How 1 Amazing AI/ML Strategy Can Propel Aerospace Manufacturing

At what stage would you expect the aviation industry to ensure 100% safety and dependability of every airplane flying out? Not at the tarmac! The assurance must start at the manufacturing level itself. Undoubtedly, it is a mission-critical industry, heavily relying on accurate Quality Gate checks before the aircraft roll out.

The “2022 Aerospace Industry Outlook” published by Deloitte reported the current macroeconomic trends, indicating the demand for small and medium-sized aircraft is growing again. Consequently, aircraft manufacturers need to shift toward digital and operational efficiencies that could accelerate time to market and reduce cycle times. [1]

The Importance of a Scalable and Robust AI/ML Strategy

What company would want to risk losing its competitive thrust? A global leader in the aerospace manufacturing sector was struggling with a terrible lag in its aircraft delivery rate.

Multiple factories were involved in the production of the vehicle structure. The aircraft assembly utilized 100+ workstations to handle 3,000,000+ parts. The final assembly line was also a complex system of a series of workstations designated to complete crucial tasks.

Quality Gates that were established after every few stations to assess the critical parameters detected several internal time and quality perturbations such as the late start of assembly, quality deviations need for reworks, etc. Also, there were external perturbations such as delays in supplier deliverables, crucial deliverables with open work items, etc. An early warning alerts system was also completely missing, which worsened the situation further.

Aside from the lack of visibility on the upstream processes and the pending work in progress (WIP), the failure to pass through quality gate checks affected their output performance.

Consider the enormous impact on business due to such anomalies in the production process!

Yes, AI/ML can give aerospace manufacturing wings!

Our Bodhee® Predictive Quality AI App facilitated integrated data analytics, providing foresight on bottlenecks, predicted success rate at quality gates, and identified failure patterns in critical downstream parameters. Predictive alerts and accurate recommendations for process correction were given by our AI app when the aircraft were only in the initial stages of assembly.

Our revolutionary and much-acclaimed Digital Twin technology enabled the accurate simulation of the entire complex flight engineering and intricate manufacturing processes. The virtual representation of the physical world provided the necessary levels of visibility for precision manufacturing.

The user-friendly and interactive real-time data visualization made the generated production models easily interpretable by production planners. End-to-end visibility of the manufacturing of flight vehicles allows AI-powered data analytics to provide actionable insights, which can minimize the scope for errors in the production line to slip through the Quality Gates.

The advanced ML algorithms utilized the training data and the LIVE production data to provide actionable insights for the operators to make informed timely decisions, which improved process control.

The value derived within just 8-12 weeks of having incorporated our Bodhee® Predictive Quality AI App and ML in their production process proved to be transformative, to say the least. The work closure rate improved by 20%, and there was a commendable quality improvement of 15%. [2]

That was just a high-level retelling of our data-intensive, scalable, and robust AI/ ML technique, which catalyzed the streamlining of their manufacturing, lifting it out of the doldrums!


[1] Deloitte. (2021). 2022 Aerospace and Defense Industry Outlook. Deloitte United States.

[2] Neewee. (n.d.). Case studies Archive – Neewee. Neewee.

Brunton, S. L., Nathan Kutz, J., Manohar, K., Aravkin, A. Y., Morgansen, K., Klemisch, J., Goebel, N., Buttrick, J., Poskin, J., Blom-Schieber, A. W., Hogan, T., & McDonald, D. (2021). Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning. AIAA Journal, 1–26.

Neewee Joins the SAP® PartnerEdge® Program

Bengaluru, India, September 23, 2021

Neewee announced today that it has joined the SAP® PartnerEdge® program as a partner that designs, develops, and builds software. 

“We are happy to announce Neewee is now an SAP partner,” said Harsimrat Bhasin CEO, Neewee. “This is a new milestone in Neewee’s journey and we would like to thank the entire team for this achievement. With Neewee’s leading-edge artificial intelligence apps in industrial analytics, manufacturing companies can improve their quality, efficiency, and productivity by leveraging the power of the internet of things (IoT) and AI.” 

Neewee enables manufacturing companies to see the larger context by collecting, connecting, and analyzing data from every point of the manufacturing process. This helps discover underlying patterns, uncover high-potential opportunities, predict deviations, and prescribe solutions. In turn, this intelligence augments day-to-day operations, empowering analysts, managers, and shop-floor staff to take crucial business decisions in real time. Neewee’s AI apps developed specifically for the manufacturing industry help identify parameters impacting yield, quality, production efficiency, consistency, and cycle times. They provide real-time recommendations and integrate with existing Information Technology/Operational Technology systems and platforms. 

As a partner in the SAP PartnerEdge program, Neewee is empowered to build, market and sell software applications that supplement and build on SAP software and technology. Neewee has its platform agnostic AI apps deployed on SAP Business Technology Platform. The SAP PartnerEdge program provides the enablement tools, benefits and support to facilitate building high-quality, disruptive applications focused on specific business needs – quickly and cost-effectively. The program provides access to all relevant SAP technologies in one simple framework under a single, global contract. 

About Neewee

We here at Neewee believe that a data-filled world needs a data-first approach. Neewee’s proprietary AI applications are optimizing manufacturing operations for leading global companies, and we have offices worldwide. We are driven with the vision of enabling complete digitalization of manufacturing to accelerate industrial transformation and profitable growth. 

Any statements in this release that are not historical facts are forward-looking statements as defined in the U.S. Private Securities Litigation Reform Act of 1995. All forward-looking statements are subject to various risks and uncertainties described in SAP’s filings with the U.S. Securities and Exchange Commission, including its most recent annual report on Form 20-F, that could cause actual results to differ materially from expectations. SAP cautions readers not to place undue reliance on these forward-looking statements which SAP has no obligation to update and which speak only as of their dates. 

SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE in Germany and other countries.
Please see for additional trademark information and notices. All other product and service names mentioned are the trademarks of their respective companies. 

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Understanding the Difference between Digitization, Digitalization, and Digital Transformation.

91% of industry leaders have increased digital transformation investments in the past year,says the newly released 2021 State of Manufacturing Report.

Rising out of the phase of uncertainty brought by the global pandemic-driven shutdowns, the global manufacturing industry is now putting its back into regaining stability. Implementation of Industry 4.0 technologies is not an option for manufacturing companies but imperative to strategize the full recovery of business and achieve greener processes with more agility. The Fourth Industrial Revolution (4IR) leverages the 3 Ds of technology- Digitization, Digitalization, and Digital Transformation. 

Although the word ‘digital’ has been around for a few decades now, constantly advancing technology has changed its meaning dramatically over time. Also, the difference between digitization and digitalization is not clearly understood by many. And how these two terms are essential for digital transformation.

Digitization converts information available in the old analog form by scanning and encoding to store, process, and transmit in a computer-readable format. Essentially, digitization is the acquiring of data in the form of binary numbers to be processed by digital computers. 

In the manufacturing context, digitization of a product involves recreating an image of the physical product with the help of software tools, e.g., a clay model of an object gets designed in 3D CAD file format. The production process also gets digitized by creating a digital twin that mirrors every step in the process, end-to-end. With the help of AI applications, the entire manufacturing process- from product design and workflow of the production line to the finished product gets coded into the machines connected by the Internet of Things. Digitization replaces the paper-based processes even at the shop floor, where physical product design is no longer handed out but transmitted to a device. Thus, digitization is the foundation of digitalization — the latter cannot occur without the former.

The two terms, being closely associated, are often confused. But, scholars emphasize the analytical value in understanding the distinct difference between digitization and digitalization.

Digitalization is less about the specific process of going from analog to digital and more about a strategic and radical change in business operations. Gartner defines digitalization as the use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business. Accepting the overwhelming process of digitizing your traditional manufacturing processes and embracing automation and the Industrial Internet of Things is just one aspect. Digitalization also involves the workforce of your organization. In the wake of automation factory- workers and other employees need to shift from manual processes and adapt by acquiring digital skills relevant to their field of work. 

And thus, we arrive at understanding what digital transformation means. The strategic and considered move of upgrading the old factories to optimize your manufacturing processes by adopting technologies like Artificial Intelligence, Big Data Analytics, Machine Learning, Robotics, etc., is radical business transformation through digitalization. And equally vital to the transformation are the people working in the organization. But, digital transformation initiatives cannot stop at the implementation of digital technologies only. It goes beyond digitalization. For how can we forget that business is people, after all?

Digital transformation (Dx) is primarily a change in mindset that shifts the focus of organizational activities toward satisfying customer expectations, understanding pain points, and solving customer problems. Customer and employee experience is a crucial driver for successful digital transformation, as identified by the MIT Sloan Center for Information Systems Research. And the other driving factor is the operational efficiency of the organization. Embracing digital transformation means being willing to adopt artificial intelligence (AI) and automation to augment and free up workers for performing higher-value tasks. Harnessing technology for enhancing customer experiences while also aiming for a real-time lean manufacturing ecosystem will give massive business benefits —including cost efficiency, improved innovation potential, and the quintessential customer relationship. 

The unexpected advent of the COVID-19 pandemic made health and safety a major priority, which saw the whole world scrambling to cope with the new normal of remote working. And as a consequence, most enterprises converted into digitally functioning businesses for the sake of survival. There was an unprecedented change in human interaction, customer behavior, and people’s attitude toward exploring digital possibilities. There was a drastic paradigm shift, and it has come to stay.

Almost all business sectors have undergone slow but escalating digitalization. And we can surely expect that in the post-pandemic era, digital transformation — accelerated and deliberate — will become inevitable for all areas of manufacturing. If you wish to thrive (not just survive) in the next normal, your manufacturing industry has to turn agile and SMART.