Cognitively automated assembly processes: a simulation based evaluation of performance

Abstract

The numerical control of an experimental assembly cell with two robots – termed a cognitive control unit (CCU) – is able to simulate human information processing at a rule-based level of cognitive control. To enable the CCU to work on a large range of assembly tasks expected of a human operator, the cognitive architecture SOAR is used. The CCU can plan assembly processes autonomously and react to ad-hoc changes in assembly sequences effectively. Extensive simulation studies have shown that cognitive automation based on SOAR is especially suitable for random parts supply, which reduces planning effort in logistics. Conversely, a disproportional increase in processing time was observed for deterministic parts supply, especially for assemblies containing large numbers of identical parts. In this contribution, the effect of phase-shifts in deterministic part supply is investigated for assemblies containing maximal different parts. It can be shown that the concept of cognitive automation is as well suitable for these planning problems.