Towards increasing operator wellbeing and performance in complex assembly
Doctoral thesis, 2018

This thesis provides insights on complex assembly issues and presents pragmatic models, methods, measurable parameters and prototypes that can be used to support operators in complex assembly. Assembly systems are complex partly because of a high degree of product variety and the strategy of having mass-customised products. Complex assembly causes product quality issues, uncertainties and poor ergonomics. Since stress and psycho-social health are emerging problems, it is important to further investigate how complexity affects operator wellbeing and how this and performance can be increased. The aim of this thesis was to investigate and suggest actions that can increase operator wellbeing and operator performance in complex assembly. This was achieved by first identifying and assessing factors influencing operator wellbeing and performance. Five factors were identified as such: work variance, disturbance handling, job satisfaction, motivation and operator emotion. Empirical studies were carried out to investigate what measurable parameters could be used to assess operator wellbeing and performance. The assessment of physiological data in real-time was identified as relevant. Two prototypes were developed to support the factors that were discovered: the DFIP prototype was used to design work instructions to support operator cognition and the DIG IN prototype was used to support operator emotion. The tests and evaluations of the prototypes showed that operator wellbeing and performance can be supported through these prototypes. Two actions were suggested to increase operator wellbeing and performance in complex assembly: 1) supporting cognition through improved assembly instructions and 2) supporting emotion through physiological measurement and environmental data in real time. If these actions are carried out in collaboration with operators (in regard to implementation and usability for example) and do not disrupt the operator workflow, then complexity can be reduced, performance can be increased and a more satisfying and attractive workplace can be created.

Complex systems

assembly

operator wellbeing

performance

smart wearables

Chalmers Virtual Development Laboratory, Chalmers tvärgata 4.
Opponent: Prof. Anders Arweström Jansson, Department of Information Technology, Uppsala University, Sweden.

Author

Sandra Mattsson

Chalmers, Industrial and Materials Science, Production Systems

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

International Journal of Advanced Robotics and Automation,;Vol. 2(2016)

Journal article

A Relationship Between Operator Performance and Arousal in Assembly

Procedia CIRP,;Vol. 44(2016)p. 32-37

Paper in proceeding

Perceived production complexity – understanding more than parts of a system

International Journal of Production Research,;Vol. 54(2016)p. 6008-6016

Journal article

Mattsson, S., Fast-Berglund Å. & Thorvald, P. Forming a cognitive automation strategy for Operator 4.0 in complex assembly

Because today’s products are customised, there are many variants and many different associated components, which must be handled by operators. This puts heavy demands on the operator, who must stay focused to avoid making errors. Also, operator work is often associated with disturbances such as lack of components or changes in production, making assembly work complex. In turn, complex assembly is linked to bad ergonomics and poor assembly performance. In Sweden and Europe, work-related stress is on the increase and it is expected that future assembly work will be even more complex. It is therefore important to investigate how operators can be supported.

This thesis describes how operator wellbeing can be assessed and what factors are important in complex assembly. The results were based on theory, interviews, workshops and experiments.

Two actions were suggested to increase wellbeing and performance. The first one involves supporting operators by improving work instructions. Operators need instructions that are adapted to how they think while they work. However, current instructions are often text-based. Text-based instructions take a long time to read and may therefore not be used at all. The second action supports operators by assessing physiological data. Examples of physiological data include heart rate and step calculations. These are currently used in commercial wristbands. This was suggested because wellbeing is difficult to measure and because smart wristbands are cheap and robust. It was therefore interesting to test whether they could be used in an industrial environment. A prototype was developed and results revealed opportunities as well as risks associated with wristbands.

If operators are involved in these actions, if work tasks are clearly described and appropriate training given, then complexity in assembly could be reduced. A more attractive workplace can be created if complexity is reduced as described.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Areas of Advance

Production

ISBN

978-91-7597-680-8

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4361

Publisher

Chalmers

Chalmers Virtual Development Laboratory, Chalmers tvärgata 4.

Opponent: Prof. Anders Arweström Jansson, Department of Information Technology, Uppsala University, Sweden.

More information

Latest update

1/25/2018