Finding Trends in Human-Automation Interaction Research in Order to Formulate a Cognitive Automation Strategy for Final Assembly

Abstract

This article presents a literature review within the area of Human-Automation-Interaction in order to find trends and central factors in recent HAI research. These factors will then be used in order to suggest a cognitive automation strategy for final assembly. Trends within final assembly is towards take individual aspects into account, choose an appropriate level of automation and investigate trust and joint-interaction factors. In addition, automation system processes should be made more transparent in order to keep the operator in the decision-loop. environment for operators. Results from case studies shows that at perceived complex workstations, work variance was the main cause of complexity (36 stations at 7 companies, Mattsson, et al. [9]). Work variance was in the study connected to cognitive load e.g. that there are many product variants, many other tasks to perform except for the assembly tasks and that it takes time to learn the station work. The results indicate that how product variants and instructions are presented play an important role in how assembly is perceived by operators. To support operators' in a better the way instructions and information are presented could be improved to support them [10-16]. The aim of this paper is to present a review of the development of Human-Automation Interaction in order to see the trends of interaction between humans and automation and not specifically the technology used. This will be used in order to suggest cognitive automation strategies to support operator 4.0 and to find solutions that could increase operators' performance and satisfaction in a final assembly context. Formulating strategies form cognitive automation is becoming more and more important since the complexity of the work environment increases. Findings from the literature review described in this paper shows that there is a gap within the research of measuring how the operators perceives this complex environment and what factors to measure to capture this. A lot of the research done within HAI is in the environment of control-rooms and air-traffic control, but there is not a lot done within the area of manufacturing and production. Technologies and automation has been in focus the resent years but it is seen that research within interaction and human factors is needed to fully understand the potential of HAI.