User-friendly, requirement based assistance for production workforce using an asset administration shell design

Assadi, Anwar Al; Fries, Christian; Fechter, Manuel; Maschler, Benjamin; Ewert, Daniel; Schnauffer, Hans-Georg; Zürn, Michael; Reichenbach, Matthias

doi:10.1016/j.procir.2020.02.192

Cited by 12 publications

(4 citation statements)

References 13 publications

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“…The research of Al Assadi et al [36] has created a Human Administration Shell (HAS) that uses smart devices (e.g., smart watches, smartphones) to collect and provide information. This solution distinguished between two main categories: condition monitoring (real-time data such as heart rate, location, and accessing data) and service provider (e.g., personal skills and knowledge).…”

Section: Haas Extension To Manage Cognitive Loadmentioning

confidence: 99%

Extension of HAAS for the Management of Cognitive Load

Eesee,

Jaskó,

Eigner

et al. 2024

IEEE Access

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The rapid advancement of technology related to Industry 4.0 has brought about a paradigm shift in the way we interact with assets across various domains. This progress has led to the emergence of the concept of a Human Digital Twin (HDT), a virtual representation of an individual's cognitive, psychological, and behavioral characteristics. The HDT has demonstrated potential as a strategic tool for enhancing productivity, safety, and collaboration within the framework of Industry 5.0. In response to this challenge, this paper outlines a process for tracking human cognitive load using the galvanic skin response as a physiological marker and proposes a novel method for managing cognitive load based on the extended Human Asset Administration Shell (HAAS). The proposed HAAS framework integrates real-time data streams from wearable sensors, user skills, contextual information, task specifics, and environmental and surrounding conditions to deliver a comprehensive understanding of an individual's cognitive state, physical wellness, and skill set. Through the incorporation of skills set, physical, physiological, and psychological variables, and task parameters, the developed HAAS framework enables the identification, management, and development of individual capabilities, thereby facilitating individualized training and knowledge exchange. The applicability of the developed framework is proved by an experiments in the Operator 4.0 laboratory with the detailed HAAS parameters. INDEX TERMS Cognitive load , GSR , Human Asset Administration Shell Implementing I4.0 and incorporating human-in-the-loop control systems showed that the cognitive load on operators in

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Section: Haas Extension To Manage Cognitive Loadmentioning

confidence: 99%

Extension of HAAS for the Management of Cognitive Load

Eesee,

Jaskó,

Eigner

et al. 2024

IEEE Access

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“…Traditional social interaction is the interaction between HDT and HDT through limited means, such as face-to-face communication, and telephone communication. Assadi et al [33] established the lightweight Message Queuing Telemetry Transport protocol based on the "JSON" format, modeled the interaction between employers and employees in the factory, and realized a model of intelligently assigning tasks according to their conditions. This model treated social interaction as a separate module that facilitates qualitative analysis and utilization of inter-HDT interactions.…”

Section: Social Interaction Modelingmentioning

confidence: 99%

“…Ariansyah et al [34] built HDT models by collecting human fatigue data to allocate production operations work and decision-making better. Al Assadi et al [33] implemented a personnel management system for the automatic training and placement of workers by modeling employees' behavior and professional behavior. Sharotry et al [1] modeled the behavior of people carrying heavy objects and judged the risk of injury by the degree of muscle fatigue and the standard of carrying movements.…”

Section: Industry Domainmentioning

confidence: 99%

Human Digital Twin: A Survey

Lin

Chen

Ali

et al. 2022

Preprint

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Digital twin has recently attracted growing attention, leading to intensive research and applications. Along with this, a new research area, dubbed as "human digital twin" (HDT), has emerged. Similar to the conception of digital twin, HDT is referred to as the replica of a physical-world human in the digital world. Nevertheless, HDT is much more complicated and delicate compared to digital twins of any physical systems and processes, due to humans' dynamic and evolutionary nature, including physical, behavioral, social, physiological, psychological, cognitive, and biological dimensions. Studies on HDT are limited, and the research is still in its infancy. In this paper, we first examine the inception, development, and application of the digital twin concept, providing a context within which we formally define and characterize HDT based on the similarities and differences between digital twin and HDT. Then we conduct an extensive literature review on HDT research, analyzing underpinning technologies and establishing typical frameworks in which the core HDT functions or components are organized. Built upon the findings from the above work, we propose a generic architecture for the HDT system and describe the core function blocks and corresponding technologies. Following this, we present the state of the art of HDT technologies and applications in the healthcare, industry, and daily life domain. Finally, we discuss various issues related to the development of HDT and point out the trends and challenges of future HDT research and development.

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“…Additional work has been carried out by Lang et al, where the AAS has been used for maintenance procedures [21]. Al Assadi et al presented an AAS for human workers in production, which included worker preferences to improve the human-machine-interface [22]. The AAS has not been used as an enabler for automated EIA.…”

Section: Usage Of Aasmentioning

confidence: 99%

Automated Environmental Impact Assessment (EIA) via Asset Administration Shell

et al. 2021

Self Cite

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Due to growing public awareness and rising requirements of legislation and customers' expectations in the field of sustainability, it is increasingly important for enterprises to assess and subsequently reduce their environmental impact. However, the acquisition of environmental data in enterprises still causes considerable effort, due to the necessary manual acquisition. A unified asset administration shell (AAS) potentially provides higher data transparency and environmental data interoperability along the value chain and, thus a more detailed (real-time capable) accounting of the environmental impact of products and services. Hence, this paper presents an approach for an automated environmental impact assessments (EIA) of products and production sites via AAS. Thereby, a first application of the AAS in the context of automated EIAs was implemented at the ARENA2036 research factory. The AAS automatically collects energy and emission data throughout a production process and thus allows the allocation of actual emissions to product and equipment (environmental wallet). The results reveal a first starting point for automated EIA, facilitating individual EIAs to address increasing product variety.

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User-friendly, requirement based assistance for production workforce using an asset administration shell design

Cited by 12 publications

References 13 publications

Extension of HAAS for the Management of Cognitive Load

Extension of HAAS for the Management of Cognitive Load

Human Digital Twin: A Survey

Automated Environmental Impact Assessment (EIA) via Asset Administration Shell

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