NDEOUTLOOK | SCANNER FROM CONCEPT TO REALITY The concept and implications of NDE 4.0 have been discussed for a couple of years. The importance and relevance of this topic is reflected in industry media and conference programs throughout the world, along with the publication of the first handbook on NDE 4.01 as well as countless papers. There is a plethora of available resources for practitioners to get started. These activities also have led toward industry workgroups and commit- tees tasked with developing the required standards, data structures, and guide- lines, which will enable the next level of implementation across the industry. This can be seen as building the foundations. For many practitioners, all these academic activities might seem far away and practical implications can be hazy. It is said we humans overestimate short-term impact and underestimate long-term impact. This is also the case for the adoption of NDE 4.0. It requires significant changes in technologies, processes, and—most importantly— mindset to implement aspects of NDE 4.0 into production environments. If done right, it can unleash significant competitive advantages for those imple- menting it, while it can result in fatal consequences for those left behind. Many people are familiar with Moore’s law, which states that computing power is doubling regularly2. This law has been proven empirically and is also true for general technology development, inno- vation, and even content generation. The reason is that each technology development is building on the previous round of innovation. Such exponential processes can be treacherous and hard for our brains to grasp. We tend to underestimate the impact of exponential processes until they hit the tipping point, triggering rapid acceleration and irre- versible growth. Those companies that reach this tipping point will be propelled forward, where gains and improvements fuel further innovations that quickly compound on one another. Those left behind struggle to work through the slow-growth early phase of the expo- nential curve, seeing the gap between them and their peers widening rapidly. We all have seen many demonstra- tions of these forces at work. The business-to-consumer (B2C) markets are full of them. You can look at Google, Amazon, and Apple (among others), who have employed new technologies and even business models to transform their industries. The underlying technology drivers are, in many cases, cloud connec- tivity, artificial intelligence (AI), digitaliza- tion, automation, and big data. These are exactly the technologies that make up the technology plethora of NDE 4.0. Right now, we are at the brink of massive adoption of these technologies in business-to-business (B2B) markets and especially the manu- facturing industry. These transformations will lead to similar reorganization in our industrial landscape as we have seen in the consumer world. Therefore, this devel- opment is called the fourth industrial revo- lution. As we know from history, there are winners and losers of revolutions, but one thing is for sure—the world will look signifi- cantly different afterward. As a provider for digitalization and automation equipment, we have seen a surge of inquiries for solutions that are concerned with technologies covered by NDE 4.0. This proves that the next phase is already underway, and we are seeing accelerated adoption throughout the industry. Now that the first wave of digi- tization (meaning moving from analog film to digital X-ray detectors) has been completed in many cases, companies are implementing further automation and process digitalization to leverage the possibilities of these digital tools. Implementation of simple automation and digitalization is already resulting in significant efficiency gains. According to Jan Danielson from Kongsberg Aerospace & Defense, it led to a “90% reduction of working hours”3 for his organization. This frees up capital and capacity that can be allocated to the next innovation cycle, which will in turn also lead to further savings and effi- ciency gains. This could, for example, be the implementation of AI to automat- ically evaluate and interpret images. It has been shown that this could lead to further efficiency gains of roughly 60%4, but it wouldn’t be possible without auto- mating the acquisition process. This is what is called a technology-induced positive feedback loop, which will ensure a long-lasting competitive advantage. In times of rising throughput requirements, A P R I L 2 0 2 2 • M A T E R I A L S E V A L U A T I O N 15