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An overwhelming amount of inspection data is gathered across the lifetime of an industrial asset. From the research and development phase, through testing and production, to operations and repairs, it is both required by regulators and essential for managing product development, quality and production processes.

But ask any plant manager whether the industrial inspection data they gather can be used by the engineers in a meaningful way, and they might shrug. “Until now there hasn’t been a tool to easily gather and analyze this vast array of data in one place,” says Arungalai Anbarasu, CTO at Waygate Technologies, a leading non-destructive testing (NDT) solutions provider that serves major companies across demanding industries like automotive, aerospace, electronics, or energy. “But with InspectionWorks we’ve developed an agnostic data management platform to connect the entire inspection history of an asset throughout its lifecycle and deliver meaningful insights for innovation

In the past, industrial inspection data would have been gathered and stored in a fragmented fashion, with little supplier integration and disconnected results. This has led to inspections being seen as a costly investment with little opportunity to extract value. To solve this massive conundrum, InspectionWorks has taken an approach that sums it up in three words: acquire, analyze and act. Each step along the way, the data is used to create a digital twin of an asset that serves to optimize processes, maximize uptime, predict failures, and ultimately improve product design.

Moreover, it is possible to add a third layer to the digital twin with real data from inspections. This is the information about the actual defects and material properties of the part. It gives a real overview of the current condition of the part or the different defects the part has gone through. This can be used to make even more accurate predictions about the condition of a part and its safety.

Adding inspection data to existing parts and process data in digital triplets enables various value-added optimizations such as improved manufacturing processes, new process optimizations and new design optimizations. By activating such a digital triplet, it becomes possible to create a cross-generational improvement plan for all parts and processes, ranging from the detection of defects to their complete elimination.

By providing this framework, InspectionWorks turns your data into a tool for faster and better decisions, ultimately saving costs and enabling a more competitive product,” says Anbarasu, adding that one European airline maintenance operation has already saved some $50 million since it began using the platform. This completely changes the game when it comes to inspections. Instead of just being a costly necessity, they now provide valuable insights that not only detect defects, but actively provide the information required to avoid them in the first place.”

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The InspectionWorks software suite enhances every phase of an asset’s lifecycle. Source: Waygate Technologies

How it works

Say a company has an asset such as a vehicle. The first step of creating an NDT digital twin is to acquire valuable inspection data during its manufacture. From raw material, to supply components and factory assembly – InspectionWorks can catalogue and integrate results with existing data for a comprehensive picture of the asset. With several modules available for different requirements and applications, large data volumes can be seamlessly and accurately collected, stored and managed in the cloud with the platform’s latest digital tool, InspectionWorks Archive. Compatible with all industry standards, it can safely catalogue up to two billion images. This makes it possible to revisit results from years ago with just a part number.

Taking things a step further, InspectionWorks Insight provides a data management framework. It connects results from multiple sources to the asset model in a centralized pool where technicians can develop guided workflows and create customized and automatic reports. So an inspection of a spot-weld or an injection-molded component on our hypothetical vehicle could be conducted by following a menu-guided process to capture the necessary. Then the results are automatically transferred to the platform. If required, an automatic report of the inspection sequence can be produced.

Once the data has been acquired, the asset and its production process can be analyzed using advanced techniques like artificial intelligence (AI) and machine learning (ML). Using the InspectionWorks Analyze module, the safety-critical parts of the asset can be measured and automatically checked to ensure that they are within tolerances.

The Analyze components of the platform provide contextual data management through a single, integrated interface,” says Anbarasu, adding that AI and ML offer manufacturers the option to go even deeper, optimizing and deriving enriched data, or combining multiple inspections and applying them to the same part, or even across several parts.

Once the NDT data lake for the asset has been established and analyzed, InspectionWorks enables the creation of innovative solutions. The result is more informed actions such as process improvement, component redesign, and the ability to predict failures in the field as routine inspection data continues to be collected.

This cycle of taking data from the source to the cloud, and back again enhances the evolution of a product and represents multi-generational value for our customers,” says Nicola Jannis, CEO at Waygate Technologies. “With this we have elevated industrial inspection from a mere means of maintaining quality standards to the basis of a whole new universe of innovation opportunities – from product design, to operations, and all the way down the value chain.”