786 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 ME BACK TO BASICS w purpose and pursuit of nde 4.0 On the same timeline, in 2013 an international community of experts from 45 nations embarked on developing standards for innovation management with a keen acknowledgment of this revolution. A signifi- cant milestone was recently achieved with the publica- tion of ISO 56002 (ISO 2019), which provides guidance for the establishment, implementation, maintenance, and continual improvement of an inno- vation management system for use in all established organizations. Although this ISO standard does not explicitly call out the fourth industrial revolution as the driving force, it has been written to help any organiza- tion work through a rapidly changing business context. It has the strength to enable companies to success- fully pursue a purposeful NDE 4.0. Quick Recap of NDE Revolutions If we look at the evolution of NDE in terms of the recognized industrial revolutions, NDE 1.0 is consid- ered inspection based on human senses (visual, hearing, touch, smell) with some schedule and evalua- tion criterion. NDE 2.0 started when analog instru- ments and methods began to provide amplification and even the ability to look beyond the line of sight. NDE 3.0 was marked by the advent of digital technolo- gies for signal processing and visualization. In this article, we have aligned these with themes behind industrial revolutions, although exact changeover cannot be as precisely identified as the application of steam power (Industry 1.0), electricity (Industry 2.0), and computers (Industry 3.0). NDE 4.0 can be defined as a cyber-physical NDE system—a confluence of Industry 4.0 technologies with traditional physical NDE methods. Within the context of the physical–digital–physical loop of NDE 4.0, we have seen digital technologies and physical methods continuing to evolve, mostly independently and sometimes interdependently. The real power is in the concurrent design of inspection systems through an appreciation of digital twins, with the ability to capture and leverage data directly from the materials and manufacturing process to usage and in-service maintenance, across multiple assets, to optimize prescriptive maintenance, repairs, and overhauls over the lifetime of an asset, and even feed the big data back to the original equipment manufacturer (OEM) for design improvements. The four design principles of Industry 4.0 (Hermann et al. 2016) have been interpreted for NDE application as (Singh 2019): l Interoperability: the ability of instruments, sensors, devices, inspection equipment, and people to connect and communicate with one another via the Internet of Things (IoT). l Information transparency: the ability of information systems to create a virtual or augmented reality (VR/AR) of physical anomalies by enriching digital artifact models with sensor data. l Technical assistance: (1) artificial intelligence (AI) capability to support humans by aggregating and visualizing information comprehensively for making informed decisions and (2) robotics using cyber- physical systems to support inspectors with tasks that are unpleasant, exhausting, or unsafe. l Decentralized decisions: the ability of automated cyber-physical systems to make decisions on their own and perform tasks independently. Only in the case of exceptions, interferences, or conflicting goals are tasks delegated to a higher-level inspector. Currently, the depot maintenance of an aircraft involves a predetermined schedule for maintenance, repair, and overhaul of an asset with parts repaired or replaced based on manual inspections, stored in inventory, guided by written instructions, judgments made by a team of skilled personnel, and data captured electronically in a knowledge base for offline analytics. A depot maintenance scenario of the future as projected by Deloitte (Vitale et al. 2018) presents some very interesting opportunities. Imagine that the depot begins “all and only” necessary activities before the asset arrives: AR guides the crew’s activities on the asset upon arrival advanced scheduling orches- trates acquisition of spares/repairs intelligent workflow optimizes the downtime components are NDE 4.0 can be defined as a cyber-physical NDE system–a conf luence of Industry 4.0 technologies with traditional NDE methods.

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 787 tagged with real-time performance data robots begin performing inspections with better probability of detection (POD) AI looks at the correlations to data from other assets and creates prescriptive analytics 3D printing (additive manufacturing) is brought in to help with missing spares and special tools and soon the asset is all set to go back to service—safer, faster, and cheaper. All of these technologies work like an orchestra serving the purpose. The connectivity providing speed, economic benefits, and enhanced safety is what differentiates NDE 4.0 from our current state of the art. System-level integration has the potential of becoming a platform, where applications can evolve to rapidly and continu- ously make inspection more reliable. Not necessarily direct, but think about how a smartphone—with the integration of Wi-Fi, mobile data, a processor, memory, GPS, a camera, an HD display, and a couple of other sensors—has completely changed the world within 10 years in ways that were not originally conceived. Did you ever think that phone could be a compass, plus a stud finder, gauss meter, sound Db meter, and light meter, all in one? Such is the exponential power of digital-physical integration. There is so much to emerge that I can’t predict most of it. And whatever I can, might be wrong. And that is where having a purpose and process to pursue becomes highly relevant. The Purpose: Safety 5.0 Assuring safety is the number-one motivation behind inspection and maintenance. Everybody wants the system to function reliably, whether it is an air, water, or ground transportation vehicle, a material or energy manufacturing plant, a bridge or building, or an appliance or piece of equipment. Everyone wants safety for all the customers, users, stakeholders, operators, and construction and maintenance crews, as well as for the inspectors. This is why we engage in the business of NDE. To begin with, most digital systems offer a clear advantage over traditional systems in terms of accuracy and speed. However, a significant contribu- tion of a cyber-physical NDE system (NDE 4.0) stems from better control over human factors. This leads to a more reliable inspection system with more consistent POD from inspection to inspection (see Figure 1). This improved and dependable POD provides enhanced safety and enables the optimization of inspection programs, reducing the lifetime operating cost of an asset. The structured management of lifetime digital data, like a digital twin, opens up an additional economic opportunity to asset manufacturers and operators. Key questions we must ask include: l What safety issues can NDE 4.0 address or create? l How far and broad should we go with safety and economic impact? l How many ways are there to deliver business value through fleet-wide lifetime data synthesis and digital-physical integration? The possibilities for cyber-physical confluence using various sensory systems provide numerous opportunities (Vitale et al. 2018). Let’s dig deeper into the application of NDE 4.0 technologies to both enhance safety and bring economic value to stake- holders, with an underlying emphasis that the two need not be mutually exclusive. l Robotics and automation improve safety through dependable POD by virtue of reducing human factors and increasing precise execution. In addition, robots can protect the inspector from risks associated with confined spaces and hazardous areas. l AR improves visualization of anomalies, leading to faster and more reliable interpretation provides step-by-step instructions digitally layered over the physical asset to inform maintenance processes and provides a possibility to engage OEMs and experts remotely. l AI has the potential to significantly reduce false calls through data correlations and increase the accuracy of diagnoses, conduct root cause analysis of asset failures, enable continuous improvement in physical processes and automation, and more that we cannot comprehend today. AI ability in prescriptive and predictive maintenance is expected to be superior to human judgement. Industry 4.0 potential (robotics, AR, AI) Intrinsic capability System reliability Anomaly size 100% Figure 1. Industry 4.0 technologies have the potential to move system reliability closer to intrinsic capability, and even go beyond, making the POD curve rise up steeply toward the 100% mark. Probability of detection