Human performance in manufacturing tasks: Optimization and assessment of required workload and capabilities

This paper discusses some examples where human performance and/or human error prediction was achieved by using a modified version of the Rasch model (1980), where the probability of a specified outcome is modelled as a logistic function of the difference between the person capacity and item difficulty. The model needs to be modified to take into account an outcome that may not be dichotomous and to take into account the interaction between two macro factors: (a) Task complexity: that summarises all factors contributing to physical and mental workload requirements for execution of a given operative task & (b) Human capability: that considered the skills, training and experience of the people facing the tasks, representing a synthesis of their physical and cognitive abilities to verify whether or not they are matching the task requirements. Task complexity can be evaluated as a mathematical construct considering the compound effects of Mental Workload Demands and Physical Workload Demands associated to an operator task. Similarly, operator capability can be estimated on the basis of the operators' set of cognitive capabilities and physical conditions. The examples chosen for the application of the model were quite different: one is a set of assembly workstation in large computer manufacturing company and the other a set of workstations in the automotive sector. This paper presents and discusses the modelling hypothesis, the interim field data collection, results and possible future direction of the studies.