Toward Digital Twin for Cyber Physical Production Systems Maintenance: Observation Framework Based on Artificial Intelligence Techniques

Abdoune, Farah; Nouiri, Maroua; Castagna, Pierre; Cardin, Olivier

doi:10.1007/978-3-030-69373-2_8

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…The data about the actual work of the equipment can be used in the analysis of emergencies for predictive analytics and machine learning [37]. Moreover, the tracking of physical objects can enable control of the key parameters of both individual equipment and the entire production system work [1].…”

Section: Resultsmentioning

confidence: 99%

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Development of an industrial cyber-physical platform for small series production using digital twins

Yablochnikov

Chukichev

Timofeeva

et al. 2021

Phil. Trans. R. Soc. A.

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The article describes an industrial cyber-physical platform for small series production using digital twins under development at ITMO University (Saint Petersburg, Russia). The platform is based on the following approaches: group technology, adaptive and selective assembling, and digital twin of production systems and processes. The article presents a mechanism for constructing a unified manufacturing process, and results of an integrated multiscale simulation of an injection moulding process. The issues of ensuring identification and monitoring of objects of the industrial cyber-physical platform are considered. Specific service applications required to implement the smart product concept are discussed. The combination of the considered technologies is used to create digital twins of production system objects. All humans that have different roles in the product value stream can interact with the industrial cyber-physical platform at the three levels, receiving support in performing their tasks. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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Section: Resultsmentioning

confidence: 99%

“…A modern production facility is a complex system of systems [1]. It is composed of heterogeneous technological manufacturing and automation equipment and industrial communication networks.…”

Section: Introductionmentioning

confidence: 99%

Development of an industrial cyber-physical platform for small series production using digital twins

Yablochnikov

Chukichev

Timofeeva

et al. 2021

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

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Overall Prompting Effectiveness for Optimising Human-Machine Interaction in Cyber-Physical Systems

Wilbers,

Espinosa-Leal,

van de Sand

et al. 2024

Journal of Integrated Design and Process Science: Transactions

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This paper presents the Overall Prompting Effectiveness (OPE) framework, designed to enhance interactions with systems employing generative AI(genAI) through prompt engineering. Leveraging principles from Total Productive Maintenance (TPM): Overall Equipment Effectiveness (OEE), the OPE framework provides a systematic tool for iterative refinement of prompts, crucial for optimising human-AI interactions in cyber-physical-social-human systems. Evaluating prompting results in three actionable categories: Availability, Performance, and Quality, OPE aims to generate more accurate, relevant, and effective AI responses. Preliminary applications and workshops with prompt engineers underscore the potential of OPE to significantly improve the efficiency and effectiveness of AI engagements. The integration of OPE within Large Language Models (LLMs) or other genAI systems promises to expand automation capabilities, enhancing the intellectualisation and personalisation of CPS. This framework fosters continuous improvement in prompt quality and contributes to the synthetic knowledge management and smart reasoning mechanisms essential for advanced CPS. Our findings suggest that OPE could play a significant role in cognitive engineering, offering a novel methodology for enhancing decision-making and problem-solving in intelligent systems. This aligns with the current research directions in CPS, emphasising the need for tools supporting technology's socialisation and personalisation in complex integrated environments.

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Toward Digital Twin for Cyber Physical Production Systems Maintenance: Observation Framework Based on Artificial Intelligence Techniques

Cited by 2 publications

References 18 publications

Development of an industrial cyber-physical platform for small series production using digital twins

Development of an industrial cyber-physical platform for small series production using digital twins

Overall Prompting Effectiveness for Optimising Human-Machine Interaction in Cyber-Physical Systems

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