Driving Digital Thread Initiatives in the Automotive, Aerospace and Engineering Industries

Written by missing user171 do not delete on 08 January 2024. Posted in PROJECT INSIGHTS - ENGINEERING & MANUFACTURING

metaphactory supports a number of customers across the automotive, aerospace and engineering industries in driving Digital Thread initiatives as strategic differentiators in their digital transformation and AI journeys. With Digital Thread, these customers enable their organizations to achieve safety, certification and configuration management objectives and use AI to significantly scale and speed up decision-making based on more precise and contextualized knowledge and insights.

What is Digital Thread?

Knowledge workers in large organizations can spend up to 30% of their time searching for information and may need up to eight attempts to find an accurate answer to their search query.¹ They rely heavily on data scientists and data engineers to search, integrate and provide them with consumable data products, which are usually not reusable outside of the use case they were created for. Additionally, organizations have access to an ever-increasing amount of data which humans alone cannot manually process or leverage to its full potential.

Digital Thread initiatives support consistent modeling and management of data and metadata across the lifecycle of a product, process or system, and in a format that is both human- and machine-interpretable and executable. Because all the data and models used to describe a particular product, process or system throughout its lifecycle are linked as part of the Digital Thread, they only need to be created once and can then be used by all downstream data consumers. Additionally, they provide the context, traceability, provenance and relationships to other products, processes and systems. They can enable AI-driven business decisions and trace the evidence and rationale behind them, as well as enable continuity over time and across domains.

By implementing Digital Thread, organizations support their teams in capturing, linking, communicating, using and reusing knowledge across systems, departments and processes, ultimately enabling them to use the interlinked knowledge to inform decisions and create value for the business.

metaphactory – A key component of Digital Thread solutions

metaphactory is a fundamental part of the supporting Digital Thread initiatives. Customers use metaphactory to semantically model their domain knowledge and create a shared understanding of the knowledge available in the organization.

metaphactory allows customers across the automotive, aerospace and engineering industries to model, manage and govern their schemas – from upper-ontologies to domain ontologies – and provide an end-to-end view of how information flows and changes over time or across different processes. This is achieved by explicitly capturing concepts and processes that are relevant to the business domain, along with their logical structures and relations, and their corresponding physical systems and IT applications. Relevant governance metadata documenting how models and data have been transformed and who owns them and is responsible for them ensures that assets are reusable across use cases and domains. Moreover, comprehensive governance workflows help streamline change and communication and collaboration processes across teams, stakeholders and departments.

metaphactory's semantic knowledge modeling capabilities support customers in their Digital Thread initiatives by enabling them to:

• bridge the semantic gap by enabling machine-interpretable, explicit semantics across the entire data value chain,
• augment explicit knowledge (symbolic AI) with AI algorithms to scale and drive more informed decisions and encourage innovation,
• transition their strategy away from application-centricity and towards data- and knowledge-centricity.

Throughout the entire design process of the Digital Thread, metaphactory follows a data- and user-centric approach, as opposed to an application-centric approach. This is enabled by an intuitive visual modeling interface that allows all relevant stakeholders - from knowledge graph engineers to domain experts - to contribute to the ontology modeling process. Ultimately, this leads to interoperable and vendor-agnostic domain-ontologies and solutions that can easily integrate with the customer's existing ecosystem.

Example use cases

By establishing connections between the physical and virtual layers of data management, a Digital Thread strategy provides the foundation for developing and implementing valid digital twin solutions. Ultimately, customers can use these to support use cases such as:

• Product lifecycle management – from R&D and design, through development and testing, to manufacturing and distribution – improve and manage the accuracy of products developed; ensure that parts and products meet requirements and specifications and follow all relevant protocols
• Supply chain management – digitally identify, track and verify parts and products to streamline processes
• Operations management – support inventory management and after-sales operations; identify and quantify risks and uncertainties and how they propagate and make informed decisions across the entire lifecycle of a product
• Process and outcomes documentation – capture steps relevant in certain processes and decision making in a transparent manner; prevent data duplication and support traceability

References

¹ Digital Thread: Definition, Value, and Reference Model