In manufacturing, the goal is to achieve optimal efficiency and quality. The Golden Batch concept is often used in the process industry to represent a production batch where all variables align perfectly—from raw materials to equipment operation—resulting in a product that meets or surpasses quality standards. Drawing on this concept, we developed the idea of a Golden Day in manufacturing, which envisions a day when every operation proceeds smoothly, machines function seamlessly, raw materials are available on time, production data is accurately recorded and the entire production line operates harmoniously.
What if such a situation wasn't exceptional but a norm? This is what we want to achieve by integrating artificial intelligence (AI) in manufacturing operations.
While AI's predictive capabilities are well-acknowledged (for example, in predictive maintenance or predictive quality), its potential extends beyond forecasting. AI can actively assist in decision-making processes within organizational operations. By distilling expertise from historical process control data with AI's capabilities it becomes feasible to identify potential production situations or disruptions and strategize to manage them best. This way, the manufacturing process can be optimized to achieve the desired outcome and minimize the risk of production loss due to unexpected events or wrong decisions. AI can support less experienced operators, providing them insights and reducing the gap in skills and expertise many manufacturing companies are experiencing.
An agnostic approach
One of the challenges in harnessing AI's potential is the complexity of developing mathematical models. However, the dependency on specialized data scientists diminishes with an agnostic AI platform. By pooling data from various sources, including sensors, machines and management systems, AI can predict and suggest actionable measures. An agnostic AI approach can help manufacturers simplify their data analysis process and leverage the power of AI to optimize their manufacturing operations.
From data to insights
The true potential of AI isn't just in gathering and contextualizing data but in translating this data into actionable insights. By analyzing vast datasets, AI can pinpoint optimal production parameters, identify process vulnerabilities and suggest corrective measures. Such insights empower even less-experienced operators to manage production efficiently. Moreover, AI can help manufacturers identify opportunities for process optimization by providing real-time insights and recommendations based on the data collected from various sources.
The broader vision
This approach to manufacturing is more than just a technological shift; it represents a broader vision for the industry. By integrating AI, the goal isn't just to achieve a "Golden Day," but to establish a consistent standard of excellence throughout the year. Manufacturers can leverage the power of AI to optimize their production processes, improve product quality and reduce costs. This can lead to a win-win situation for both manufacturers and customers, as manufacturers can produce high-quality products at a lower cost and customers can get better products at a lower price.
The integration of AI in manufacturing operations offers a very promising future. By moving beyond traditional paradigms of operations management and leveraging AI's capabilities, the industry stands on the edge of a transformative era where “optimal” production becomes the norm rather than the exception. Trends like “aging workforce,” “great resignation,” and the profound shift in workforce demographics and habits are significant challenges for any manufacturing company that AI can help to mitigate.
Moreover, the integration of AI in manufacturing operations can lead to a more sustainable future by reducing waste, improving energy efficiency, and minimizing the impact on the environment.
For all the reasons cited here, the integration of AI in manufacturing operations represents a paradigm shift and explains why it is poised to transform the industry.
Luigi De Bernardini is CEO at Autoware and president of Autoware Digital, certified members of the Control System Integrators Association (CSIA). For more information about Autoware, visit its profile on the Industrial Automation Exchange.