The manufacturing industry has become increasingly digitized over the past few decades as manufacturers become more reliant on emerging technology to automate production and manage operations remotely. These trends have formed the basis of what’s known as “smart manufacturing,” an evolution that’s empowered companies to save money, spot issues earlier, and keep their supply chains running smoothly.
However, the infrastructure that powers these systems has to handle a vast amount of data — an amount that grows every year as technology continues to advance. If they don’t keep up with the exponential increase of data, the very technology that’s meant to improve processes can actually slow down operations and leave companies vulnerable to shipment delays, quality control issues, and even costly operational shutdowns.
These are some of the issues that professionals like Manish Rajendran are working to solve. As Managing Director at Deloitte Consulting, Manish is outfitting manufacturers with private 5G networks and localized data platforms, giving them a faster, more advanced system that can process greater volumes of data with fewer delays. He’s also implemented features like quality sensors and anomaly detection tools, allowing companies to monitor production conditions in real-time and maintain consistent quality. Following the success and adoption of his work, Manish has documented many of his insights in a paper published by Deloitte.
Learn how Manish is helping to build a more connected and reliable manufacturing industry.
Understanding smart manufacturing and its shortcomings
The technological shift that has been transforming the face of the manufacturing industry has seen the mass adoption of tools like remote controllers, sensors, 3D printers, and robotic arms to automate manual tasks like managing raw materials and assembling final products. These tools are stitched together to form an intricate network of interconnected devices — a methodology known as the Internet of Things (IoT) — upon which they can seamlessly interact and exchange data with other devices in the network to keep everything running smoothly with minimal human intervention.
This shift toward smart manufacturing has become increasingly widespread, with over half of American and European manufacturers using these systems to streamline their operations and reduce costs. However, the vast amount of data these devices generate (an estimated 1 billion gigabytes daily) can pose significant challenges for companies relying on third-party cloud servers to process their data. For one, the physical distance between a manufacturer and the cloud server they use can lead to severe issues with latency, causing noticeable (and costly) delays in transferring data, and for industries like manufacturing, such delays can cause actuators to reject the wrong item.
This is where innovators like Manish Rajendran step in to design and implement systems that scale accordingly with exponential data growth.
Building faster, more resilient data systems
With over 20 years of experience in the telecommunications industry, Manish has been working as the Managing Director and 5G & Edge Chief Technical Officer for Deloitte Consulting, one of the largest consulting firms in the U.S.
In his role, Manish works with engineering teams to design private data networks tailored to the unique needs of individual companies. Powered by the ultra-fast speed of 5G, these networks offer uninterrupted connectivity, data transfer rates reaching up to 20 gigabits per second, and latency as low as one millisecond. Unlike the public cloud, these private networks ensure seamless, near-instant communication for IoT devices.
Key to this methodology is the implementation of edge computing infrastructure. This infrastructure is composed of small servers that are located close by, which means the network can process data closer to where it’s generated and greatly reduce delays in data transfer. The result is a rapid reduction of latency compared to traditional cloud servers, enabling companies to process data faster, gain real-time insights into their production lines, and keep downtime to a minimum.
Manish also helps companies improve quality control protocols by integrating specialized IoT tools. This includes high-end quality sensors that monitor factors like temperature, pressure, humidity, and vibration, providing continuous, real-time feedback to manufacturers. This helps companies meet strict quality standards for their products while reducing the need for manual quality inspections — which are often time-consuming and prone to human error.
He’s also implemented anomaly detection systems that analyze production data, identify deviations like weight changes or temperature spikes, and immediately notify companies, helping them address potential issues on the spot and preventing them from spiraling into larger, more expensive problems.
Together, these tools not only streamline operations but also successfully reduce manufacturers’ cost of quality (CoQ) — the total cost of ensuring products meet industry standards. And given that CoQ can account for up to 15% of all operating expenses, these measures stand to significantly boost manufacturers’ profitability while maintaining optimal productivity and quality levels.
A more connected manufacturing industry
Manish Rajendran’s work at Deloitte demonstrates how technologies like 5G and edge computing solve many of the challenges that manufacturers face. By addressing issues like data transfer latency and limited processing speeds while integrating tools like quality sensors and anomaly detectors, Manish is helping businesses improve their production workflows, reduce costs, and maintain consistent quality.
