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The application of fuzzy set theory to cognitive workload evaluation of electronic circuit board inspectors
Author(s) -
Ntuen Celestine A.
Publication year - 1999
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/(sici)1520-6564(199922)9:3<291::aid-hfm6>3.0.co;2-s
Subject(s) - workload , fuzzy logic , task (project management) , fuzzy set , set (abstract data type) , computer science , data mining , artificial intelligence , engineering , operations research , reliability engineering , systems engineering , programming language , operating system
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. © 1999 John Wiley & Sons, Inc.