2.1 AI Supported Manufacturing Processes
In this era of consumer centric business environment, supply chain management has changed from push based model to pull based model for many consumer products (Janvier-James, 2012). After an order is received from a web frontend, the order is forwarded to uplink manufactures and probably their suppliers to start the manufacturing process. When products are ready for delivery, logistic companies are notified to pick up and deliver the order to customers in time. With the advent of internet of things, more and more manufacturers are starting to integrate their operational technology with information technology.
AI plays the role of a brain in Industry 4.0 applications. An Accenture research report shows that AI has the potential to boost profitability by 39% in manufacturing industry in 2035 (Purdy & Daugherty, 2017). AI helps factories with predictive maintenance to avoid unplanned downtime (Confalonieri et al., 2015), quality control to increase product profitability (Weimer et al., 2016), and job scheduling to increase manufacturing efficiency (Calis & Bulkan, 2015) among many other issues. Because of the unprecedented success of CNNs in computer vision applications, deep learning has been used in many recent AI supported manufacturing processes (Lin et al., 2018; Weimer et al., 2016).