Cognitive automation strategy for reconfigurable and sustainable assembly systems

Purpose - The paper aims to discuss the importance of considering both the physical and cognitive automation when aiming for a flexible or reconfigurable assembly system. This is done in order to handle the increased demand for mass customized production and to maintain or improve the social sustainability within the company. Design/methodology/approach - The methodologies used in this paper are a theoretical review about task allocation and levels of automation and a methodology called DYNAMO++ for the industrial case studies. Findings - The paper provides both theoretical and empirical insights about the importance of considering both the cognitive and physical automation when aiming for a reconfigurable assembly system. Research limitations/implications - The paper will only discuss the cognitive strategy from a social sustainability perspective and not from an economical or environmental angle. Practical implications - The paper presents data from three industrial case studies, mostly in the automotive industry. The result points towards a need for a more structured and quantitative method when choosing automation solutions, furthermore an increased use of cognitive automation solution. Social implications - The results from the case studies show that when the complexity and variety of products increases, a cognitive support for the operators is needed. This strengthens the theory of a need for a cognitive automation strategy within companies. Originality/value - The paper demonstrates an advance in the state of the art in task allocation. The concept model and the DYNAMO++ method can be seen as a step closer towards quantitative measures of task allocation (i.e. changes in both physical and cognitive LoA) and dynamic changes over time.