Published on February 20, 2024, 12:13 pm

Manufacturers in the industry have maintained a data-driven vision for the future, emphasizing the importance of streamlined data flow between IT and operational technology systems. This vision encompasses the integration of all types of data – structured, semi-structured, and unstructured – into automated processes and AI tools. By enabling this seamless data exchange, companies aim to create a more adaptable sector capable of responding effectively to continuous changes.

Despite this aspiration, many manufacturers face challenges due to legacy data management practices that hinder their ability to fully embrace transformative technologies. Data segregation within facilities, departments, and systems, coupled with the lack of integration between IT and OT networks, has impeded progress. Additionally, difficulties in harnessing unstructured data have resulted in missed opportunities to extract valuable insights from various sources such as CAD designs, audio or video files, and maintenance records.

Generative AI presents unprecedented opportunities for manufacturers to enhance operational decision-making significantly. By 2030, up to 75% of decisions could be facilitated through AI applications. Leveraging generative AI can lead to risk reduction, increased resilience and agility, heightened productivity levels, and minimized environmental impact within manufacturing processes.

Industry pioneers like Denso have begun exploring advanced use cases for AI technology. For instance, Denso utilizes AI solutions to organize unstructured data efficiently across its operations. Through platforms such as Microsoft Copilot, Denso has automated manual tasks, streamlined search functionalities, and enhanced information accessibility across its organization. Such implementations not only optimize workflows but also facilitate knowledge sharing and utilization among employees.

Key players acknowledge that achieving IT-OT convergence demands a fundamental shift in data management practices to unleash the full potential of generative AI tools. Industrial knowledge graphs are increasingly recognized as indispensable tools that merge structured and unstructured data sources from diverse software systems to enhance decision-making processes and drive advanced automation initiatives.

The adoption of a graph-of-graphs approach enables comprehensive insights into the manufacturing ecosystem by consolidating information from various operational software systems onto a unified platform. This strategy amplifies the capabilities of AI applications like Microsoft Copilot by empowering organizations with real-time collective intelligence derived from interconnected datasets.

Experts emphasize that industrial knowledge graphs play a pivotal role in realizing IT-OT convergence aspirations while maximizing the benefits of AI technologies within manufacturing settings. Collaborating with proficient teams specializing in Microsoft technologies can expedite this transition journey towards establishing robust data foundations for future-proof manufacturing operations centered on employee empowerment.

For companies looking to delve deeper into IT-OT convergence and AI implementations tailored to their specific needs, workshops conducted by industry experts can provide valuable insights and guidance on navigating these technological advancements seamlessly within their business frameworks without disrupting existing operations.


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