From Digital Twins to Digital Triplets: Advancing NDT and Inspections
Introduction
Non-destructive testing (NDT) has been integral to quality assurance since the dawn of the industrial revolution. It is the silent guardian ensuring that airplanes land safely and that cell phones connect seamlessly to satellites orbiting miles above. These everyday conveniences, often taken for granted, are the result of meticulous inspections carried out by machines, humans, and, more recently, artificial intelligence. From the manual inspection of an aircraft's landing gear to sophisticated computed tomography (CT) scans of intricate engine components, these tests form the backbone of our expectation that technology simply works.
The Role of Digital Twins in Failure Prediction
While NDT remains crucial for safety and reliability, the advent of digital twins represents a significant leap forward in predictive maintenance and lifecycle management. A digital twin is a precise virtual replica of a physical object, such as an aircraft or a smartphone, housed within a computer system. This digital counterpart undergoes the same lifecycle as its physical version—whether it's simulating take-offs and landings or replicating social media interactions and phone calls. By doing so, it allows for the prediction of potential failures and, importantly, the extension of the product's lifespan.
The digital twin, existing in a virtual and highly controlled environment, can simulate real-world scenarios at a much faster pace, predicting issues before they manifest in the physical world. Today, digital twins are indispensable in process and product optimization across various industries.
Waygate Technologies and the Emergence of Digital Triplets
At Waygate Technologies, a leader in industrial inspection and NDT solutions, we are pushing the boundaries by integrating industrial inspection data with digital twins to create what we term the "digital triplet." This innovative approach adds a third dimension—real-world inspection data—to the digital twin, creating a more accurate and reliable predictive model.
From Twins to Triplets: A New Paradigm in Product Reliability
Our approach leverages a three-tiered methodology, using inspection data to drive improvements in product design and manufacturing. The digital triplet extends beyond mere simulation by continuously refining the digital twin with real-world data obtained through ongoing inspections.
Digital twins allow for the simulation of a part’s performance under various conditions throughout its design and lifecycle. For instance, an aircraft can be digitally simulated to assess the impact of a bird strike on its ability to land safely. A digital triplet enhances this simulation by incorporating real-world data from industrial inspections, such as actual defects and material properties. This additional layer of information significantly improves the accuracy of predictions, ultimately leading to greater safety and reliability.
Industrial Inspections and the Future of Product Development
Industrial inspections thus become more than a tool for defect detection; they drive a new paradigm by integrating the digital twin with real-world conditions. This connection not only provides deeper insights into the actual state of an asset but also allows for substantial optimizations in manufacturing processes, design, and overall performance.
The concept of the digital triplet enables a multi-generational improvement strategy for parts and processes, moving from mere defect detection to the potential for complete defect elimination. By incorporating inspection data into digital twins, we pave the way for smarter manufacturing and more resilient product designs.
The Journey from Defect Detection to Defect Prevention
Digital triplets represent a critical advancement in using inspections not only to identify defects but also to enhance manufacturing and product performance. Ultimately, the goal is to reach a point where inspections are no longer necessary because defects are entirely prevented. This evolution marks the path from detecting defects to avoiding them altogether—a journey that will redefine quality assurance in the years to come.