The methodology of knowledge acquisition and modeling for troubleshooting in automotive braking system

Authors:
Janus S. Liang
Affiliations:
Department of Vehicle Engineering, Yung-Ta Institute of Technology and Commerce, 316 Chunshan Road, Linlo, Ping Tung 909, Taiwan
Venue:
Robotics and Computer-Integrated Manufacturing
Year:
2012

Citing 10
Cited 0

Java: network programming and distributed computing

Java: network programming and distributed computing
Professional Java Server Programming J2EE 1.3 Edition

Professional Java Server Programming J2EE 1.3 Edition
Java Network Programming, Third Edition

Java Network Programming, Third Edition
A new methodology for extracting manufacturing features from CAD system

Computers and Industrial Engineering
Personal assistant agents for collaborative design environments

Computers in Industry - Special issue: Collaborative environments for concurrent engineering
The troubleshooting task implementation in automotive chassis using virtual interactive technique and knowledge-based approach

Journal of Network and Computer Applications
A Web-based automotive refrigeration troubleshooting system applying knowledge engineering approach

Computers in Industry
Agent-based collaborative product design engineering: An industrial case study

Computers in Industry
Multi-Agent Systems: Simulation and Applications

Multi-Agent Systems: Simulation and Applications
Intelligent agent based framework for manufacturing systems control

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Quantified Score

Hi-index	0.00

Visualization

Abstract

This study introduces a methodology of knowledge acquisition and modeling for troubleshooting in automotive braking system. It is essential for constructing a knowledge base that can be maintained and shared. A knowledge base should not merely be a set of rules, but a framework of troubleshooting that can be controlled and customized by rules. For the construction of a knowledge base, identifying the types of knowledge components to be included is a prerequisite. To identify the knowledge components, this study employs a modeling methodology consisting of three sub-models: instance model, functional model and dynamic model. In addition, mechanisms for maintaining dependency relations of the troubleshooting descriptions at different locations and reasoning using the knowledge at different locations are also developed. The system is implemented using an object-oriented programming language. The proposed methodology is applied to the troubleshooting in automotive braking system.