Safety is paramount in industrial workplaces. The Internet of Things (IoT) can serve that goal in many ways, from real-time hazard detection to providing data for ongoing optimization. Non-destructive testing (NDT) is a less obvious but highly beneficial use case in this area.
As its name implies, NDT involves testing materials or products without destroying them. While it’s most well-known as a quality assurance measure, it also has several important safety benefits.
How NDT Improves Industrial Safety
All material and product testing methods are crucial for the safety of a product’s end users. Without testing, manufacturers cannot guarantee that something will withstand expected stresses. These flaws can make contact with objects and equipment — the third leading cause of workplace fatalities — more likely.
Since NDT allows early detection of material flaws, it helps businesses prevent larger hazards before they arise. It’s important to realize that this testing can apply to more than just a company’s products. Using NDT to monitor workplace equipment can inform proactive maintenance schedules to prevent hazardous breakdowns.
NDT is also safer than destructive testing, partly because it can apply to a wider range of scenarios. The only real way to test mission-critical equipment is through NDT testing, as breaking a machine to inspect it would be counterproductive. NDT also removes hazards associated with material destruction, like exposure to dangerous chemicals or flying debris.
Not destroying materials in testing also streamlines the process, which has unique safety benefits. Less downtime means reduced workloads, helping prevent the human errors that almost all safety incidents involve.
How IoT Advances NDT
NDT predates IoT by decades, but the two have quickly become synonymous in many applications. Using IoT to improve NDT can take its safety benefits further in several ways.
Streamlining NDT Processes
First, IoT solutions make NDT an even more efficient process. All NDT is faster than destructive testing because it typically requires less setup and removes the need to remove the broken material. However, collecting the necessary data can still take time — that is, without IoT.
Manually reading and recording test results takes time, especially in the context of a high-throughput facility over an entire year. Manual data entry also has an average error rate of around 1 percent, which can lead to 4,000 faulty calibrations a year in a typical production operation.
IoT devices, by contrast, record and report NDT data in real-time. Automating the data-recording process also eliminates human mistakes. Consequently, NDT is more reliable and takes less time. That efficiency can further reduce process errors or help justify NDT to time-conscious manufacturers.
Powering Predictive Maintenance
IoT technology also enables predictive maintenance. Real-time NDT data can reveal underlying trends in machinery that suggest when it may need repair. Organizations can then service their equipment long before it experiences hazardous breakdowns.
Conventional NDT methods can only reveal a product’s current condition. IoT functionality changes that by continuously monitoring these factors. As a result, operators can see changes in this data that imply larger trends businesses can use to predict future maintenance needs.
This use case can also mitigate the costs of implementing expensive IoT solutions. While IoT equipment can be costly, NDT keeps production costs low by reducing material waste and downtime. Those cost reductions leave more room in the budget for new technology, making these safety benefits more accessible to smaller manufacturers.
Enabling AI Analysis
Applying IoT to NDT paves the way for another game-changing technology — artificial intelligence (AI). While AI analysis is possible without IoT-driven NDT, implementing IoT first can make it easier to use this technology to its full potential.
AI can take NDT to new heights by drawing faster, more accurate conclusions from test results or simulating real-world scenarios for more informed testing. However, 71 percent of organizations today struggle to get all the data required for these models to be reliable. IoT devices provide that data.
IoT devices collect more data across a wider range of NDT factors, laying the groundwork for accurate AI analysis. Businesses can then use AI to remove human errors and further streamline their testing workflows. When this testing is more efficient and reliable, it will result in fewer safety incidents.
Predicting Future Performance
Similarly, IoT data enables predictive NDT. With enough data on a material and how products behave in the real world, companies can test an object’s real-world performance, not just ensure its current conditions meet standards.
While conventional NDT can indicate a product’s future reliability, its predictive capabilities are limited. All predictions would be based on general correlation, not necessarily cause-and-effect relationships, and they may miss how downstream processing may change certain qualities. IoT devices can provide enough data to fuel predictive analytics models to make more reliable predictions.
Some experiments have found that machine learning can achieve 98 percent accuracy in predicting product quality. As manufacturers gather more data through IoT, these predictions can become even more reliable. NDT can extend further into the future as a result, taking quality assurance to unprecedented levels.
IoT-Driven NDT Is the Future of Industrial Safety
Industrial safety is a complex subject. While NDT may not be the only part of building a less hazardous workplace or designing safer products, it is an important step. IoT connectivity takes these benefits further.
As more organizations embrace IoT, NDT standards will rise. As a result, the industry as a whole will become safer and more reliable.
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