Abstract: Did you know that all manufacturing processes generate about a third of all data today? With the recent rise of digital manufacturing this percentage will likely continue to increase in the coming years. Industry 4.0 could be viewed as the next phase in digital manufacturing, and it is driven by several main technologies: (i) Internet of Things (IoT) and astonishing amounts of generated data; (ii) physical connectivity and integration; (iii) Big Data Analytics enabled by computational power; (iv) augmented-reality systems and (v) advanced robotics. Industry 4.0 promises higher productivity, rapid innovation, reduced costs, and improved customer satisfaction. However, the adoption has been very slow. The main reason is probably that many manufacturing companies still lack the foundational technology infrastructure that must be in place before they can fully exploit Industry 4.0.
The talk will offer practical advices how to collect and effectively organize enormous amount of industrial data from various siloed sources into a cloud data lake and then unleash the full power of advanced analytics to help benefit manufacturing companies. The speaker will also cover a few use cases how machine learning and AI helped digital manufacturing organizations. The first one is predictive maintenance, where equipment with IoT is remotely monitored to early predict its failures, diagnose the root cause of the faults and predict equipment remaining useful life. The second one is supply chain management, where real-time machine learning is used to track the location of assets in transit, predict when shipments will arrive and provide end-to-end visibility of goods throughout the supply chain.
Bio: Coming soon
Aleksandar Lazarevic, PhD
VP of Advanced Analytics and Data Engineering | Stanley Black & Decker