Social Factory Architecture: Social Networking Services and Production Scenarios Through the Social Internet of Things, Services and People for the Social Operator 4.0

Romero, David; Wuest, Thorsten; Stahre, Johan; Gorecky, Dominic

doi:10.1007/978-3-319-66923-6_31

Cited by 49 publications

(47 citation statements)

References 23 publications

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“…This can be done by using different ICT-tools that are autonomous, easyto-use and use different multimedia principles when collecting information. In cognitive multi-agent systems [16] [17], softbots and co-bots can be used to embody the automation [13], and we believe that "trust" to share tacit knowledge to an ISS increases if the information is feed through "smart cognitive agents" [14] that are adaptable to the operators. Such (agent) intelligence allows the cognitive multi-agent system to know what question to ask and what comments to say in order to trigger the motivation of the operator.…”

Section: Base Concepts: Cooperative Agent-based Systems and Embodmentioning

confidence: 99%

Conceptualizing Embodied Automation to Increase Transfer of Tacit knowledge in the Learning Factory

Fast-Berglund

Thorvald

Billing

et al. 2018

2018 International Conference on Intelligent Systems (IS)

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This paper will discuss how cooperative agent-based systems, deployed with social skills and embodied automation features, can be used to interact with the operators in order to facilitate sharing of tacit knowledge and its later conversion into explicit knowledge. The proposal is to combine social software robots (softbots) with industrial collaborative robots (co-bots) to create a digital apprentice for experienced operators in humanrobot collaboration workstations. This is to address the problem within industry that experienced operators have difficulties in explaining how they perform their tasks and later, how to turn this procedural knowledge (knowhow) into instructions to be shared among other operators. By using social softbots and co-bots, as cooperative agents with embodied automation features, we think we can facilitate the 'externalization' of procedural knowledge in human-robot interaction(s). This enabled by the capabilities of social cooperative agents with embodied automation features of continuously learning by looking over the shoulder of the operators, and documenting and collaborating with them in a non-intrusive way as they perform their daily tasks.

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Section: Base Concepts: Cooperative Agent-based Systems and Embodmentioning

confidence: 99%

Conceptualizing Embodied Automation to Increase Transfer of Tacit knowledge in the Learning Factory

Fast-Berglund

Thorvald

Billing

et al. 2018

2018 International Conference on Intelligent Systems (IS)

Self Cite

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“…Romero et al [1] postulated an Operator 4.0 typology with eight different operator types such as Healthy Operator, Collaborative Operator and Social Operator. In later papers, Romero et al further defined the concepts of Healthy Operator [3] and Social Operator [4]. The visionary papers introduce future concepts but not yet evaluation results.…”

Section: Introductionmentioning

confidence: 99%

“…To improve team performance, organizations must ensure that knowledge is both shared and applied [7]. New technologies can encourage collaboration among workers, support problem-solving and bring together the right people [4]. The Operator 4.0 paradigm shift cannot succeed simply by introducing new technologies to the factory floor, but work processes need to be reshaped in parallel [8].…”

Section: Introductionmentioning

confidence: 99%

“…The aim of the study described in this paper was to evaluate user experience, user acceptance and foreseen impacts of three Operator 4.0 solutions developed in the Factory2Fit project (www.factory2fit.eu): Worker Feedback Dashboard, Participatory Design with a Virtual Factory and Contextual Knowledge Sharing. The solutions can be seen as examples of Operator 4.0 types Healthy Operator, Virtual Operator and Social Operator as defined by Romero et al [1,3,4]. The leading idea of the solutions is that the workers are the best experts of their own work and they should be given effective possibilities to develop their competence, based on their own initiative, and their role should be more active in designing and developing manufacturing processes [8].…”

Section: Introductionmentioning

confidence: 99%

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Empowering and Engaging Solutions for Operator 4.0 – Acceptance and Foreseen Impacts by Factory Workers

Kaasinen

Aromaa

Heikkilä

et al. 2019

IFIP Advances in Information and Communication Technology

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Industry 4.0 factories require smart and skilled operators-Operators 4.0. We evaluated three Operator 4.0 solutions that aim to empower and engage workers, so that workers can understand and develop their own competences and they can take an active role in developing the manufacturing environment. 118 shop stewards from different factories assessed user experience, user acceptance and foreseen impacts of the solutions. The results show that there are high expectations towards the virtual factory-based participatory design solution. Opinions were shared about empowering the worker by feedback about worker well-being and work achievements. The solution was seen interesting and useful but there were doubts regarding privacy. Contextual knowledge sharing was felt important but the workers were a bit skeptical as many previous knowledge sharing attempts had been failed. The results give insight to how the solutions should be further developed and how the solutions should be introduced at factory floor.

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“…Although occupational health has been a popular topic for decades in both academic research and industrial applications, it has rarely had the advantage of real time quantitative measurements, mainly due to the limited capabilities for directly measuring such factors [21,[26][27][28][29][30][31].…”

mentioning

confidence: 99%

Healthy Operator 4.0: A Human Cyber–Physical System Architecture for Smart Workplaces

Sun

Zheng

Gong

et al. 2020

Sensors

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Recent advances in technology have empowered the widespread application of cyber–physical systems in manufacturing and fostered the Industry 4.0 paradigm. In the factories of the future, it is possible that all items, including operators, will be equipped with integrated communication and data processing capabilities. Operators can become part of the smart manufacturing systems, and this fosters a paradigm shift from independent automated and human activities to human–cyber–physical systems (HCPSs). In this context, a Healthy Operator 4.0 (HO4.0) concept was proposed, based on a systemic view of the Industrial Internet of Things (IIoT) and wearable technology. For the implementation of this relatively new concept, we constructed a unified architecture to support the integration of different enabling technologies. We designed an implementation model to facilitate the practical application of this concept in industry. The main enabling technologies of the model are introduced afterward. In addition, a prototype system was developed, and relevant experiments were conducted to demonstrate the feasibility of the proposed system architecture and the implementation framework, as well as some of the derived benefits.

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Social Factory Architecture: Social Networking Services and Production Scenarios Through the Social Internet of Things, Services and People for the Social Operator 4.0

Cited by 49 publications

References 23 publications

Conceptualizing Embodied Automation to Increase Transfer of Tacit knowledge in the Learning Factory

Conceptualizing Embodied Automation to Increase Transfer of Tacit knowledge in the Learning Factory

Empowering and Engaging Solutions for Operator 4.0 – Acceptance and Foreseen Impacts by Factory Workers

Healthy Operator 4.0: A Human Cyber–Physical System Architecture for Smart Workplaces

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