The application of fuzzy set theory to cognitive workload evaluation of electronic circuit board inspectors

This article presents an approach to workload modeling of manufacturing workers using fuzzy set theory. Inspectors of integrated circuit boards in an electronic manufacturing system were observed for 9 months. Two types of inspectors were observed: novice inspectors with an average of 1.8 years and experts with an average of 26.5 years of experience. Data were collected on judgment, perception, and attention tasks. The inspectors were given subjective self-evaluation tests to capture the level of workload experienced in each of the task categories. The data were transformed into fuzzy membership functions and were used to quantify workload metrics and inspectors' performance.