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NDE 4.0 Ethics Panel – Roundtable Discussion with NDE 4.0 Influencers | Episode 11

– Ripi Singh, Tracie Clifford, Matt Litschewski

In this episode of the NDE 4.0 Podcast, we have an exciting new panel format in which we chat with NDE 4.0 influencers and leaders and discuss the future and what an NDE 4.0 Ethics Code would look like. In this discussion, hear from three experts who are leading the way in NDE 4.0 innovation, education, and coaching.

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Can Industry 4.0 Bring 6th Sense to Inspection Activity?

Oh Really?

Human ability to see when something is failing has become better through non-destructive evaluation methods. It has evolved from highlighting surface to looking inside and now getting to point, where data analytics from diverse sources could provide a digital indication of damage that is yet to appear on the physical structure, kind of a sixth sense!

Can Industry 4.0 Bring 6th Sense to Inspection Activity

The Revolutions in Non-destructive Evaluation (NDE)

For centuries humans have taken care of their safety using the five basic senses – touch, sight, hearing, smell, and taste. The revolutions in manufacturing, infrastructure, and transportation systems came with unfortunate incidents and fatal accidents. The engineering community rose to the challenge of quality, safety, and reliability through non-destructive inspections. This important domain serving so many industries, has also seen its share of revolutions, aligned with the changing needs of the industrial revolutions, and enabled by similar suite of technologies.

The first inspection revolution was around highlighting the surface for human organic sensory perceptions. Tools such as lenses, colors or stethoscopes improved the detection capabilities of naked eye and human ear. Procedures made the outcome of the inspection comparable over time.

The second revolution in NDE used physical understanding of material response to electromagnetic or acoustic waves, which lie outside the range of human perception, into signals that can be interpreted by humans. This resulted in a “look inside” into the components or a better visualization of material inhomogeneities behind or close to the surface. For example – X-ray, gamma testing, ultrasonic, Infrared and terahertz detection, eddy current, etc.

The third revolution in NDE came along with computers and digitalization that simplified imaging and analysis of signals, such as X‑ray detectors, digital ultrasonic and eddy current equipment, and digital cameras. Robotics automated the processes, making them convenient, fast, and repeatable. The digital technologies offered another leap in managing inspection workflow data from acquisition, storage, processing, 2D and 3D imaging, interpretation, to communication. Data processing and sharing became the norm, and data security and integrity came in as a new challenge.

The fourth revolution in NDE (now) integrates the digital techniques (from the third) and physical methods of interrogating materials (from the second) in a closed loop manner transforming human intervention and enhancing inspection performance. Within the context of the physical-digital-physical loop of NDE 4.0; digital technologies and physical methods may continue to evolve independently, interdependently, or concurrently. The real value is in concurrent design of an inspection through application of Digital Twins and Digital Threads. This provides the ability to capture and leverage data right from materials and manufacturing processes to usage and in-service maintenance. The data captured across multiple assets, can be used to optimize predictive and prescriptive maintenance, repairs, and overhauls over the lifetime of an asset. The relevant data can be fed back to OEM for design improvements. NDE 4.0 also serves the emerging trends in custom manufacturing. Remote NDE can keep the inspector away from harm’s way and integration by “tele-presence” can bring additional specialists in the decision process from anywhere in the world quickly and affordably.

The role of human is changing from ‘human-in-the-loop’ to ‘human-on-the-loop’ from ‘human-outside-the-loop.’

Game Changer – Intelligent Inspection System

The continuous improvement in inspection capability is driven by the need and desire to pick smaller and smaller damage or material discontinuity (Crack, corrosion, delamination, foreign object inclusions) with higher and higher likelihood. It is called probability of detection (POD), typically characterized by an S-shaped curve. Just like with naked eye, we all have slightly different probability of seeing small stuff on the floor. Most of the time a small shiny spec on the kitchen tile floor could go unnoticed, however it is different, if you knew that your child broke a glass yesterday.  You will likely scan a larger area looking for more such pieces. That is the power of knowledge, experience, and intelligence.

The Industry 4.0 can bring the ability to synthesis all of the data right from manufacturing, usage, environment, (digital history acting like a lifelong blackbox) and combine it with data from detected damage in other older assets (experience), the intelligent inspection system could predict with a certain probability that there is a discontinuity hiding here smaller than equipment’s ability to detect.

We have seen such capability in many domains. Ten years ago, Target store figured out a teen girl was pregnant before her father did (Forbes Feb 16, 2012). Amazon regularly ships products to the distribution centers nearest to your house based on your shopping patterns to cut down delivery time. Law enforcement agencies can thwart threats from social media chatter. That is the power of the data and intelligence augmentation.

The probability of detection by cyber-physical system using digitalized history can get better than intrinsic capability of the physical equipment, in a sense the 6th sense of the machine. Machine can predict with certain confidence that there is a signal here hidden in the noise, from an anomaly that will be detectable sometime in the near future. 

Discontinuity Size

In Summary,

The NDE 2.0 changed the game providing inspectors with equipment to see hidden damage using physical waves.

The NDE 4.0 could change the game again by augmenting an inspector with an intelligent system to foresee a damage on the digital twin before the inspection equipment can pick it up on physical structure.

If you like this blog post, you will like our upcoming book “Welcome to the World of NDE 4.0” DM me or Johannes Vrana and we can alert you when it is available on Amazon.

For a dedicated session for your company, please reach out to Ripi Singh directly.

Has anyone ever built muscles by taking a tour of the gym?

Really?

Bringing innovation into an organization culture is like building a mental muscle. You cannot learn it online or through watching panel discussions amongst thought leaders. It requires sustained effort for long period of time, and painful learning.

Has anyone ever built muscles by taking a tour of the gym

Basic Physics behind an Organizational Behavior

Organizations seem to follow some basic principles of physics. For example

  • Friction: Opposing force resisting relative motion.
  • Inertia: Tendency to do nothing or to remain unchanged.
  • Gravity: Left to themselves, unsupported objects will fall to the ground.
  • Energy: The capacity for doing work.
  • Momentum: Impetus gained by a moving object.

When an individual or a team tries to get innovative, to change a process or product, essentially trying to move it from its current state to a different state; it encounters both friction and inertia. The team has to put in a lot of energy to get it moving, and to build and sustain the momentum.

Overcoming Inertia and Friction

Organizations have inertia and internal friction that will hold them back from a successful positive transition. But, if you can build momentum through proper infusion of energy, you can make a lasting enterprise-wide change.

Start by sending the right message to the 13% early adaptors, and they will join the 3% innovators already working in that direction. The 34% of early majority will need some kind of objective and training to follow through. The 34% late majority would need incentives and tangible rewards in addition to the objectives and capability training. Never mind the last 16% laggards and CAVE people, they will find a different role.

Building Momentum

In Volume-3, we discussed 4 tracks of activities to build an innovation profile. Consistent execution will help build the momentum.  Leadership needs to think of the following steps as a wheel

  1. Be clear about the Innovation Purpose, and the vision of success.
  2. Create, communicate, and use the two sheets of music, the Innovation Strategy (Roadmap), and the Dashboard to track the progress.
  3. Build the Innovation Capital, by investing in talent and knowhow.
  4. Inspire talent to engage in Innovation Activity to realize the roadmap.
  5. Keep Innovation Lean by aligning people, products, and markets.
  6. Recognize and reward teams for performance and learnings.
  7. Update the roadmap and dashboard annually and go back to step 2.

Keeprotating this flywheel and build a momentum that would be hard to stop. Purpose, strategy, and rewards provide the willingness to innovate. Capital and activities build the capability. Lean reduces internal friction. Collectively, they build the culture of innovation, over a few years. It is a mental muscle.

Just like a few workout sessions at the local gym won’t build your body muscle, a few successful projects won’t build the mental muscle of your organization. You will have to go through many projects, over the years, and slowly change the basic behavior. I get into conversations with senior leaders who think that a 2-day workshop on ideation or innovation is all they need, and after that, it will happen on its own. A 2-day workshop is just like taking a tour of the gym.

Lesson from the Coronavirus Pandemic

In March 2020, within 2 weeks, America went from business as usual to a complete stop, except essential services. The markets were shutdown, social distancing put in force, almost everyone working from home, no more parties, weddings postponed, no access to beaches, bars, or nightlife. The level of change that would normally take a decade was visible in a blink of an eye. Situation updates and restrictions were being brought into the workforce by the hour. What was at stake? Life. No one asked you to think or act Out of the Box. Your box was just crushed by the tiniest invisible life form, leaving everyone scrambling to find a new box to think in. Innovation was seen all across from primary life-saving equipment, to communication, to support structure. Innovation was not a struggle at all. Organizational leadership was open to all sorts of ideas to keep their employees safe and the business afloat. They were willing to quick test, follow any successful option, and learn.

Where did that innovation muscle strength came from? Life saving rush of Adrenaline!

In Summary,

There are many reasons, excuses, and myths about why innovation does not succeed. I concur with Bill Fischer that it never gets started or supported by leadership even if it starts. The primary struggle is a leadership mindset, which slowly erodes employee morale to innovate. In some sense companies have successfully managed to promote productivity performers to the leadership roles, putting innovators and innovation on the back seat. Will the pandemic change that? Will it mark the start of an innovator’s era with a very different form of struggle, the struggle to let innovators lead, for a while.

If you like this blog post, you will like my book series “Inspiring Next Innovation ….” available on Amazon and summarized in these book launch webinars on YouTube.

For Leaders –

Inspiring Next Innovation Purpose,

Available on Amazon Watch on YouTube                               

For Innovators –

Inspiring Next Innovation Value Chain,

Available on Amazon Watch on YouTube  

For Managers –

Inspiring Next Innovation Framework,

Available on Amazon Watch on YouTube     

For Leaders –

Inspiring Next Innovation Mindset,

Available on Amazon Watch on YouTube

To engage with the author – please register for upcoming virtual sessions.

Ethics and NDE 4.0

Ripi Singh & Tracie Clifford

Sound of an Alarm

There are too many unknowns around explosive growth of Industry 4.0 technology applications, that it needs a hard conversation around ethics. The situation is particularly alarming as decision making shifts from humans to autonomous machines that can learn action but incapable of fear of penalty.

One of the aspects of any revolution is that innovation happens faster than laws and regulations needed to keep the business drivers in check, and particularly where there is no precedence to provide initial guidance. The graphic below depicts that dangerous zone, where on one is looking for general public.

Ethics and NDE 4.0

What is Ethics?

The field of ethics[1] (or moral philosophy) involves systematizing, defending, and recommending concepts of right and wrong behavior. Philosophers today usually divide ethical theories into three general subject areas: metaethics, normative ethics, and applied ethics.

Metaethics focus on the issues of universal truths, the will of God, the role of reason in ethical judgments, and the meaning of ethical terms themselves.

Normative ethics involve articulating the good habits that we should acquire, the duties that we should follow, or the consequences of our behavior on others.

Applied ethics involves examining specific controversial issues, such as abortion, infanticide, animal rights, environmental concerns, homosexuality, capital punishment, or nuclear war.

The topic of NDE 4.0 relates closely to Normative Ethics.

Proposed Ethical Principles for AI in NDE 4.0

The U.S. Department of Defense officially adopted a series of ethical principles[2] for the use of Artificial Intelligence on Feb 24, 2020 following recommendations provided to Secretary of Defense Dr. Mark T. Esper by the Defense Innovation Board in October 2019. These principles encompass five major areas: Responsibility, Equity, Traceability, Reliability, and Governance. Those recommendations came after 15 months of consultation with leading AI experts in commercial industry, government, academia and the American public that resulted in a rigorous process of feedback and analysis among the nation’s leading AI experts with multiple venues for public input and comment. We can adopt those to the NDE sector.

The adoption of AI ethical principles should align with the organizations growth, NDE digitalization strategy, and the lawful use of AI systems in host state/country. The adoption of AI ethical principles will enhance the organization’s commitment to upholding the highest ethical standards, while embracing the strong history of applying rigorous testing and validation of inspection technology innovations and methods. The proposed AI ethical principles should build on existing ethics framework in use within the organization and longstanding norms and values.

While the existing ethical frameworks provide a technology-neutral and enduring foundation for ethical behavior, the use of AI raises new ethical ambiguities and risks. These principles address these new challenges and ensure the responsible use of AI by the organization.

These principles will apply to both inspection and non-inspection functions and assist the organization in upholding legal, ethical and policy commitments in the field of AI.

The AI ethical principles encompass five major areas adopted from DoD and sixth one data specific to NDE data here:

Responsibility. NDE personnel will exercise appropriate levels of judgment and care, while remaining responsible for the development, deployment, and use of AI in NDE capabilities. [Notes: such as ASNT Level 3 is responsible for requirements, validation, and training, whereas a Level 2 can deploy it on qualified techniques]

Equity: The digital inspection system developers will take deliberate steps to minimize unintended bias in AI based NDE capabilities. [Notes: This includes development and training data. Training data should come from diverse users and decision makers, as supported by DEI expert. Refer to the section on bias for further details]

Traceability: The AI capabilities will be developed and deployed such that relevant NDE personnel possess an appropriate understanding of the inspection technology, development processes, and operational methods applicable to AI capabilities, including with transparent and auditable NDE methodologies, data sources, inspection procedure and documentation.

Reliability: The AI capabilities will have explicit, well-defined uses, and the safety, security, and effectiveness of such capabilities will be subject to calibration, validation, and POD assessment within those defined uses across their entire life cycles.

Governance: The digital inspection system developers will design and engineer AI capabilities to fulfill their intended functions while possessing the ability to identify and avoid unintended consequences, and the ability to disengage or deactivate deployed systems that demonstrate unintended behavior.

Data Management: The NDE personnel will honor the data acquisition, transfer, storage, analysis, processing, security, and ownership/sharing rights as determined by organizational policy and contractual obligations.

Call for Action

If you are working on autonomous machines with learning capability, please consider ethics seriously. What we have known and practiced up until now may not be adequate.

If you have an opinion on the content presented above, please engage in a conversation and lets us refine it together.

About Tracie Clifford

Tracie is Quality Manager, ANDE-1 Examination Center, Nondestructive Testing and QA/QC Programs, at Chattanooga State. She has over 30 years of experience in quality assurance and is a champion of training and certification programs in USA. She serves ANSI TAG-176 in development of ISO standards on quality terminology, quality systems, and quality technology.

[1] Internet Encyclopedia of Philosophy.

[2] DoD Adopts Ethical Principles for Artificial Intelligence; US DoD – Feb. 24, 2020.