Manufacturing ontologies play a crucial role in the architecture and improvements of manufacturing systems, particularly in the context of Industry 4.0. Here are some reasons why:
- Effective Information Management: Ontologies provide an effective way to manage information and data from production systems by describing them in a common language. Often, this language is standardized, like in this case. This is critical for digital transformation, where the integration of existing systems requires data transformation to allow efficient data processing.
- Semantic Support and Reasoning Capability: Ontologies provide the semantic support for sharing and accessing manufacturing-related data in a global cloud environment. They also offer the reasoning capability to analyze digital manufacturing data for making intelligent decisions.
- Enhanced Competitiveness: It is critical to capture and share product manufacturability knowledge across all sites in a global manufacturing enterprise, to enhance competitiveness. Ontologies can make this knowledge shareable more easily.
- Support for AI-Assisted Decision Making: With the help of AI, including AI based on Large Language Models, the utilization of ontologies supports decision making in industrial projects, such as preventive maintenance of manufacturing systems, diagnosis and prognostics, cost estimation, etc.
- Interoperability and Avoid Misinterpretation Issues: In manufacturing, a process plan for a product comprises manufacturing operations, their sequences, and manufacturing resources for implementing the operations. An ontology can semantically represent this knowledge, avoiding interoperability and misinterpretation issues.
Therefore, paying attention to the architecture and improvements of manufacturing ontologies leads to more efficient, effective, and competitive manufacturing processes.
We have recently made the following improvements to the Manufacturing Ontologies reference solution and expect a significant positive impact to manufacturing systems leveraging this solution as a result:
- Integrating Azure IoT Operations: Azure IoT Operations, enabled by Azure Arc, helps organizations onboard assets, capture insights, and take actions to scale the digital transformation of their physical operations. Due to its built-in high availability and support for open industrial standards, it reduces downtime and enables scale in a global rollout due to its centralized manageability.
- Adding the ISA95 asset hierarchy into OPC UA metadata messages: This significantly simplifies the calculation of Overall Equipment Effectiveness (OEE) in the Cloud. ISA-95 provides, among many other things, a standard way to describe the asset hierarchy of a manufacturing operation. By integrating this directly into OPC UA metadata messages, it allows for secure and efficient data transfer, enhancing interoperability.
- Encoding ISA95 models as standard W3C Web of Things models: Alongside the existing DTDL models, these new models give an additional option for increased interoperability with existing systems. The W3C Web of Things provides a standardized way to describe assets and processes and acts as an abstraction layer for existing platforms, devices, gateways, and services, complementing existing standards.
- Integrating Dynamics 365 Field Service for maintenance scenarios: This improves the efficiency of maintenance operations. Dynamics 365 Field Service provides AI-driven assistance and remote expert support, enabling faster and more impactful frontline services. It can reduce hours billed for repair and maintenance work orders, decrease field dispatch, cut commuting time, and reduce service calls.
- Simplifying the deployment of the solution and Azure Arc onboarding: This makes the deployment process smoother and more efficient, reducing time to value.
- Cost-optimizing the solution: Cost optimization in manufacturing is a complex business problem that involves the dynamic interaction of design choices with the total cost structure of all product leveraged. This is especially true for Cloud operations, where many pieces have to come together.
- Simplifying the reference architecture diagram and adding a simpler overview diagram: A software’s architecture is the foundation for any successful software system. It influences everything from maintainability, scalability, stability, and security throughout that system’s lifecycle. This is why it is so important to get the architecture right from the start and continuous simplification is required to keep the entire system efficient, especially as new features are added.
We hope that you find the recent improvements beneficial to your manufacturing operation and we can’t wait to hear your feedback on it, either through this tech community channel or directly on the GitHub page of the Manufacturing Ontologies repository: https://github.com/digitaltwinconsortium/ManufacturingOntologies