A fingerprint approach for computationally efficient digital twins of precision manufacturing processes
Puthanveettil Madathil, Abhilash and Luo, Xichun and Liu, Qi and Madarkar, Rajeshkumar and Walker, Charles (2024) A fingerprint approach for computationally efficient digital twins of precision manufacturing processes. MATEC Web of Conferences, 401. 13004. ISSN 2261-236X (https://doi.org/10.1051/matecconf/202440113004)
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Abstract
Over the past decade, digital twin (DT) technology has seen significant advancements, enabling it to effectively address complex manufacturing challenges. However, the effectiveness of data-driven DTs is hindered by the sheer volume of data generated by sensors and devices which limits the traditional computational resources causing latency issues. To address this challenge, there is an urgent need to optimize data processing and ensure real-time responsiveness in DT applications. This paper presents a novel fingerprint-driven approach aimed at building computationally efficient DTs for smart manufacturing. When embedded within the DT framework, process and product fingerprints capture the essential manufacturing parameters while reducing the overall computational overhead of the DT. A case study on machining Inconel 718 for a high-fatigue application demonstrates the practical application of the proposed approach in ensuring computational efficiency. When compared to conventional machine learning (ML) methods, the fingerprint approach exhibited substantially superior performance in terms of responsiveness (20 times less latency) and prediction accuracy (3% more accurate).
ORCID iDs
Puthanveettil Madathil, Abhilash ORCID: https://orcid.org/0000-0001-5655-6196, Luo, Xichun ORCID: https://orcid.org/0000-0002-5024-7058, Liu, Qi ORCID: https://orcid.org/0000-0002-1960-7318, Madarkar, Rajeshkumar and Walker, Charles;-
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Item type: Article ID code: 90501 Dates: DateEvent27 August 2024Published1 August 2024AcceptedSubjects: Technology > Manufactures Department: Faculty of Engineering > Design, Manufacture and Engineering Management Depositing user: Pure Administrator Date deposited: 06 Sep 2024 10:34 Last modified: 01 Oct 2024 13:07 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/90501