COGNITIVE AUTOMATION STRATEGY -FOR RECONFIGURABLE AND SUSTAINABLE ASSEMBLY SYSTEMS
Journal article, 2013

Purpose - The paper aims to discuss the importance to consider both the physical and cognitive automation when aiming for a flexible or reconfigurable assembly system in order to handle the increased demand for mass customized production. Furthermore to maintain or improve the social sustainabilitin within the company. Design/methodology/approach - The methodologies used in this paper is both a theoretical review about task allocation and levels of automation. For the industriacl case studies a methodology called DYNAMO++ is used. 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 perspetctive and not from an economical or environmantel angle. Practical implications - The paper presents data from three industrial case studies, mostly in automotive industry. The result points towards a need for a more structured and quantitative method when choosing automation solutions and towards an increased use of cognitive automation solution. Originality/value - The paper demonstrate 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.

Cognitive automation

reconfigurable systems

Automation

Automation

strategy

Social sustainability

LoA

cognitive

Author

Åsa Fasth

Chalmers, Product and Production Development, Production Systems

Johan Stahre

Chalmers, Product and Production Development, Production Systems

Assembly Automation

0144-5154 (ISSN)

Vol. 33 3 294-303 17092645

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Areas of Advance

Production

DOI

10.1108/AA-12-2013-036

More information

Latest update

4/5/2022 6