The semiconductor industry, a cornerstone of modern technology, faces critical sustainability challenges. As companies strive to shorten product life cycles and innovate rapidly, artificial intelligence (AI) and machine learning (ML) emerge as powerful tools to drive sustainability. ML driven AI creates actionable insights through real-time monitoring of energy consumption, water and gas usage, and waste generation. By identifying inefficiencies and their sources or causes, companies can more quickly identify and implement meaningful improvements.
During this technology spotlight, we will discuss the positive impacts on operations on advancing automation and decision intelligence capabilities throughout the fab, and how digital transformation for greater sustainability is not as daunting of an initiative as it may seem. Advances in machine learning have made it possible to efficiently apply advanced analytics to operational data on a variety of processes throughout the fab. As these technologies continually evolve, it is important to understand how they can be applied to, and interact with existing systems in the fab to increase efficiency, reliability, and sustainability.
We will also highlight examples and use cases leveraging AI to consume available data (electrical signals, vibration data, or process measurements) from sub fab assets to determine whether a pump, a motor, or a process is deviating from normal operation, and apply ML and AI to determine what actions may be required. Results show that AI-enabled, data-driven, condition-based monitoring increases fab’s facility maintenance productivity and reduces unplanned downtime.
Additionally, we will demonstrate how AI can monitor a controller, determine performance deteriorations of the operation being controlled, and by discovering the causal relationships that underpin the operation and/or mining best past practices, recommend and deploy corrective action that restores optimal controller and process behavior. Unlike more rigid control optimization techniques, these continuous learning and AI-driven modifications to the control system can respond to the presence of uncontrolled variables that directly affect complex processes like water treatment.
Please join us to learn more about how the digital transformation in the Semiconductor Industry is advancing and how AI can be successfully implemented to improve sustainability and operational outcomes in energy usage, water savings, operator interventions, and reduction in waste across all aspects of a utility's operations in a fab, including the optimization of pumping system and wastewater treatment operation.
By embracing AI-driven sustainability practices, the SEMI industry can achieve economic gains while minimizing its environmental impact.
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