Active data warehouses: complementing OLAP with analysis rules
Data & Knowledge Engineering - Data warehousing
Comprehensive data warehouse exploration with qualified association-rule mining
Decision Support Systems
Expert Systems with Applications: An International Journal
Development of an intelligent quality management system using fuzzy association rules
Expert Systems with Applications: An International Journal
A hybrid model using genetic algorithm and neural network for classifying garment defects
Expert Systems with Applications: An International Journal
Stitching defect detection and classification using wavelet transform and BP neural network
Expert Systems with Applications: An International Journal
Integrating in-process software defect prediction with association mining to discover defect pattern
Information and Software Technology
Fabric defect detection using morphological filters
Image and Vision Computing
Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses
Information Sciences: an International Journal
Design of a knowledge-based logistics strategy system
Expert Systems with Applications: An International Journal
Integrating data mining with KJ method to classify bridge construction defects
Expert Systems with Applications: An International Journal
Data mining for quality control: Burr detection in the drilling process
Computers and Industrial Engineering
Classifying defect factors in fabric production via DIFACONN-miner: A case study
Expert Systems with Applications: An International Journal
Review: A review of data mining applications for quality improvement in manufacturing industry
Expert Systems with Applications: An International Journal
A novel evolutionary method to search interesting association rules by keywords
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Re-mining item associations: Methodology and a case study in apparel retailing
Decision Support Systems
Development of a soldering quality classifier system using a hybrid data mining approach
Expert Systems with Applications: An International Journal
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
Hybrid genetic algorithm and association rules for mining workflow best practices
Expert Systems with Applications: An International Journal
Discovering business intelligence from online product reviews: A rule-induction framework
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In today's garment industry, garment defects have to be minimized so as to fulfill the expectations of demanding customers who seek products of high quality but low cost. However, without any data mining tools to manage massive data related to quality, it is difficult to investigate the hidden patterns among defects which are important information for improving the quality of garments. This paper presents a hybrid OLAP-association rule mining based quality management system (HQMS) to extract defect patterns in the garment industry. The mined results indicate the relationship between defects which serves as a reference for defect prediction, root cause identification and the formulation of proactive measures for quality improvement. Because real-time access to desirable information is crucial for survival under the severe competition, the system is equipped with Online Analytical Processing (OLAP) features so that manufacturers are able to explore the required data in a timely manner. The integration of OLAP and association rule mining allows data mining to be applied on a multidimensional basis. A pilot run of the HQMS is undertaken in a garment manufacturing company to demonstrate how OLAP and association rule mining are effective in discovering patterns among product defects. The results indicate that the HQMS contributes significantly to the formulation of quality improvement in the industry.