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• W4322731715 abstract "The updated trends in manufacturing industries and use of technologies like industry 4.0, Internet of Things (IoT), and Smart Factory are been implemented in the production of a product for series of sequential operations to obtain end product which can be used further. Machine learning (ML) enables the scope of automation by using previous data used to manufacture or build a product, improves the productivity of an industry. ML is categorized into sub-components namely supervised learning, Unsupervised learning and Reinforcement learning, and these approaches have their own identity in the field of automation. This paper reviews the various Machine Learning techniques which are been implemented in the production process and summarize the concept of ML to understand it better, recent developments by using ML are also been included in this study, implementing ML in 3D printing to predict the best angle of deposition in FDM." @default.
• W4322731715 created "2023-03-03" @default.
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• W4322731715 date "2022-11-25" @default.
• W4322731715 modified "2023-10-01" @default.
• W4322731715 title "Machine Learning based Comparative Analysis and Prediction for Sustainable Additive Manufacturing" @default.
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• W4322731715 doi "https://doi.org/10.1109/pdgc56933.2022.10053152" @default.
• W4322731715 hasPublicationYear "2022" @default.
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