Table of Content
- The Conception of Digital Twins
- Digital Twin Outputs and Their Role in Modern Inspection Processes
- Benefits of Digital Twins for NDT Inspections
- Technical Applications of AR in NDT
- Technical Evolution of NDT with Digital Twins and AR
- Key Takeaways
- FAQs
The concept of the Digital Twin—a digital counterpart of a physical object—dates back further than many realise. Initially emerging in NASA's Apollo space missions of the 1960s, early digital twins were used to replicate complex space-bound systems at ground level, enabling mission control to simulate and troubleshoot issues remotely. The role of digital twins became notably critical during the Apollo 13 mission (Source: https://ntrs.nasa.gov/citations/20210023699), where engineers employed a physical twin on Earth to resolve the life-threatening issues the astronauts were experiencing over 200,000 miles away. This milestone set the stage for today’s digital twin technology, incorporating real-time data and sophisticated simulations.
Alongside digital twins, Augmented Reality (AR) has emerged as a powerful tool, enabling inspection professionals to overlay real-time data directly onto physical assets. In industries with minimal margins for error, such as aviation, energy, and manufacturing, the integration of AR and Digital Twins has revolutionised Non-Destructive Testing processes, enhancing the inspection precision and maintenance workflows.
Digital Twins simulate the behaviour of components under real-time conditions in aviation and AR assists technicians in visualising this data in situ, leading to improved efficiency and reliability in inspections.
The Conception of Digital Twins
The formal concept of digital twins gained traction in 2002 through a presentation by Dr. Michael Grieves at the University of Michigan, outlining a model including the foundational elements of real and virtual spaces, with an interconnected data flow between them.
This concept has evolved into fully digital, data-rich twins since the Internet of Things (IoT) introduced connected sensors capable of monitoring every element of a physical asset’s operation in real time. Digital Twins and AR are rapidly gaining traction in aviation, energy, and manufacturing, where inspection precision directly impacts operational safety.
In aviation, where tolerances are narrow and the margin for error is virtually non-existent, Digital Twins simulate component behavior under various conditions. AR aids in overlaying this data directly onto physical assets for a precise, real-time inspection.
By improving inspection accuracy, these digital tools play a pivotal role in predictive maintenance and operational excellence, helping industries achieve higher standards in asset reliability and safety.
Digital Twin Outputs and Their Role in Modern Inspection Processes
(Source: Boyes, Hugh, and Tim Watson. "Digital twins: An analysis framework and open issues." Computers in Industry 143 (2022): 103763.)
One of the most compelling aspects of Digital Twin Technology lies in its versatile outputs, which can serve a diverse range of end-users and operational objectives. A Digital Twin can generate data that feeds back into the physical asset it represents, directly impacting its environment.
In aviation and high-stakes industries, Machine-to-Machine (M2M) outputs from a Digital Twin can provide crucial data for automated control systems, enabling real-time adjustments to operational parameters and, in some cases, autonomously responding to environmental conditions or detected anomalies. This feedback loop is essential for achieving inspection efficiency and ensuring component maintenance proactively.
Beyond immediate physical interactions, Digital Twin outputs offer extensive data integration capabilities for organisational Enterprise Resource Planning (ERP) or Manufacturing Resource Planning (MRP) systems. Data generated by a Digital Twin can be analysed within the ERP system to assess long-term trends in component wear or stress, thus supporting predictive maintenance models.
This data flow not only boosts maintenance using digital twins but also enhances the organisation’s ability to transform digital data into actionable insights, significantly impacting accuracy in aviation inspections with digital tools.
For end-users, especially in NDT, Digital Twin outputs deliver specific insights that improve operational precision.
Combined with Augmented Reality overlays, these outputs enable inspectors to visualise subsurface issues, understand the real-time condition of components, and make data-informed decisions immediately.
This integration fosters a digital transformation in NDT and maintenance processes, creating new standards for accuracy and dependability within the aviation sector and other critical industries.
Benefits of Digital Twins for NDT Inspections
Image Credit: GetManup
Digital Twins have enabled real-time data synchronisation across various industrial assets, such as aircraft engines, turbines, and structural components. These virtual models integrate data from embedded sensors, which monitor operational parameters like temperature, pressure, vibration, and stress.
Reduced Downtime through Proactive Asset Management:
In traditional NDT, inspections are scheduled based on a fixed timeline, leading to downtime for routine checks, even when no faults are present. With Digital Twins, inspections become condition-based, where assets are only taken offline when necessary. This real-time monitoring helps predict when components need repair or replacement, drastically reducing downtime and maintaining operational continuity.
Enhanced Simulation for Complex Systems:
Digital Twins model real-world physics, from simulating thermal stress in aircraft turbines or fatigue in structural components of a bridge, with advanced computational techniques. Engineers can simulate the impact of future stresses on aircraft structures, turbines, or engines, adjusting maintenance schedules accordingly.
Real-Time Data Synchronisation and Predictive Maintenance:
Through continuous data collection, the Digital Twin evolves with the physical system, allowing predictive maintenance rather than reactive repairs. AR technology complements Digital Twins by providing maintenance engineers with augmented views of the physical asset, overlaying sensor data, predictive analyses, and potential failure zones directly onto the aircraft’s structure.
Remote Monitoring and Inspection:
Remote monitoring is useful in geographically dispersed industries such as offshore wind farms, oil rigs, or space stations, where sending a team for physical inspection is costly and time-consuming. With AR technology, remote operators can conduct inspections via real-time visualisations projected onto digital models.
Real-Time Collaboration and Data Sharing:
Multiple teams, from field inspectors to engineers, can collaborate on the same Digital Twin model, regardless of location. This level of real-time collaboration ensures that inspection data is always up to date and readily available to those making critical decisions about maintenance or repair.
Improved Compliance:
Digital Twins provides an auditable record of all inspections and maintenance activities for industries governed by stringent regulatory standards, such as aerospace (e.g., AS9100) or energy. Recording every aspect of an inspection, from sensor data to predictive maintenance models, Digital Twins ensure transparency and regulatory compliance.
Sustainability:
As industries push towards sustainability, Digital Twins contribute by reducing waste through optimised resource use. By accurately predicting when a component needs repair or replacement, maintenance is conducted only when necessary, avoiding premature disposal of materials. This reduction in unnecessary inspections, repairs, and replacements helps industries minimise their environmental footprint, particularly in sectors such as aviation, where resource-intensive materials like metals and composites are used.
Early Detection:
In industries like aerospace and civil infrastructure, subsurface defects, such as cracks or delamination, pose significant risks. Digital Twins, equipped with NDT sensor data, allow for early detection of these hidden flaws by integrating ultrasonic, radiographic, and other sensor inputs into the virtual model.
Optimisation of Maintenance Schedules:
Rather than following a generic, periodic maintenance plan, Digital Twins allow for optimised maintenance schedules tailored to the actual condition of assets. In aviation, Digital Twins track engine cycles, landing gear usage, and airframe wear to predict when specific parts will reach their operational limit, ensuring the safest, most efficient scheduling of inspections and repairs.
Adaptive Learning and Continuous Feedback Loops:
Through machine learning algorithms, Digital Twins learn from past inspection cycles and adjust their models to predict anomalies. This allows for a dynamic inspection process where each successive inspection benefits from a more refined understanding of the system’s behaviour under operational stresses. Digital Twins align with modern Augmented Reality Applications, where real-time updates and predictive analyses can be overlaid on the physical component being inspected. This AR technology allows engineers to see how a component’s current state deviates from its ideal or original design, offering a more intuitive understanding of wear and tear.
Merging Digital Twins with augmented reality for aircraft inspections improves the accuracy of the inspection process, reducing the likelihood of human oversight and enabling early intervention before significant damage occurs.
Applications of AR in NDT
The applications of AR in NDT include:
1. Enhanced Weld Inspection Through Digital Twin Mapping:
In industries such as shipbuilding and aerospace, the integrity of welds is critical for structural safety. Augmented Reality (AR)-enabled digital twins allow inspectors to overlay weld maps directly onto components, identifying specific weld joints that require inspection or reinspection. By integrating with AR, inspectors can directly visualise real-time NDT data on critical welds, enhancing accuracy and reducing inspection times by over 30%.
2. Pipeline Corrosion Mapping and Wall Thickness Monitoring:
Corrosion detection and wall thickness assessment are central in pipeline integrity management. AR-integrated digital twins enable inspectors to view historical data on specific pipeline sections, tracking corrosion progression over time. Using AR goggles, NDT professionals can superimpose thickness data and wall loss rates on the pipeline's digital twin, revealing areas at risk of structural failure.
3. Real-Time Crack Propagation Analysis in Aerospace NDT:
In aerospace applications, monitoring crack growth in structural components such as wings, fuselage, and landing gear is essential to prevent catastrophic failure. Digital twins integrated with AR provide a visual framework for tracking crack initiation, propagation speed, and direction across critical components.
4. AR-Enabled Tank Floor Scanning for Above-Ground Storage Tanks:
Above-ground storage tanks (ASTs) used in petrochemical industries require regular bottom plate inspections to detect potential leaks and corrosion. With AR-enabled digital twins, inspectors can view floor scan data overlaid on a 3D model of the tank, isolating areas where corrosion or thinning has been detected. TThe integration of magnetic flux leakage (MFL) and ultrasonic testing data enhances defect identification, facilitating quick decision-making and potentially reducing inspection costs by up to 40%.
5. Valve Integrity Testing in High-Pressure Systems:
Digital twins for valve assemblies in high-pressure systems enable AR-based visualisation of critical parameters, including internal leakage rates, wear patterns, and operational cycles. AR can provide immediate, visual feedback on deviations detected by eddy current testing or radiographic NDT methods, helping inspectors assess valve conditions in real time.
6. Detailed Fatigue Analysis for Offshore Structures:
Offshore structures face unique challenges due to saltwater corrosion, fluctuating loads, and extreme weather conditions. Digital twins coupled with AR technology allow NDT inspectors to conduct fatigue analyses across structural components, monitoring strain data and overlaying it onto digital replicas. Using ultrasonic or magnetic particle testing data, AR can highlight vulnerable zones, such as joints and welds, offering a comprehensive view of component fatigue over time.
7. Eddy Current Array Mapping in Complex Geometries:
For assets with complex geometries—such as turbine blades, heat exchanger tubes, or intricate castings—eddy current array data can be mapped onto a digital twin. Using AR, inspectors can visualise subsurface defect distributions on the digital model, identifying cracks, voids, or inclusions that are otherwise difficult to detect. T
8. Structural Health Monitoring (SHM) for Large-Scale Infrastructure:
For long-term structural health monitoring, digital twins generated from photogrammetry and LiDAR data capture a comprehensive view of entire bridges, dams, or railway tracks. The digital twin can continuously update with new NDT data from embedded sensors, alerting engineers to any significant deviations from baseline conditions.
9. Enhanced Bolt Torque and Tension Inspection with AR Guidance:
Bolt integrity is critical for structures subjected to high stresses, such as wind turbines, transmission towers, and heavy machinery. By integrating ultrasonic bolt load measurement data, AR can also indicate bolts showing signs of loosening or fatigue, allowing maintenance teams to intervene promptly. This method improves accuracy and reduces human error in high-stakes inspections.
10. Robotic Inspections in Hazardous and Confined Spaces:
Drones and robots equipped with ultrasonic and visual sensors enable digital twin creation for assets in challenging environments. Robots, such as pipe crawlers with ultrasonic thickness sensors, create real-time digital replicas of pipelines, enabling remote inspection of confined or hazardous areas, thus significantly reducing risks and downtime.
11. SLAM-Based LiDAR for Internal Structural Mapping:
SLAM technology, combined with LiDAR, enables drones like the Elios 3 to capture internal structural details of complex environments. Real-time mapping of these internal spaces supports precise navigation, ensuring that NDT personnel can monitor asset integrity in real-time, with rapid feedback on potential structural issues.
12. Automated Corrosion Tracking and Mapping with SLAM-Enabled Robots:
SLAM-enabled robots equipped with corrosion-sensing technologies are invaluable in industrial settings, such as in chemical storage tanks or wastewater treatment facilities. Using SLAM, robots create accurate digital twins of surfaces affected by corrosion, mapping degradation patterns that can be analysed for future trends. This approach provides NDT inspectors with a powerful tool to understand corrosion progression, enabling precise maintenance planning and reducing unexpected failures.
13. Integrated Inspection Data Systems for Multi-Site Management:
Digital twins used in conjunction with inspection data management systems, such as the Mechanical Integrity Suite, allow NDT teams to manage data across multiple facilities. This integration supports real-time updates on equipment health, using risk-based inspection data to drive predictive maintenance.
14. Digital Twin for Online Monitoring in NDT:
Digital twins integrated with augmented reality (AR) devices, such as the Microsoft HoloLens, create virtual counterparts of specific components like valves, pumps, sensors, and tanks. In NDT, these digital twins synchronise with physical components to facilitate real-time monitoring and control through AR interfaces. Through predictive diagnostics, these AR-enhanced digital twins support proactive maintenance by forecasting issues before they become critical, significantly enhancing safety and operational efficiency in high-risk environments.
15. Digital Twin in Real-Time Optimisation and NDT Precision:
Digital twin-driven optimisation in manufacturing NDT processes brings high precision to defect detection and component analysis. Digital twins thus provide a continuous quality check loop, ensuring that components meet exacting NDT standards with minimal downtime and superior defect resolution, particularly in applications where parts must meet stringent tolerances, such as aerospace and automotive NDT inspections.
16. Cost Management for Facility-Wide Inspection Using Digital Twins:
For large-scale facilities, digital twins offer plant-wide cost control by allowing NDT professionals to monitor the condition of equipment across multiple locations simultaneously. In the energy sector, for example, predictive models in digital twins can align with AR-driven inspections, ensuring that critical assets are inspected and maintained effectively without excessive costs, adhering to compliance and safety standards.
17. Enhancing Defect Mapping Accuracy:
Traditional inspection methods—such as marking assets with chalk or paint—are prone to error and misinterpretation over time. Digital twins, however, streamline defect tracking by creating accurate, visual representations of physical assets that detail exact defect locations. This digital mapping accelerates the inspection process and improves reporting accuracy.
18. Data Collection Using Photogrammetry and LiDAR in NDT:
Digital twins for NDT applications are often created using high-resolution data captured via photogrammetry or LiDAR. Photogrammetry, a method of constructing 3D models from multiple images, enables inspectors to generate accurate digital replicas of inspected components or sites. When combined with real-time kinematic (RTK) positioning, photogrammetric models achieve high spatial accuracy, ideal for NDT inspections where precise measurements are critical.
LiDAR technology, using laser pulses to measure distances, is especially effective in creating digital twins of complex structures. LiDAR sensors mounted on drones or robots capture data that can be transformed into 3D models, which allow NDT inspectors to assess equipment and detect flaws with great precision, even in challenging environments.
19. Role of Drones and Robots in NDT Data Collection:
Equipped with photogrammetry or LiDAR sensors, drones and robots enhance NDT by providing high-quality imaging and data capture in confined or hazardous environments. The Elios 3 Indoor Inspection Drone leverages SLAM-based LiDAR for detailed indoor navigation, making it a valuable tool for NDT inspections where GPS coverage is limited, ensuring precise localisation and defect tracking.
20. LiDAR Digital Twins for GPS-Denied NDT Environments:
In environments where GPS is unreliable, Simultaneous Localisation and Mapping (SLAM) technology paired with LiDAR provides a comprehensive solution for spatial mapping and navigation. The Elios 3 drone utilises SLAM-based LiDAR to continuously adjust to new obstacles, offering a robust solution for real-time mapping in confined or hazardous NDT inspection zones.
21. Fixed Equipment Inspection Data Management:
For comprehensive NDT inspection data management, systems like the Mechanical Integrity Suite offer effective data organisation and ensure compliance with regulatory standards. By supporting time- or risk-based approaches, such systems streamline the inspection process for fixed equipment.
Technical Evolution of NDT with Digital Twins and AR
Digital Twins are set to evolve into self-improving, predictive models capable of detecting structural anomalies like micro-cracks or material fatigue in aircraft by incorporating Machine Learning (ML) and Artificial Intelligence (AI). This predictive capability will shift maintenance from a reactive to a proactive approach, minimising unexpected failures and optimising the life cycle of critical components.
AR-driven inspection applications will redefine how inspections are conducted in hazardous and hard-to-access environments.
Autonomous systems, such as AR-equipped drones, can conduct detailed visual inspections with minimal human intervention.
The strategic synergy of Digital Twins and AR in NDT will lead to faster, safer, and more reliable inspections, particularly in complex or safety-critical sectors.
As industries adopt these technologies, universal standards for Digital Twins and AR applications will emerge, allowing cross-sector integration that boosts operational accuracy and inspection scope. The convergence of AI-enhanced Digital Twins and AR-driven inspection processes will be instrumental in enabling efficient, real-time NDT operations, marking a pivotal advancement in inspection accuracy and safety across industries.
Key Takeaways
- Digital Twins and AR combine to deliver real-time monitoring and predictive maintenance, increasing inspection accuracy and reducing unplanned downtime in safety-critical industries.
- AR overlays critical inspection data directly onto physical assets, providing engineers with immediate, in-situ insights that reduce human error and improve inspection precision.
- Industries are shifting towards standardised, real-time inspection protocols, with the integration of Digital Twins and AR, marking a significant step towards predictive and condition-based maintenance.
FAQs
1. What are the main challenges of integrating Digital Twins and AR in inspection workflows?
A: Challenges include ensuring data accuracy, calibration across various systems, and managing the technical complexity of integrating real-time data with physical models, which requires sophisticated sensor and calibration systems.
2. How can Digital Twins and AR applications support sustainability goals?
A: These technologies promote resource efficiency by reducing unnecessary inspections and early repairs, minimising waste, and helping companies schedule maintenance only when needed, aligning with industry sustainability targets.
