Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective

Wang, Baicun; Zheng, Pai; Yin, Yue; Shih, Albert J.; Wang, Lihui

doi:10.1016/j.jmsy.2022.05.005

Cited by 159 publications

(53 citation statements)

References 146 publications

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“…According to the grid division in the experimental workshop, coordinate (5,5) is taken as the initial The operating process in performing multiple logistics tasks by AGVs is shown in Figure 10. There are two AGVs executing logistics task separately at the same time with the destinations of auxiliary material station (3,1) and parking station (4,4). Firstly, the logistics control system assigns the execution equipment according to the semantic logistics distribution tasks, after which the intelligent agents are deployed to provide customized path planning scheme for each AGV.…”

Section: A Case Studymentioning

confidence: 99%

“…1 Compared to traditional large-scale repetitive production, agile manufacturing provides a framework to allocate various resources and respond seasonably, 2 requiring a higher level of automation and intelligence in the workshop. 3 Pertinently, the development of artificial intelligence provides more disparate solutions to cater to this trend, which endows manufacturing systems with human-level perception and judgment abilities 4 to adjust frequently according to the progress of manufacturing processes and the change of workshop conditions.…”

Section: Introductionmentioning

confidence: 99%

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A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

Bao

Zheng

Dai

2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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With the increasing demand for customization, the tendency of mechanical manufacturing has gradually shifted to flexible and mixed-line production, which brings new challenges to the existing scheduling pattern. As an indispensable part, logistics is responsible for establishing connections among various production equipment and processes. Meanwhile, the promotion of digital twin theory introduces an application schema for the logistics system. However, there is still a deficiency in the real-time dispatching and path planning of logistics equipment due to the uncontrollability of algorithm efficiency for complex scenes. To fill this gap, a digital twin-driven dynamic path planning approach for multiple automatic guided vehicles (AGVs) is proposed. Firstly, the AGVs are virtualized as the major component of logistics systems, while the ontology expression of logistics tasks is consistently accomplished as well. Secondly, the digital twin-driven application framework of multi-AGV dispatching is established. Moreover, a dynamic path planning method for AGVs relying on deep reinforcement learning is implemented. A segmented path planning method is illustrated considering potential route conflicts, which is regarded as the key contribution of the presented research. At last, a case study is illustrated to show the entire process of multiple vehicle path planning and conflict resolution.

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Section: A Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

Bao

Zheng

Dai

2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…The best approach to CPSs is that humans and machinery/robots work collaboratively in a semi-automated way, thus combining the strength, accuracy, consistency, and speed of machinery with the adaptability, ingenuity, judgment, creativity, and dexterity of human workers. In the literature, there are several terms that have been used to refer to such systems: cyber-human systems [ 38 ], Human-in-the-Loop CPSs (HiLCPS) [ 39 , 40 , 41 ], Human-centered CPSs, Human Cyber-Physical Systems (HCPSs) [ 42 , 43 ], Cyber Physical Human Systems (CPHSs) [ 44 , 45 ], or even the term Cyber-Physical-Social Systems [ 46 , 47 , 48 , 49 ], which considers social networks as part of the different user information sources. In the rest of this article, we will use CPHS to refer to CPSs that leverage people’s capabilities to meet the goal of advanced complex industrial systems by ensuring contextual awareness, higher efficiency, enhanced performance, high interoperability, self-cognition, and human error reduction.…”

Section: Introductionmentioning

confidence: 99%

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

Fraga‐Lamas

Barros

Lopes

et al. 2022

Sensors

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While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.

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“…The field of neural engineering depicts over the fields of computational neuroscience, experimental neuroscience, neurology, electrical engineering and signal processing of living neural tissues to work impactfully within a patient. Whereas, rehabilitation engineering implements the innovative and periodical implementation of scientific knowledge and technology to craft and construct such devices, systems or procedures which can be able to satisfy human requirements of an individual who has disabilities [2]. Rehabilitation engineering is a type of chronological engineering which helps to craft, grow, adapt, examine, implement and provide technological issues which have been confronted by people who have disabilities.…”

Section: Introductionmentioning

confidence: 99%

Neural and Rehabilitation Engineering: Applications, Process, and Role in the Future of Medicine

kumar¹,

Ramachandran²

2022

TBEAH

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The rate of neuro-psychological issues has been increasing day by the day due to increasing rate of social and environmental pollution all around the world. It has been actually escalating the demand for neural and rehabilitation treatment worldwide. Neural and rehabilitation engineering is one of the key inventions of modern science which most significantly enhance the entire diagnosis, communication and treatment process in the neural and rehabilitation process. Hence, the study has been keeping its concerns on developing a superior idea about Neural and rehabilitation engineering. A number of concepts relevant to Neural and rehabilitation engineering has been discussed within the overall study. It also developed understanding on the applications and process involved with Neural and rehabilitation engineering. It helps to evaluate the role of Neural and rehabilitation engineering in future of medical filed. A large number of secondary data and formations has been gathered following inductive approach within the entire process within the study to comes forth with a suitable and effective output results. The study has been found that the application of various technological support through Neural and rehabilitation engineering enhance the treatment success and impact a positive role in upcoming future of medical science. Keyword : Neural, rehabilitation, engineering, medical

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Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective

Cited by 159 publications

References 146 publications

A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

Neural and Rehabilitation Engineering: Applications, Process, and Role in the Future of Medicine

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