Whitepaper Published: How Nokia uses Computer Vision to transform Quality Management

We are thrilled to announce the publication of our latest whitepaper in collaboration with Nokia, titled “Amplifying Quality Management in Assembly with AI.” This comprehensive document showcases the revolutionary strides we’ve made together in integrating Artificial Intelligence (AI) and computer vision into the manufacturing processes, setting new standards for quality and efficiency in the telecom industry.

Nokia, a leading Original Equipment Manufacturer (OEM) in the telecom sector, faced the daunting challenge of maintaining high production rates, exceptional quality levels, and competitive pricing, all while catering to the telecom customers’ demand for near-perfect network reliability and operating within tight margins. The whitepaper explores how Nokia, with nFlux’s advanced worker guidance solutions, has overcome these hurdles to significantly enhance quality benchmarks and operational excellence in what we now refer to as the “Factories of the Future.”

Nokia’s Head of Operational Excellence at Nokia Chennai, emphasizes the critical need for precision in production engineering. With the assembly of hundreds of 5G antennas per shift, the margin for error is virtually non-existent. Any mistake could result in costly servicing or replacements, underscoring the importance of flawless assembly processes.

The collaboration between nFlux and Nokia means a paradigm shift in quality management. By moving away from traditional quality management methods that focused on streamlining tasks at individual stations and relying heavily on specialized tools, to embracing AI-powered guidance solutions, we’ve demonstrated a more dynamic and cost-effective approach to achieving high-quality standards. This shift not only enhances worker satisfaction by reducing mental fatigue but also allows for a more efficient allocation of resources, leading to a notable decrease in the cost of quality.

Our whitepaper details the significant impact of the nFlux Guide™ system, which has led to a 34% reduction in quality escapes and an 18% reduction in scrap materials, showcasing the tangible benefits of integrating AI and computer vision into manufacturing processes. The Guide™ system offers real-time, step-by-step guidance to assembly workers, reducing human error and improving overall quality standards.

This collaboration marks a significant milestone in telecom manufacturing, blending traditional methods with the latest in AI technology to not only meet but exceed Nokia’s high-quality standards. It represents not just a technological leap but a move towards a more sustainable, worker-friendly manufacturing environment.

We invite you to explore the full details of this transformative journey by reading the whitepaper available on our website, www.nflux.ai. Discover how nFlux’s AI solutions, like those implemented at Nokia, can revolutionize your production efficiency. Join us in embracing the future of manufacturing with nFlux.

Experience the Edge of Manufacturing Innovation with nFlux Guide™!

For more insights, check our first whitepaper on how nFlux and Nokia transformed worker training and set new benchmarks in manufacturing excellence.

Related Article

robots rule and human worker
Future Manufacturing

Do robots ‘rule’​ and human workers ‘drool’​?

Elon Musk said: “It’s relatively easy to make a prototype but extremely difficult to mass manufacture a vehicle reliably at scale. … For cars it’s maybe 100 times harder to design the manufacturing system than the car itself.”

nokia nflux whitepaper
Case Study

Whitepaper published: How Nokia is reducing their training time with nFlux

Unlock the secret to halving your manufacturing training time with AI—discover how in our latest whitepaper! This groundbreaking study showcases how nFlux’s cutting-edge AI solutions have transformed employee training within a leading tech company, dramatically reducing training durations by 50%

Leave a Reply

Your email address will not be published. Required fields are marked *