Detecting failure of a material handling system through a cognitive twin

D’Amico, Rosario Davide; Sarkar, Arkopaul; Karray, Hedi; Addepalli, Sri; Erkoyuncu, John Ahmet

doi:10.1016/j.ifacol.2022.10.128

Cited by 5 publications

(1 citation statement)

References 8 publications

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“…Furthermore, DTs can be used for anomaly detection, as seen in studies like that of Calvo-Bascones et al [7]. They can also be used in combination with ontologies for failure detection [8].…”

Section: Introductionmentioning

confidence: 99%

Industrial Insights on Digital Twins in Manufacturing: Application Landscape, Current Practices, and Future Needs

D’Amico

Addepalli

Erkoyuncu

2023

BDCC

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The digital twin (DT) research field is experiencing rapid expansion; yet, the research on industrial practices in this area remains poorly understood. This paper aims to address this knowledge gap by sharing feedback and future requirements from the manufacturing industry. The methodology employed in this study involves an examination of a survey that received 99 responses and interviews with 14 experts from 10 prominent UK organisations, most of which are involved in the defence industry in the UK. The survey and interviews explored topics such as DT design, return on investment, drivers, inhibitors, and future directions for DT development in manufacturing. This study’s findings indicate that DTs should possess characteristics such as adaptability, scalability, interoperability, and the ability to support assets throughout their entire life cycle. On average, completed DT projects reach the breakeven point in less than two years. The primary motivators behind DT development were identified to be autonomy, customer satisfaction, safety, awareness, optimisation, and sustainability. Meanwhile, the main obstacles include a lack of expertise, funding, and interoperability. This study concludes that the federation of twins and a paradigm shift in industrial thinking are essential components for the future of DT development.

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Section: Introductionmentioning

confidence: 99%