A Survey on Human Machine Interaction in Industry 4.0

Müller, Sebastian; Krupitzer, Christian; Züfle, Marwin; Edinger, Janick; Lemken, Alexander; Schäfer, Dominik; Kounev, Samuel; Becker, Christian

doi:10.48550/arxiv.2002.01025

Cited by 16 publications

(17 citation statements)

References 68 publications

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“…This implies that physical processes are consistently examined and controlled within the digital domain through a computational process that directly influences the real world manufacturing operations. The feedback received by the physical processes also influences computational procedures in an optimization feedback loop [ 16 ]. Smart factories may consist of several CPPS whose role is not only to automate machine interaction, but to minimize production anomalies, thus maximizing efficiencies in production.…”

Section: Smart Manufacturing Use Cases and Requirementsmentioning

confidence: 99%

Wireless Communications for Smart Manufacturing and Industrial IoT: Existing Technologies, 5G and Beyond

Noor-A-Rahim

John

Firyaguna

et al. 2022

Sensors

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Smart manufacturing is a vision and major driver for change in today’s industry. The goal of smart manufacturing is to optimize manufacturing processes through constantly monitoring, controlling, and adapting processes towards more efficient and personalised manufacturing. This requires and relies on technologies for connected machines incorporating a variety of computation, sensing, actuation, and machine to machine communications modalities. As such, understanding the change towards smart manufacturing requires knowledge of the enabling technologies, their applications in real world scenarios and the communication protocols and their performance to meet application requirements. Particularly, wireless communication is becoming an integral part of modern smart manufacturing and is expected to play an important role in achieving the goals of smart manufacturing. This paper presents an extensive review of wireless communication protocols currently applied in manufacturing environments and provides a comprehensive review of the associated use cases whilst defining their expected impact on the future of smart manufacturing. Based on the review, we point out a number of open challenges and directions for future research in wireless communication technologies for smart manufacturing.

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Section: Smart Manufacturing Use Cases and Requirementsmentioning

confidence: 99%

Wireless Communications for Smart Manufacturing and Industrial IoT: Existing Technologies, 5G and Beyond

Noor-A-Rahim

John

Firyaguna

et al. 2022

Sensors

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“…With the development of highly complex and dynamic human-machine systems, comprising of enhanced connectivity, increased autonomy and automation, as well as intelligence, adaptive mechanisms, are emerging. These enable forming independent (active) machine agents for the application in dynamic and uncertain environments to support and assist human workers (Krupitzer et al 2020), which are, despite the technological enhancement, a significant factor in design of manufacturing systems. Assistance systems aim to compensate human worker's shortcomings in cognitive, physical, or even sensorial capabilities.…”

Section: Human-machine Collaborationmentioning

confidence: 99%

Reciprocal Learning in Human-Machine Collaboration: A Multi-Agent System Framework in Industry 5.0

Steffen¹,

Ansari²,

Schlund³

2022

Digitization of the Work Environment for Sustainable Production

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The increasing skill mismatch in manufacturing workforce is raising demand for training opportunities to cope with advanced manufacturing systems. To maintain production and adjust quickly to technological transformation, innovative work-based learning approaches are emphasized. Intelligent machines are becoming capable of interaction and collaboration with humans. They not only introduce a new type of learnable workforce to manufacturing but may open opportunities to enhance learning of all learners. Symbiotic relationships of humans and machines have wide potential for human-centric manufacturing (aka Industry 5.0). Moreover, connecting smart devices and deploying self-learning solutions is envisioned to increase flexibility of manufacturing, thus changing work division between humans and machines. Where humans and machines collaborate, the term Reciprocal Learning has been coined to describe the process of bidirectional learning. While a definition of Reciprocal Learning exists the boundary conditions of the concept are still ambiguous. In this paper, a framework for Reciprocal Learning in Human-Machine Collaboration for Industry 5.0 is presented to clarify what it is and what it isn’t. The approach is based on a multi-agent system perspective, comprising human and machine agents. Finally, an outlook on future research is presented.

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“…To better understand the current development of HMI in smart manufacturing, this paper proposes two classification methods for the current research in this field. The first method is based on the research of [14], which divides HMI into three toplevel categories: Human, Machine, and Interaction. Humans and machines belong to different categories due to their different nature.…”

Section: State-of-the-art Of Hmi In Smart Manufacturingmentioning

confidence: 99%

Review of Human-Machine Interaction Towards Industry 5.0: Human-Centric Smart Manufacturing

Yang

Liu

et al. 2022

Volume 2: 42nd Computers and Information in Engineering Conference (CIE)

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Human-centric smart manufacturing (HCSM) is one of the essential pillars in Industry 5.0. Hence, human-machine interaction (HMI), as the centre of the research agenda for the advances of smart manufacturing, has also become the focus of Industry 5.0. As Industry 5.0 proposed three core concepts of human-centric, sustainable and resilient, the design orientation of HMI needs to change accordingly. Through understanding the state-of-the-art of HMI research, the technology roadmap of HMI development in the smart manufacturing paradigm can be shaped. In this paper, the focus is to review how HMI has been applied in smart manufacturing and predict future opportunities and challenges when applying HMI to HCSM. In this paper, we provide an HMI framework based on the interaction process and analyse the existing research on HMI across four key aspects: 1) Sensor and Hardware, 2) Data Processing, 3) Transmission Mechanism, and 4) Interaction and Collaboration. We intend to analyse the current development and technologies of each aspect and their possible application in HCSM. Finally, potential challenges and opportunities in future research and applications of HMI are discussed and evaluated, especially considering that the focus of design in HCSM shifts from improving productivity to the well-being of workers and sustainability.

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A Survey on Human Machine Interaction in Industry 4.0

Cited by 16 publications

References 68 publications

Wireless Communications for Smart Manufacturing and Industrial IoT: Existing Technologies, 5G and Beyond

Wireless Communications for Smart Manufacturing and Industrial IoT: Existing Technologies, 5G and Beyond

Reciprocal Learning in Human-Machine Collaboration: A Multi-Agent System Framework in Industry 5.0

Review of Human-Machine Interaction Towards Industry 5.0: Human-Centric Smart Manufacturing

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