Driving Zero-Downtime, Zero-Defect Manufacturing with Industrial A.I.
A reduction in unplanned downtime or a few percentages of scrap reduction can yield millions of dollars in savings for manufacturers. This compelling value proposition has resulted in significant investment and interest in using predictive maintenance and predictive quality solutions based on artificial intelligence (AI). This presentation will address many of those challenges and present compelling real-world business examples with demonstrated value for rapidly deploying AI in manufacturing. You will be introduced to a methodology to define the business and technical problem, a state-of-the-art and end-to-end analysis platform from data collection to the delivery of the health and process information, and lessons learned on how the solution can be maintained and improved over time. These case studies will shed light on how manufacturers can transform from a “fail and fix” to a “predict and prevent” zero-downtime and zero-defect operation.
Mo Abuali, PhD - IoTco, LLC
AI for Good - Leveraging AI for Sustainable Practices in the Manufacturing Industry
The Pandemic of 2020 demonstrated the importance of sustainability within manufacturing environments, with many leaders navigating environmental factors outside of their control. Sustainability is not only a corporate responsibility, it is also a shared social responsibility. Thus, there should be a tool that individuals and manufacturing organizations of all sizes can access to positively contribute to a more sustainable world. In this presentation, we will discuss how a democratized AI solution can benefit the organization that develops this tool or marketplace, the manufacturing industry as a whole, as well as the organization’s consumers, to allow us to achieve the 2030 goal the United Nations set forth in 2015.
Justin L. Goldston, PhD - Penn State University
Smart Manufacturing Track Sponsored by:
