Partilhar via


Overview of manufacturing industry data model (preview)

Important

Some or all of this functionality is available as part of a preview release. The content and the functionality are subject to change.

The manufacturing industry data model (preview) is designed with a focus on enhancing Manufacturing Operations Management (MoM) and aims to empower production teams to make informed, data-driven decisions and elevate operations efficiency across the factory floor. At its core, Manufacturing data solutions streamline data across the diverse landscape of Operational Technology (OT), Information Technology (IT), and Engineering Technology (ET) systems. Our goal is to promote seamless interoperability and deliver a cohesive data consumption experience to our customers.

In preview, the manufacturing industry data model is aligned to ISA95 (IEC 62264), the leading industry standard for manufacturing operations management, the basis for many Manufacturing Execution Systems (MES) and many of the shop-floor systems for production, quality, maintenance, and inventory management.

Key advantages of manufacturing industry data model (preview) include:

  • Enhanced interoperability: Manufacturing industry data model (preview) accelerates achieving interoperability by applying an open-standards-based model with a proven track record of adoption. This interoperability ensures that both customers and partners understand the underlying semantics, facilitating seamless integration and communication across systems.

  • Democratized data access: The platform democratizes data access for both citizen developers and domain experts by utilizing a semantic model that supports low-code consumption methods. This approach simplifies the process of accessing and using data across various levels of technical expertise, empowering a wider range of users to use valuable insights.

  • Generative AI powered insights: Using a manufacturing semantic model, the manufacturing industry data model provides the connections and grammatical structure for generative AI copilots to deeply understand the data. This framework enables GenAI to uncover correlations, discern patterns, and establish causality and reasoning within the data, offering users the ability to derive insights and make informed decisions.

For more information about the manufacturing industry data model, see Data models in Microsoft Cloud for Manufacturing.