Predictive quality solutions aim to detect, identify, predict and prevent product quality issues before they occur by utilizing AI-based machine learning algorithms that automatically analyze and monitor quality and process parameters. The actionable intelligence derived from these data insights can help enhance business operations by optimizing production processes, reducing costs and wasted scrap, and preventing warranty claims and recalls. In this webinar, we will discuss predictive quality solutions through several industry case studies, how they address common industry pain points and provide value to businesses, as well as what kinds of infrastructure and data you will need to get started in each area. The case studies will span multiple manufacturing industries in automotive and CPG.
About the Presenter: Mo Abuali, PhD Managing Partner at IoTco
Dr. Mo Abuali is the CEO and Managing Partner at IoTco, the internet of things company. He is a strategic and transformative technology and business management leader with 20-year record of achievement driving and sustaining change in Manufacturing. . Mo serves Industrial and Manufacturing Clients in Automotive, Aerospace & Defense, and others, providing Digital Transformation, Industrial IoT (IIoT), and Predictive Analytics technology and services, as well as the IoT Academy for Industry 4.0 Training. Mo has a doctorate degree in Industrial Engineering and has worked with companies like IBM, P&G, Omron, and Toyota.