Development of an intelligent quality management system using fuzzy association rules

Authors:
H. C. W. Lau;G. T. S. Ho;K. F. Chu;William Ho;C. K. M. Lee
Affiliations:
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Hong Kong;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Hong Kong;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Hong Kong;Operations and Information Management Group, Aston Business School, Aston University, Birmingham B4 7ET, United Kingdom;Division of Systems and Engineering Management, School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 6
Cited 5

Fuzzy data mining for interesting generalized association rules

Fuzzy Sets and Systems - Theme: Learning and modeling
Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques
PROTEUS: creating distributed maintenance systems through an integration platform

Computers in Industry - Special issue: E-maintenance
Knowledge support for problem-solving in a production process: A hybrid of knowledge discovery and case-based reasoning

Expert Systems with Applications: An International Journal
A novel manufacturing defect detection method using association rule mining techniques

Expert Systems with Applications: An International Journal
Mining association rules with multiple minimum supports using maximum constraints

International Journal of Approximate Reasoning

Fuzzy theory applied in quality management of distributed manufacturing system: A literature review and classification

Engineering Applications of Artificial Intelligence
Mining association rules from time series to explain failures in a hot-dip galvanizing steel line

Computers and Industrial Engineering
A hybrid OLAP-association rule mining based quality management system for extracting defect patterns in the garment industry

Expert Systems with Applications: An International Journal
Using data mining synergies for evaluating criteria at pre-qualification stage of supplier selection

Journal of Intelligent Manufacturing
ENVIRONMENT-BASED DESIGN EBD APPROACH TO DEVELOPING QUALITY MANAGEMENT SYSTEMS: A CASE STUDY

Journal of Integrated Design & Process Science

Quantified Score

Hi-index	12.05

Visualization

Abstract

In order to survive in the increasingly customer-oriented marketplace, continuous quality improvement marks the fastest growing quality organization's success. In recent years, attention has been focused on intelligent systems which have shown great promise in supporting quality control. However, only a small number of the currently used systems are reported to be operating effectively because they are designed to maintain a quality level within the specified process, rather than to focus on cooperation within the production workflow. This paper proposes an intelligent system with a newly designed algorithm and the universal process data exchange standard to overcome the challenges of demanding customers who seek high-quality and low-cost products. The intelligent quality management system is equipped with the ''distributed process mining'' feature to provide all levels of employees with the ability to understand the relationships between processes, especially when any aspect of the process is going to degrade or fail. An example of generalized fuzzy association rules are applied in manufacturing sector to demonstrate how the proposed iterative process mining algorithm finds the relationships between distributed process parameters and the presence of quality problems.