Learning and performing assembly processes

Oestreich, Hendrik; Wrede, Sebastian; Wrede, Britta

doi:10.1145/3389189.3397977

Cited by 10 publications

(8 citation statements)

References 31 publications

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“…This might contribute new insights for firms' training policies and motivate researchers, companies and training providers to further explore digitalised ways of guided on the-job training in combination with theoretical schooling. Recent studies have underlined the importance of adaptivity of digital assistance system regarding learning types and user state along the learning path (Meier and Vernim, 2021; Oestereich et al , 2020). In line with this, our experimental study provides evidence for group differences regarding the combination of theoretical knowledge and learning via a digital assistance system.…”

Section: Discussionmentioning

confidence: 99%

“…While the participants with paper-based task instructions optimised their work processes after a few cycles, the participants using the assistance systems lacked the flexibility to do so and had a slower production speed at the end of the experiment. The importance of adaptivity in the design of digital assistance systems for efficiently supporting learning processes and work performance was stressed by other studies (Meier and Vernim, 2021;Oestreich et al, 2020).…”

Section: Digital Assistance Systems In Work-related Trainingmentioning

confidence: 99%

“…Because of the advances in information and communication technology and human–computer interaction technology, many scholars and policymakers expect substantial improvements regarding work-related training (Gorecky et al , 2013; Oestreich et al , 2020). Digital assistance systems are one example.…”

Section: Research Context and Objectivesmentioning

confidence: 99%

“…A well-known example of this is navigation systems in cars, which display the optimal route to a destination and directions through a city or country and help in finding the right route even in a completely unknown environment. In a similar way, digital assistance systems in industrial production are intended to instruct and support employees in operating machines, even when they lack prior knowledge (Oestreich et al , 2020). However, when using these systems, workers rely on fragmented advice broken down into small tasks by automated technology instead of applying holistic knowledge.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, we observe a shift in the nature of training, from abstract theoretical learning, usually based on holistic information communicated by trainers, colleagues or supervisors or received from independently compiled information, to practical learning based on the repetition of predefined tasks. Previous research has shown that both types of learning have advantages and disadvantages (Kuhlmann et al , 2018; Falkenberg, 2018; Oestreich et al , 2020; Tang et al , 2004; Warnhoff and de Paiva Lareiro, 2019). However, the role of digital assistance systems in learning is yet to receive much attention.…”

Section: Introductionmentioning

confidence: 99%

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Learning via assistance systems in industrial manufacturing. An experimental study in an Industry 4.0 environment

Wotschack,

Vladova,

de Paiva Lareiro

et al. 2023

JWL

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Purpose The purpose of this paper is to investigate how learning solely via an assistance system influences work performance compared with learning with a combination of an assistance system and additional training. While the training literature has widely emphasised the positive role of on-the-job training, particularly for groups that are often underrepresented in formalised learning situations, organisational studies have stressed the risks that emerge when holistic process knowledge is lacking and how this negatively affects work performance. This study aims at testing these negative effects within an experimental design. Design/methodology/approach This paper uses a laboratory experimental design to investigate how assistance-system-guided learning influences the individuals’ work performance and work satisfaction compared with assistance-system-guided learning combined with theoretical learning of holistic process knowledge. Subjects were divided into two groups and assigned to two different settings. In the first setting, the participants used the assistance systems as an orientation and support tool right at the beginning and learned the production steps exclusively in this way. In the second setting, subjects received an additional 10-min introduction (treatment) at the beginning of the experiment, including detailed information regarding the entire work process. Findings This study provides evidence that learners provided with prior process knowledge achieve a better understanding of the work process leading to higher levels of productivity, quality and work satisfaction. At the same time, the authors found evidence for differences among workers’ ability to process and apply this additional information. Subjects with lower productivity levels faced more difficulties processing and applying additional process information. Research limitations/implications Methodologically, this study goes beyond existing research on assistance systems by using a laboratory experimental design. Though the external validity of this method is limited by the artificial setting, it is a solid way of studying the impact of different usages of digital assistance systems in terms of training. Further research is required, however, including laboratory experiments with larger case numbers, company-level case studies and analyses of survey data, to further confirm the external validity of the findings of this study for the workplace. Practical implications This study provides some first evidence that holistic process knowledge, even in low-skill tasks, has an added value for the production process. This study contributes to firms' training policies by exploring new, digitalised ways of guided on-the-job training and demonstrates possible training benefits for people with lower levels of (initial) abilities and motivation. Social implications This study indicates the advantage for companies and societies to invest in additional skills and training and points at the limitations of assistance systems. This paper also contributes to training policies by exploring new, digitalised ways of guided on-the-job training and demonstrates possible training benefits for people with lower levels of (initial) abilities and motivation. Originality/value This study extends existing research on digital assistance systems by investigating their role in job-related-training. This paper contributes to labour sociology and organisational research by confirming the importance of holistic process knowledge as opposed to a solely task-oriented digital introduction.

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Section: Discussionmentioning

confidence: 99%

Section: Digital Assistance Systems In Work-related Trainingmentioning

confidence: 99%

Section: Research Context and Objectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Learning via assistance systems in industrial manufacturing. An experimental study in an Industry 4.0 environment

Wotschack,

Vladova,

de Paiva Lareiro

et al. 2023

JWL

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Asymptotic Analysis of Intensity of Poisson Flows Assembly

Tsitsiashvili¹,

Moiseev

Voytikov

2021

Information Technologies and Mathematical Modelling. Queueing Theory and Applications

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The paper is devoted to obtaining estimations of the rate of convergence of the intensity of an assembly of Poisson flows to the intensity of a stationary Poisson flow. Analysis of the results shows that this problem should combine analytical and numerical studies. An important role is played by the Central limit theorem for both random variables and stochastic processes which is understood in the sense of C-convergence. Exact asymptotic formulas are derived for intensity of the assembly flow of identical Poisson flows, and estimations of the convergence rate are build for the case of non-identical original flows.

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