directions are presented.