Date of Award


Publication Type

Master Thesis

Degree Name



Industrial and Manufacturing Systems Engineering

First Advisor

Taboun, S. M.,


Engineering, System Science.



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


This thesis presents a new methodology for constructing a device's computer model to be used as the knowledge-base component of the model-based diagnostics expert system of the device. It is shown that parameterized functional and behavioural knowledge of a device could be applied to the diagnostics action to pin point the root cause of a fault. Four underlying concepts which are examined and deployed in this thesis to support the proposed methodology are: Parametric and feature based design, object oriented methodology for analysis and design, manufacturing as incorporating useful information into material, and using functional knowledge in diagnosing faults. The intended area of research explored in this project is Applications of Artificial Intelligence in manufacturing. To demonstrate the steps involved in implementing the proposed methodology, a prototype system is presented for diagnosing faults of a hair dryer based on its functional and behavioural parameters.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1997 .R33. Source: Masters Abstracts International, Volume: 37-01, page: 0358. Adviser: S. M. Taboun. Thesis (M.A.Sc.)--University of Windsor (Canada), 1997.