‘Shared Reality’ can transform outdated, complex industrial sites into continuously updated, intelligent 3D models within days. Thomas Grand, Director of Operations (Chief Operating Officer) at Samp, explains all.
As global industries strive for operational resilience, safety, and sustainability, high-risk sectors such as oil and gas, chemical processing, and energy are turning to digital twin initiatives to help meet these demands.
However, the term “digital twin” is often misunderstood. It’s critical to understand that a digital twin is not a single technology but rather an enterprise initiative that combines multiple technologies, adapts business workflows, and serves as a dynamic and evolving representation of physical assets.
This distinction is key. Many perceive digital twins as standalone solutions, but they are more accurately described as a strategic framework—one that integrates various tools like AI, reality capture, 3D reality models and advanced web technologies to create a single, actionable source of truth. A platform where these technologies can work cohesively acts as a mortar between the bricks, helping industrial teams to unlock the full potential of digital twin deployments.
Deploying digital twin programs is no longer a futuristic ambition, but a strategic imperative for high-risk industries aiming to drive operational excellence. However, the road to effective deployment comes with its own set of challenges and learnings.
So, what lessons should these high-risk industries take note of when deploying digital twin initiatives?
1. Transform 3D reality capture into 3D reality models
Sites are constantly shifting as they are built and maintained. So, a 3D visualisation of a site needs to mirror all of these details, imperfections and changes, whether they are planned or not, and ensure they are captured and visible. Unlike a theoretical computer-aided design (CAD) model, where changes would have to be made manually, a 3D reality model can provide an unmatched understanding of the reality of a site. In comparison, 3D reality also ensures a quicker process with real-time data insights too.
But how do you move from 3D reality capture, which shows a site at a given moment, to a 3D reality model, which can continually show exactly how a site looks and works in real time?
Beyond 3D geometry, a key part of the process is to ‘assetise’ the reality capture into a 3D reality model. This means identifying and organising equipment or assets in ‘the scene’, which can then be manipulated (i.e. hidden or exported) and linked with their technical data, such as equipment lists, properties or layout diagrams.
However, traditional approaches to this process involve techniques like 3D CAD remodelling, also known as “scan-to-BIM” – this is an expensive and time-consuming method that oversimplifies reality and limits a 3D scan’s wider usage. But if these industries harness new technologies, including AI, they can transform 3D scans into interactive, usable models without the need for a scan-to-BIM approach.
2. Recognise that some HSE risks are more visible in the virtual world
In the chemical industry, where managing hazardous materials and complex systems is routine, ensuring safety is paramount. Digital twin technology—and particularly agile solutions such as 3D reality models, have become key enablers for Health, Safety, and Environment (HSE) use cases.
Unlike traditional models, 3D reality models offer highly detailed, real-world replicas of industrial sites, its object-oriented nature and ‘site fidelity’ allows teams to produce highly accurate and detailed representations of physical sites. Industry players can then empower all teams (operators, maintenance, engineering, management, contractors) to prepare and execute their work without encountering any surprises onsite. By using the reality of the field as the single reliable source of truth, all work orders and projects are executed safely and efficiently.
In fact, it is the combination of 3D reality models with other critical technical information that can provide the optimum model. A piping and instrumentation diagram (P&ID), for example, shows how equipment, pipes and instrumentation connect. The combination of 3D reality models with P&IDs can make certain HSE risks more visible than in the real world because it offers a clear, virtual way to analyse and simulate potential risks before they occur.
The 3D reality model, for example, provides a realistic and detailed view of the equipment and layout that’s often clearer and more comprehensive than what you’d see during a walk-through, helping to spot hazards like tight spaces or dangerous proximity between equipment and people. The P&ID diagrams show how everything is connected in the system.
Using this combination can help make processes like ‘lockout tagout’, where equipment is isolated and machines shut down for maintenance and safety, easier and safer – engineers can simulate lockout tagout sequences without real-world risks and predict what could go wrong if something is isolated incorrectly or if there’s a pressure build-up.
While physical checks are still crucial to the process, these advanced technologies can identify hidden risks that might be missed altogether in the real world. They provide a proactive and preventative approach to HSE risks.
3. Create transparency across all systems
Outdated technical documentation leads to major hazards and severe inefficiencies for maintenance and revamping projects. Yet keeping your data in sync with reality is a massive challenge. As a result, operators must ensure that their digital twin approach provides integrations that allow them to connect equipment within the 3D reality models with their corresponding records stored in legacy systems such as Enterprise Asset Management or Computerized Maintenance Management Systems (EAM & CMMS).
Such integrations can deliver real extra value. They provide faster and easier access to information stored across different systems, improve the user experience (compared to legacy systems), and help to visually identify discrepancies. With this common visual data context, industry players can not only overcome the challenges of data quality and collaboration but also empower all of their teams, from maintenance and engineers to procurement and contractors, to easily access and see any changes to the 3D reality model and associated technical data.
Lessons to deploy
With digital twin enablers such as Shared Reality now a strategic necessity for high-risk industries, getting the most value out of its deployment can make a real difference in achieving operational excellence. These industries can unlock significant value by ensuring their digital twins serve as a single source of truth grounded in reality, seamlessly integrated with existing systems. This approach not only safeguards operational integrity but also lays a foundation for sustainable growth and resilience in an increasingly complex industrial landscape.
