Document Type
Thesis
Date of Award
9-30-1988
Degree Name
Master of Science in Management Engineering - (M.S.)
Department
Industrial and Management Engineering
First Advisor
Suebsak Nanthavanij
Abstract
Human Factors is one of several essential issues in a discussion of system productivity. Its consideration must be included in the design, development, operation, and maintenance of any human-machine system. In order to maximize the system productivity, humans must perform with their maximum possible efficiency. To achieve this, all human-related activities must be evaluated to determine their possible causes of errors and the consequences. Then, if unable to completely remove, the causes of human errors must be minimized.
This thesis integrates a knowledge of expert system into an analysis of human errors. Its objective is to develop a knowledge-based system to aid practitioners in identifying the causes of human errors. This system includes three major components:
1. Data base
2. Induction system
3. Knowledge-based system
The data base enables a user to input the cause-effect information as symbol structure. Using the statistical computation, the system determines the total weights of each fact in the data base. Then, the induction system performs the induction operation and transfers the data in the data base into rules, and the weights into confidence factors. Finally, the rule base, using its control strategies, determines either all possible causes of a given fact (type of error) or only the most important one.
Recommended Citation
Sung, Bang-Chiang, "Development of a knowledge-based system for human error analysis" (1988). Theses. 3222.
https://digitalcommons.njit.edu/theses/3222
Included in
Business Administration, Management, and Operations Commons, Operations Research, Systems Engineering and Industrial Engineering Commons
