The Rise of NDE 4.0 and Challenges

“Quality in manufacturing isn’t a coincidence. It’s a carefully engineered outcome—one that depends on three critical elements: the person behind the process, their skills and certifications, and the technology they use. Take any one of these away, and quality collapses. But when these three elements align, quality isn’t just a checkbox—it becomes India’s competitive advantage.”

As India accelerates towards becoming the third-largest manufacturing output nation by 2030, quality assurance systems must evolve to match the scale, complexity, and criticality of emerging industrial operations. The role of Non-Destructive Evaluation (NDE) is becoming more central—not just in post-manufacturing inspection but in ensuring trust, repeatability, and operational uptime across the asset lifecycle.

The transition from production by computer-controlled and isolated machines to smart factory systems for dynamic workflow adaptations brought to the world the fourth industrial revolution, Industry 4.0. So, What is NDE 4.0? 

Vrana and Singh, in ‘The NDE 4.0: Key Challenges, Use Cases, and Adaption’ (2020), conducted a survey during the ASNT annual conference 2019 whose responses generalized NDE 4.0 to the future of NDE – the next generation of NDE leading with data, automation and digitization. New trends comprising the deployment of cyber-physical systems, smart robots, artificial intelligence, augmented reality, and digital twins that enhance NDE inspections to a new level of performance in quality and safety assurance as well as aim to introduce NDE in Industry 4.0 or cyber-controlled production of high-reliability components by utilising the results of NDE to improve the design, the product, and the production by statistical analysis of the NDE data are together summarised as NDE 4.0.This shift toward NDE 4.0—a digital, data-rich paradigm for inspection and quality control—requires industry stakeholders to re-examine traditional practices in procurement, inspection execution, reporting, and personnel certification. 

This article aims to explore the operational challenges, technological inflection points, and pathways for digital transformation in the NDE landscape.

Quality: Beyond Compliance to Trust

In high-risk industries, inspection is not merely a checklist activity—it’s a gateway to structural integrity, workforce safety, and public confidence. However, the outcome of an inspection depends on three highly interdependent factors:

• The Inspector – Skill, certification, and field experience.
• The Data Collection Process – Repeatability, completeness, and traceability.
• The Tools & Equipment – Calibration, capability, and adaptability to varied materials and geometries.

Reliability of inspection consists of the reliability of the method chosen mixed with the human factors. And the proper determination of the reliability of Probability of Detection and of Intersection over Union will get even more crucial once NDE data is utilised for Industry 4.0 data processing, implying that each of the above-identified pillars (factors), if inconsistent, can compromise reliability.

Evolving Skills and Expectations in the NDE Workforce

As inspection needs scale, asset owners demand zero-defect reliability and 100% operational availability — expectations that the legacy NDE systems struggle to deliver due to fragmentation and analogue reporting.

In terms of skills and competencies, learning in the 4th revolution is an order of magnitude larger compared to previously, where both employers and employees need to take the learning and development process as a shared and continual investment. Operators will require training on emerging technology, whereas the managers need to get up to speed on processes while the executives explore new business models. 

Building a Future-Ready, Trust-Centric NDE Ecosystem

India’s manufacturing ecosystem is witnessing a dramatic expansion, driven by MSMEs, fabrication vendors, and speciality equipment producers catering to thermal plants, pressure vessels, and critical casting operations. To date, the MSME sector of India accounts for 36.2% of India's manufacturing output and 43.6% of exports (2022). 

India’s path to industrial leadership hinges not just on scale but on the quality assurance processes that underpin that growth. The NDE industry must shift from fragmented, reactive operations to digitally integrated, intelligence-driven ecosystems. While digitalization is not a panacea, it is a necessary enabler of transparency, traceability, and trust. The journey to NDE 4.0 will be iterative—but it must begin with a commitment to data integrity, human-centered digital tools, and industry-wide collaboration because it represents a transformative leap in the field of non-destructive evaluation.

The convergence of cyber-physical systems, data analytics, and stakeholder-centric design redefines safety and economic value—coined Safety 5.0. By advancing from descriptive to cognitive analytics, NDE 4.0 enables prescriptive, asset-customised maintenance strategies. This shift emphasises enhancing inspection accuracy as well as the creation of long-term value by embedding intelligence into decision-making. To achieve this, organisations must chart a tailored roadmap aligned with market dynamics and talent development, following a structured innovation process from ideation to monetisation. By implementing systems like ISO 56002 for innovation management, companies can navigate the complexity of adapting emerging technologies sustainably and strategically.

Innovation here is not a linear path but a multilayer filter—where ideas evolve, fail fast, and pivot based on user needs and value propositions. Key stakeholders such as inspectors and asset owners demand solutions that reduce operational friction while improving reliability. Thus, purposeful qualification, creative execution, and upskilling of the workforce are critical. 

With global collaboration and seamless integration across technologies and vendors, NDE 4.0 will open the door to a data-driven market—one where trust, transparency, and innovation will define competitiveness and safety assurance.

Can Digitalisation Solve NDE’s Core Bottlenecks?

The advent of NDE 4.0 technologies such as AI/ML-assisted data acquisition, remote inspection bots, and predictive maintenance analytics—brings new possibilities. However, implementation faces roadblocks, particularly in small and mid-sized enterprises (SMEs) such as :

• High capital costs for acquisition of inspection robots, digital radiography systems, and advanced UT arrays.
• Ambiguous ROI on digital transformation with the absence of regulatory mandates and/or financial incentives.
• Absence of requisite data infrastructure to store, analyse, and trace inspection data over an asset’s life cycle.

In this context, a valid question emerges: What trade-offs can Indian SMEs make to embrace NDE 4.0 without financial overreach?

Let’s find out some answers and I will be coming back with my Research in future editions wearing a hat of NDE 4.O Researcher!

References:

• Vrana, J., & Singh, R. (2020). The NDE 4.0: Key Challenges, Use Cases, and Adaption. https://www.researchgate.net/profile/Johannes-Vrana/publication/339997962_The_NDE_40_Key_Challenges_Use_Cases_and_Adaption/links/5e71e0f692851c93e0aa4f35/The-NDE-40-Key-Challenges-Use-Cases-and-Adaption.pdf 
• Meyendorf, N., Ida, N., Singh, R., & Vrana, J. (2023). NDE 4.0: Progress, promise, and its role to industry 4.0. NDT & E International, 140, 102957. https://doi.org/10.1016/j.ndteint.2023.102957 
• ICNDT SIG: NDT Reliability. (n.d.). ICNDT SIG: NDT Reliability. https://www.icndt.org/ICNDT-Activities/NDE-4.0.html 
• Role of MSME sector in the country. (n.d.). https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1946375 
• C. Miller. (2007). Nondestructive Evaluation: A Review of NDE Performance Demonstrations—NDE Round Robin Report. In Electric Power Research Institute. https://restservice.epri.com/publicdownload/000000000001016969/0/Product 
• Pacific Northwest National Laboratory. (2020). Nondestructive Examination (NDE) Training and Qualifications: Implications of Research on Human Learning and Memory, Instruction and Expertise (PNNL-29761). United States Nuclear Regulatory Commission. https://www.nrc.gov/docs/ML2007/ML20079E343.pdf 

Author: Srijan Tiwari