IIC Journal of Innovation 6th Edition - Page 13

How Democratized Artificial Intelligence Can Move Manufacturing to a New Evolution Pace final product quality issue detection, production performance fluctuation detection, safety and security issue detections and help you to react as soon as possible before having a worse situation to manage. For those two detections of AI technologies, it is important to understand that we must change our usual way to capture and record data from real-life. The usual way, currently implemented in Manufacturing Execution Systems, is to filter the raw data to record only the abnormal behaviors detected by predefined engineering models and set up thresholds on filtered indicators that you want to monitor. This approach was implemented to reduce the cost of data communication and storage and emphasized the limited computing power which was not able to process large amounts of data to provide useful insights. capability to process and analyze the data, it makes the historic data management approach obsolete and dangerous. Dangerous, because it is not giving the new Predictive and Machine Learning AI the opportunity to provide their power and valuable outcomes. And dangerous because the new manufacturing world of introducing new high-quality products quickly to the market – produced on new equipment, with new worker skillset, new raw materials and new suppliers – cannot wait to meet and identify all potential issues at a “human” ramp up speed, to know and place them under control. Now, we must continuously learn, predict and react at a digital speed to constantly adjust the excellence practices to achieve our short-term and long-term goals. If you want to setup a new production line, you now have a few months to deliver your product and optimize your costs. While before now, you had a few years. Now, with new technologies of cheap data capture, communication and recording, associated with an almost “unlimited” Figure 4: Example of prediction and machine learning analytics embedded in an Asset Monitoring platform - 12 - November 2017