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The Use of Machine Learning for Digital Shadowing in Thermal Spray Coatingстатья
- Авторы: Петровский С.В., Arifeen Murshedul, Петровский А.В.
- Сборник: Proceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23)
- Том: 1
- Год издания: 2023
- Место издания: Springer Nature Switzerland Cham
- Первая страница: 343
- Последняя страница: 352
- DOI: 10.1007/978-3-031-43789-2_32
- Аннотация: Digital shadows in industrial IT environments are virtual copies of production or manufacturing processes based on historical or real-time data obtained from physical sensors, control or automation systems. There is only one-way interaction between the shadowed process and its virtual copy, which differentiates a digital shadow from a digital twin exchanging the data in both directions. For many industrial applications, however, building a digital shadow using historical data is a sufficient, but quite challenging, task requiring the deployment of the entire data analytics pipeline. The presented paper demonstrates how machine learning and some related AI-based approaches can assist in developing and effective usage of intelligent IT applications. Thermal spray coating has been chosen as a use-case for demonstrating the applicability and feasibility of the chosen methodology for enhancing the operation of an industrial IT system supporting the coating process. The outcome of a comparative experimental studies demonstrated that artificial neural networks provide the most robust, versatile and generalisable technique for engineering data analytics in the chosen problem domain.
- Добавил в систему: Петровский Сергей Валерьевич