Cloud-Centric Real-Time Anomaly Detection Using Machine Learning Algorithms in Smart Manufacturing

As per the Australian Bureau of Statistics, 2019 manufacturing contributed $100 billion to GDP annually. Manufacturing is multidisciplinary, comprised of convoluted and complex operations with inefficiencies, making Australia less competitive globally. The main related reasonings were reworks, rejigging, lack of controls, miscommunications, lack of decisions, customer individual product demands and inventory costs. The research developed a novel SM framework providing distinct benefits over traditional manufacturing validated with textile manufacturing. The SM framework used artificial intelligence to harness: i) efficiency gains of over 31%, and ii) enhanced decisions saving 18% of costs and iii) unique agility for low-volume personalised product manufacturing.