Application of Probabilistic Fuzzy Set to Subjective Workload Assessment

This article presents a new approach in workload assessment using fuzzy set theory. Operators’ judgments are aggregated using Probabilistic Fuzzy Set (PFS), a multidimensional workload assessment instrument. Then, to deal with ordering of workload dimensions, information contained in this instrument is analysed using Fuzzy Dominance Relations (FDR) and non-numerical algorithms. The approach is applied to operators of milk-conditioning process, who are asked to give a judgment on four factors: execution speed, muscular effort, attention, and frustration. Com-pared to direct method based on simple average, the present approach allows for maintaining information entropy, and offers a selective analysis of factors (or posts) related to workload.