Engineering Information: The Missing Foundation of Digital Transformation

As project sizes increase, the limitations of this document-centred approach become apparent. Engineering teams spend a great deal of time coordinating information rather than doing engineering work. Changes are implemented with a delay, inconsistencies arise and valuable knowledge is lost during the transition to plant operation.

This comes at a price! The engineering effort required is high, and the need for changes during the construction phase remains considerable. Furthermore, during the operational phase, hardly any usable data from the engineering phase is available for maintenance, revamps, and change management.

Therefore, the real challenge is not to introduce further engineering tools. The challenge lies in making engineering information consistently available throughout the entire lifecycle.

The question is: how can engineering information be kept consistent when numerous disciplines and software systems are working on the same project? The answer is not another engineering tool, but a common information model. This is where DEXPI 2.0 makes a significant contribution. Originally developed as an exchange standard for intelligent R&I flow diagrams, DEXPI has evolved into a comprehensive process and plant information model for the early engineering phases. Rather than focusing solely on document exchange, DEXPI 2.0 provides a standardised representation of engineering information spanning process engineering and basic plant design. The model captures the topology of a process and the underlying engineering semantics, including process functions, equipment objects, piping systems, instrumentation, and their relationships. All elements become part of a consistent digital information structure that can be interpreted by different engineering applications. 

This fundamentally shifts the focus from standardised engineering software to standardised engineering information. Engineering information grows continuously throughout the lifecycle. From process development, through basic and detailed engineering, to commissioning, operation, and revamps, all stakeholders contribute to the same engineering objects. A pump, for instance, evolves from a process requirement to a specified asset and finally to an installed asset with its own operational history. No new objects are created; only new information about the same object is added.

No single information model can describe every aspect of a process plant throughout its entire life cycle. Process engineering, detailed equipment specifications, three-dimensional plant models, procurement, operation and maintenance all require different information at different stages. Therefore, the challenge is not to create a universal standard, but to ensure that different information models work together seamlessly. This is precisely the direction in which the industry is currently moving.

DEXPI 2.0 provides a standardised process and plant information model for the early engineering phases, describing process functions, engineering objects, and plant topology from conceptual design to basic engineering. As the project progresses, further standards contribute supplementary information. CFIHOS defines the structured information requirements for project handover and operation, while FL3DMS addresses the management of three-dimensional engineering information throughout a plant's entire life cycle. International semantic standards, such as ISO 15926 and the emerging Industrial Data Ontology (ISO 23726), establish common concepts and relationships. This ensures that information remains interpretable across software platforms and throughout decades of plant operation. Rather than competing with one another, these initiatives are increasingly complementing one another.

Perhaps the most significant development is that they are no longer evolving independently of one another. Eleven industry associations, standardisation organisations, and user groups are now jointly aligning their information models through the 'Asset Lifecycle Information Management' (ALIM) best-practice initiative. They are working together to harmonise the definitions of process functions, engineering objects, equipment classes, tags and semantic relationships across the entire plant lifecycle. This collaboration marks an important shift: whereas engineering interoperability used to focus primarily on the exchange of files between software systems, today the emphasis is on sharing a common understanding of engineering information. If engineering objects have the same meaning regardless of the software used to create them, information does not need to be translated every time it crosses an organisational or technical boundary. For operators, EPC contractors and technology suppliers, this reduces integration efforts, improves data quality and creates a far more robust foundation for lifecycle information management.

With the advent of artificial intelligence, this development is taking on even greater significance. AI can only perform as well as the information on which it is based allows. Large language models such as ChatGPT utilise structured semantic relationships between terms. Similarly, industrial AI requires structured semantic relationships between process functions, equipment, pipework, instrumentation, and plant objects. Without this foundation, AI can search through documents, but it cannot understand engineering contexts.

Therefore, lifecycle information management not only creates more efficient engineering processes but also forms the basis of information for AI-supported design reviews, engineering co-pilots, digital twins and data-driven asset management.

Over the past few decades, the process industry has digitised its engineering tools. The next stage of development now focuses on the engineering information itself. Organisations that establish integrated lifecycle information models today are therefore improving their engineering processes. They are also creating a shared information base for AI, digital twins, and the consistent application of engineering knowledge throughout a plant’s entire lifecycle.

In the coming years, the real competitive advantage will not lie solely in better software tools, but in the ability to make engineering information consistent, reusable and accessible across systems.