Assessment of the potential of gamification in manual assembly

6 Pages Posted: 8 Jun 2023

See all articles by Julia Dvorak

Julia Dvorak

Karlsruhe Institute of Technology

Martin Merforth

Karlsruhe Institute of Technology

Magnus Kandler

wbk-Institute of Production Science, Karlsruhe Institute of Technology

Fabian Clever

Kinemic GmbH

Marvin Carl May

Karlsruhe Institute of Technology

Gisela Lanza

Karlsruhe Institute of Technology

Date Written: June 7, 2023

Abstract

Digitization of production systems in the context of industry 4.0 imposes new challenges on workers in assembly lines. For instance, even though it enables smaller batch sizes and customized products, certain tasks may become more standardized and repetitive, causing workers’ attention and motivation to decline. Assistance systems can provide the necessary support for workers and contribute to overcoming the new challenges. The integration of gamification is considered to be a valuable tool to further increase user encouragement. This paper assesses gamification as a measure to improve workers’ motivation and production key performance indicators (KPI) (e.g., productivity) at the same time. In an empirical study in the protected environment of a learning factory during an assembly step of an electrical engine a wearable device is used to track the number of screwing operations which serves as an input for gamification elements like levels or badges. While examining different settings, the subject’s heart rate variability (HRV) is monitored. After the execution of the experiment, motivation, and stress among other factors of cognitive load are assessed by a questionnaire. The results of the questionnaire are then benchmarked against the HRV measurements

Keywords: Human-Centered I4.0, gamification, production, assistance system

Suggested Citation

Dvorak, Julia and Merforth, Martin and Kandler, Magnus and Clever, Fabian and May, Marvin Carl and Lanza, Gisela, Assessment of the potential of gamification in manual assembly (June 7, 2023). Proceedings of the 13th Conference on Learning Factories (CLF 2023), Available at SSRN: https://ssrn.com/abstract=4471436 or http://dx.doi.org/10.2139/ssrn.4471436

Julia Dvorak (Contact Author)

Karlsruhe Institute of Technology

Martin Merforth

Karlsruhe Institute of Technology ( email )

Magnus Kandler

wbk-Institute of Production Science, Karlsruhe Institute of Technology ( email )

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

Fabian Clever

Kinemic GmbH ( email )

Marvin Carl May

Karlsruhe Institute of Technology ( email )

Germany

Gisela Lanza

Karlsruhe Institute of Technology ( email )

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

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