Machine learning in cutting processes as enabler for smart sustainable manufacturing

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dc.contributor.authorDu Preez, Anlien_ZA
dc.contributor.authorOosthuizen, Gert Adriaanen_ZA
dc.date.accessioned2021-11-02T14:14:09Z
dc.date.available2021-11-02T14:14:09Z
dc.date.issued2019
dc.descriptionCITATION: du Preez, A. & Oosthuizen, G. A. 2019. Machine learning in cutting processes as enabler for smart sustainable manufacturing. Procedia Manufacturing, 33: 810-817. doi:10.1016/j.promfg.2019.04.102
dc.descriptionThe original publication is available at https://www.sciencedirect.com/journal/procedia-manufacturing
dc.description.abstractENGLISH ABSTRACT: Machine learning is becoming an increasingly popular concept in the modern world since its most common goal is to optimize systems by allowing one to make smarter use of products and services. In the manufacturing industry machine learning can lead to cost savings, time savings, increased quality and waste reduction. At the same time, it enables systems to be designed for managing human behaviour. This research study used a systematic review to investigate the different machine learning algorithms within the sustainable manufacturing context. The study focuses specifically on cutting processes.en_ZA
dc.description.urihttps://www.sciencedirect.com/science/article/pii/S2351978919305839
dc.description.versionPublisher’s version
dc.format.extent8 pagesen_ZA
dc.identifier.citationdu Preez, A. & Oosthuizen, G. A. 2019. Machine learning in cutting processes as enabler for smart sustainable manufacturing. Procedia Manufacturing, 33: 810-817. doi:10.1016/j.promfg.2019.04.102
dc.identifier.issn2351-9789 (print)
dc.identifier.otherdoi:10.1016/j.promfg.2019.04.102
dc.identifier.urihttp://hdl.handle.net/10019.1/123342
dc.language.isoen_ZAen_ZA
dc.publisherElsevieren_ZA
dc.rights.holderAuthors retain rightsen_ZA
dc.subjectMachine learningen_ZA
dc.subjectManufacturingen_ZA
dc.subjectCutting processesen_ZA
dc.subjectSustainable engineeringen_ZA
dc.titleMachine learning in cutting processes as enabler for smart sustainable manufacturingen_ZA
dc.typeArticleen_ZA
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