Digitalisation and AI are increasingly reshaping the way industrial projects are engineered, executed and operated, with mine companies seeking new ways to unlock value from vast amounts of engineering and operational data.

During a recent webinar hosted by Creamer Media in partnership with Innomotics, the company demonstrated how AI-enabled solutions are being used to convert traditional engineering documentation into integrated digital intelligence, helping organisations improve efficiency, accelerate project execution and enhance operational decision-making.

Opening the webinar, Innomotics head of global sales for automation and digitalisation in minerals Sunny Schoone explained that the company’s digitalisation strategy is built around connecting engineering, automation and operations through a seamless digital ecosystem. [MP1] While Innomotics is widely recognised for its motors, drives and electrification solutions, the company has expanded its offering to include end-to-end automation and digitalisation capabilities designed to optimise industrial performance throughout the asset lifecycle.

Central to this approach is the creation of digital engineering environments that enable companies to build comprehensive digital representations of their plants and processes. By combining engineering data with simulation capabilities, organisations can create digital twins that support testing, optimisation, training and commissioning activities in a safe virtual environment before changes are implemented on site.

The webinar showcased how AI is helping bridge the gap between static engineering documents and dynamic digital systems. Innomotics Systems and Solutions product lifecycle manager and business developer Fabio Rodrigues Pimenta demonstrated how AI can extract valuable information from process and instrumentation diagrams (PNIDs) supplied in PDF format.

Using a web-based interface, engineers can upload a PNID and immediately begin querying the document through an AI assistant. Rather than manually searching through drawings, users can ask technical questions about equipment, instrumentation, signals and process functions. The AI assistant analyses the document and provides contextual responses, including relevant tags, instrument details and process information.

Once the document has been interpreted, the system automatically identifies equipment, pipelines, instruments and signals, generating structured engineering data that can be transferred directly into engineering databases. According to Pimenta, this capability significantly reduces the time required to create and populate engineering environments, allowing teams to establish comprehensive project structures in a fraction of the time traditionally required.

The webinar also highlighted the role of AI in automation engineering. Innomotics has developed tools that transform engineering data into project dashboards capable of tracking automation project progress in real time. These dashboards provide visibility into engineering execution, hardware configuration and software development, enabling project stakeholders to monitor progress through live project data.

AI also assists engineers in interpreting complex automation logic. These tools are built on real-world experience, and are the same solutions used within Innomotics to enhance efficiency, reliability and decision-making. During the demonstration, the system analysed control logic and interlock conditions, providing clear explanations of programme behaviour and operational sequences. This allows engineers and operators to understand automation functionality more quickly and reduces the effort required to review detailed control documentation.

Another area of focus was the use of AI to improve access to engineering documentation throughout the asset lifecycle. Quimey Stordeur, a COMOS specialist at Innomotics, presented a web-based solution that integrates AI-powered search capabilities with engineering document management systems.

The platform enables users to navigate engineering asset structures, preview large documents and access associated metadata through a browser-based interface. More significantly, users can perform semantic searches that identify documents based on meaning rather than exact keywords.

This capability is particularly valuable in industrial environments where operators and maintenance personnel often struggle to locate the correct documentation. Instead of searching through multiple folders and document descriptions, users can ask questions in natural language and receive direct answers supported by source references from the underlying documentation.

The solution also extends to mobile devices, enabling field personnel to access technical information, documentation and AI-assisted insights directly from smartphones and tablets.

The webinar demonstrated how AI is moving beyond experimental applications and becoming a practical engineering tool. By automating document interpretation, streamlining engineering workflows and improving access to information, Innomotics believes organisations can reduce engineering effort, improve project quality and create a stronger foundation for digital operations across the industrial value chain.