J U L Y 2 0 2 0 • M A T E R I A L S E V A L U A T I O N 799 innovation management systems such as ISO 56000. The inspection of unique components will require well- trained specialists that not only understand the NDE methods and inspection requirements, but also the materials and components to be inspected. The human factor and their related skill sets will need to be developed so as to significantly enhance the relia- bility of NDE results. If a specialist is not locally available, remote NDE can be utilized. “Tele-NDE” has been demonstrated, in a simple form, previously by the authors by using standard telecommunication software and PC-attachable UT instruments (Meyendorf 2017). Increasing bandwidth and 5G networks will potentially better facilitate the telepresence of NDE. This inspection of novel individual parts made using advanced manufacturing will also challenge how NDE is organized. There needs to be a funda- mental change, which can be inspired by the changes already seen in medicine where diagnostics is always geared toward the individual. However, this requires an excellent trained specialist, which is made available by an increasing use of telecommunication or tele-NDE. In Figure 2, this is seen in a concept called the “machine doctor,” who could be an NDE specialist or small team, who has expertise in the materials, design, and loading conditions of the components. This will require capabili- ties and expertise that go beyond those found in a typical Level III. The needed workforce development will be a major challenge. NDE 4.0 will disrupt the skill sets required by Level III inspectors: not only will it require the incorporation of “digital” skills, but also the addition of a much wider multidisciplinary engineering skill set. Use of the New Cyber-Physical Techniques in NDE New smart and remote technologies can impact and improve NDE in several different ways. The Internet of Things (IoT) potentially allows the networking of all machines and products. These networks can include NDE tools. NDE inspection has to be integrated into the manufacturing process for individual custom products. For process planning, designing/optimizing, and assessing inspectability, NDE modeling will be essential in applying digital twins. Modern advanced sensor networks and measure- ment tools create a tremendous amount of data. This could be, for example, the continuous measurement data created by the next generation of structural health monitoring (SHM) systems or the 3D volume data created by X-ray, CT, or PAUT. Cloud computing potentially enables capabilities to safely store, organize, and analyze the various NDE and parts-related data. Smart robots and intelligent self-learning machines could be used to assist inspec- tors and support decisions in ways that go beyond the typical inspector’s skill set. A growing database of NDE data will help to improve the decision-making process, supported by deep learning algorithms. It is important that these NDE data are seen as an “item of value.” Saving NDE, SHM, and operational data, organizing them by creating new NDE databases, and linking the data to CAD data can have significant benefits for the service teams. NDE and SHM data need to be linked and provide data that can be related to standards (Figure 3). Safety margin Change? SHM data: Detection? Location? Size? Discontinuity size Basic safety Critical crack size for unstable Crack size limit for fitness for purpose Acceptance criteria for quality assurance Recording threshold Structural and other noise Versus Figure 3. Schematic showing relationship between crack size and NDT acceptance criteria (adapted from Bond and Meyendorf 2019).

800 M A T E R I A L S E V A L U A T I O N • J U L Y 2 0 2 0 The development of NDE/SHM databases will provide the following benefits for service and quality management teams: l Graphic planning and improved control of project processes, and subsequently a quicker overview of planned activities and results from activities that have been carried out. l CAD linking for equipment data and automatic access to assigned CAD drawings. l Comfortable implementation of inspections with a modular inspection and evaluation system (MIES) and importing of NDE data, such as X-ray radi- ographs, into protocols. l Documentation and archiving of activities and work results. l User-specific access to data and functions with intuitive operation using a graphic user interface. l Quick access combined with a high level of data security. Such a system would include standard software (such as word processing, spreadsheet analysis, and graphics) and enable graphic and statistical presenta- tion of the imported measurement data. An example for such a system is the inspection and revision management system (IRMS). The basic idea is to support all the necessary process steps in connection with inspection and revision metrics at power plants, chemical plants, and other industrial facilities based on a modular design, going beyond process limits. An IRMS approach that was developed approxi- mately 10 years ago is presented in Figure 4. This system integrated all necessary processing steps based on the organizational processing diagram of the documents and data, beginning with the planning of activities to their evaluation, documen- tation, and archiving. In today’s world, the “working box” has sensors and can adapt. Actions can deviate from original plans within an intended plan. Such planning can become very different from current methods—it includes objectives, constraints, and space for flexibility, in addition to defined activi- ties and timelines. An integrated MIES enables the complete integra- tion of all activities—for example, by including the computer-supported processing of ultrasound, eddy current, and visual inspections with videoscopy and endoscopy. Simultaneously, machine parameters and inspection results are directly transferred to the MIES modules. In such an approach, the processing of raw NDE data is supported. An example of this is scanned X-ray images with IQIs compared to measured geometric details. A CAD interface allows the linking of NDE results to CAD. Processed elements are then found in linked CAD documents and highlighted. The CAD documents can be processed online. Including process modeling, for example, along with thermal cycles and solidifica- tion sequences in welding might be a future step in obtaining information of value to make assessments for advanced NDE. An interesting and related tool, which is used for prognostics, is stress analysis. Appropriate analysis and images for stress analysis can be automatically generated for processed elements and then be imported into CAD documents. These concepts for ME FEATURE w nde 4.0: challenges and opportunities Working Documentation Planning Machine Figure 4. Integration of all processes in the inspection and revision management system (IRMS). These ideas are not new, but today advanced computers give us the capability to apply them in near real time and do so cost effectively.