Prozessinnovation

Jung, Janis; Hubert, Andreas; Doll, Konrad; Kröhn, Michael; Stadler, J.

doi:10.33968/2022.20

Cited by 4 publications

(3 citation statements)

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“…In our preliminary work on digital worker assistance, a gesture recognition method is introduced [8] and integrated into an assistance system with self-learning capabilities [9]. There are also a number of papers investigating the fundamental topic of intelligent assistance systems with a focus on two central issues: firstly, the support of the activity by a cognitive system providing context-sensitive information [10], [11] and secondly, gamification features to maintain concentration and long-term working power [12], [13].…”

Section: Related Workmentioning

confidence: 99%

Towards a Knowledge-Augmented Socio-Technical Assistance System for Product Engineering

Mittel,

Hubert,

Ding

et al. 2023

2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)

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Digital tools for handling the whole product engineering phase are getting more and more important in the context of Industry 4.0 and an increasing product variety. However, especially in small and medium-sized enterprises, a lot of information about product development and production is stored in different documents or isolated data silos. A promising way to arrive at a solution is to model data and knowledge with ontologies and enrich it with context information. This paper presents a concept and a showcase implementation of a companyinternal and personalized assistance system for an end-to-end digital product engineering process. We combine a generic and cost-efficient human assistance solution focusing on social aspects and a company-wide knowledge graph to create a seamless and highly integrated data structure that assists many stakeholders in the product engineering process, from product designers to assembly workers. As a result, more complex products can be handled and the product engineering process can be accelerated.

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Section: Related Workmentioning

confidence: 99%

Towards a Knowledge-Augmented Socio-Technical Assistance System for Product Engineering

Mittel,

Hubert,

Ding

et al. 2023

2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)

View full text Add to dashboard Cite

show abstract

“…With the help of feedback symbols, including a green tick and a red cross, the IAS gives immediate feedback to the worker when an assembly step is performed correctly or incorrectly, respectively. Machine learning allows the IAS to intelligently and automatically learn new assembly sequences for already known and new, varying products (Walczok & Bipp, 2023; Jung et al, 2022). The technical components of this IAS are discussed in detail by Jung et al (2022).…”

Section: Introductionmentioning

confidence: 99%

“…Machine learning allows the IAS to intelligently and automatically learn new assembly sequences for already known and new, varying products (Walczok & Bipp, 2023; Jung et al, 2022). The technical components of this IAS are discussed in detail by Jung et al (2022). With this set of functions, the IAS represents a common IAS in industrial applications (Jetter et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Blessed be intelligent assistance systems at high task rotation? The effect on motivational work design in assembly

Walczok,

Bipp

2023

Hum Ftrs & Erg Mfg Svc

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We aimed to provide causal evidence on the contradictory effects of projection‐based intelligent assistance systems (IASs) for nine motivational work characteristics (MWCs). IASs are increasingly implemented in assembly to counteract rising cognitive workload due to individualized manufacturing processes. However, how IASs enhance or restrict MWCs is largely unknown. We conducted two studies with experimental vignette methodology. In Study 1 (N1 = 169 German employees), we manipulated an assembly workplace (with IAS vs. without IAS) and tested whether findings indicating only positive effects of IASs in the support of a simple assembly process can be transferred to more complex assembly processes. In Study 2 (N2 = 176 German employees), we manipulated again the assembly workplace (with IAS vs. without IAS) and in addition the dynamic of product changes (task rotation after 1 h vs. no task rotation). Analyzing the data with SPSS 27, we found increased feedback from job and information processing and decreased work scheduling, decision‐making, and work methods autonomy when working with IAS. In Study 2, we did not find the main or interaction effects of task rotation on MWCs. Our experimental evidence suggests that working with IASs represents a double‐edged sword regarding MWCs and that the effect of task rotation is limited. Hence, our results provide vital theoretical implications for a much‐needed work design theory that delineates how new technologies shape work design and practical implications for modern assembly.

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Investigating the effect of intelligent assistance systems on motivational work characteristics in assembly

Walczok¹,

Bipp²

2023

J Intell Manuf

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Intelligent assistance systems (IAS) are designed to counteract rising cognitive demands caused by increasingly individualized manufacturing processes in assembly. How IAS affect work characteristics which are crucial for promoting work motivation of employees is yet unclear. Based on the cyber-physical systems transformation framework, the model of routine-biased technological change, and a comprehensive model of work design, we expected in- and decreases in motivational work characteristics (MWC) when working with IAS. Furthermore, we posited a buffering effect of the option of voluntary use on decreasing knowledge characteristics. Applying an online case study with experimental vignette methodology (EVM) allowed us to identify effects of the IAS on MWC before it is widely implemented. 203 German and British blue-collar workers evaluated an assembly workplace according to three experimental conditions (work without IAS, work with IAS, work with voluntary use of IAS). We identified enhanced feedback from the job and information processing in work with IAS in contrast to a traditional assembly workplace but found no restrictions (or elevations) in terms of other task (i.e., autonomy) or knowledge characteristics (i.e., job complexity, problem solving, specialization, skill variety). Thus, our results indicate that the IAS improves some motivational work characteristics of the assembly workplace, although it misses the primary goal of cognitive relief. Our study highlights the need for work design theories that specify the effect of IAS on motivational work characteristics and the potential benefit of IAS in assembly of the future.

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Prozessinnovation

Cited by 4 publications

References 0 publications

Towards a Knowledge-Augmented Socio-Technical Assistance System for Product Engineering

Towards a Knowledge-Augmented Socio-Technical Assistance System for Product Engineering

Blessed be intelligent assistance systems at high task rotation? The effect on motivational work design in assembly

Investigating the effect of intelligent assistance systems on motivational work characteristics in assembly

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