Machine learning is revolutionizing energy-intensive industries by enhancing process optimization, predictive maintenance, and operational efficiency. This presentation will delve into how machine learning technologies can be applied to process industries to drive innovation and sustainability. We will explore real-world applications, the benefits of integrating machine learning into existing systems, and the challenges that come with implementation.

• Process Optimization: Utilizing machine learning algorithms to optimize complex industrial processes, leading to increased efficiency and reduced energy consumption.
• Predictive Maintenance: Implementing machine learning models to predict equipment failures before they occur, minimizing downtime and maintenance costs.
• Operational Efficiency: Enhancing decision-making and operational control through real-time data analysis and machine learning insights.

The convergence of Information Technology (IT) and Operational Technology (OT) is a critical step towards achieving a more efficient, data-driven manufacturing environment. This panel will explore the strategies and best practices for integrating IT and OT systems, focusing on overcoming the significant barriers that organizations face. By addressing these challenges, companies can streamline their processes, enhance data utilization, and ultimately drive innovation and competitiveness in the manufacturing sector. The discussion will provide insights from industry experts on how to navigate the complexities of IT/OT integration and leverage the benefits of a unified approach.

• What are the most common challenges organizations encounter when attempting to integrate IT and OT systems, and how can these be mitigated?
• How can companies ensure data security and integrity during and after the integration of IT and OT systems?
• What role do emerging technologies, such as IoT and AI, play in facilitating IT/OT convergence, and how can organizations effectively implement these technologies to maximize their benefits?