Machine learning in cutting processes as enabler for smart sustainable manufacturing
Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
ENGLISH 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.
Description
CITATION: 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
The original publication is available at https://www.sciencedirect.com/journal/procedia-manufacturing
The original publication is available at https://www.sciencedirect.com/journal/procedia-manufacturing
Keywords
Machine learning, Manufacturing, Cutting processes, Sustainable engineering
Citation
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