How can smart systems transform manufacturing?

UL’s Dr Eoin O’Connell discusses how technologies such as 5G, IoT and digital twins can address challenges in the manufacturing sector.

Dr Eoin O’Connell is an associate professor at University of Limerick and the course director for the bachelor’s and master’s degrees in electronic and computer engineering.

Along with his teaching duties, O’Connell’s main research focus is on identifying and overcoming the challenges to digital transformation in manufacturing through technologies such as wireless sensors, the industrial internet of things, 5G and digital twins.

“I aim to understand the specific barriers manufacturers face and develop solutions using enabling technologies to address these challenges effectively,” he explains.

“My goal is to modernise manufacturing processes and make them smarter and more interconnected. I also focus on human-in-the-loop safety, vision systems for line clearance, and the exploration of future technologies like 6G for enhanced connectivity in smart factories.

“Addressing these challenges in partnership with industry collaborators allows companies to gain competitive advantage by being more efficient, competitive and sustainable, helping to drive the transformation needed in the manufacturing industry.”

Here, O’Connell talks to SiliconRepublic.com about his research and how technology is set to transform the manufacturing space.

How do you envision 5G networks transforming the manufacturing landscape?

Cellular technologies, including advancements in 5G, have the potential to transform manufacturing by providing the high-speed, reliable connectivity essential for sensor-driven environments. Currently, real-time data insights on assembly lines can require up to 10,000 sensors, posing challenges for spectrum allocation and data integrity.

As cellular connectivity continues to evolve – becoming more inexpensive – it is allowing manufacturers to deploy private cellular resources on site, enabling the company to gain the ability to scale and manage complex sensor ecosystems, unlocking new levels of reliability, efficiency and sustainability across a large geographical area or densely equipped factory floor.

How can digital twins reshape manufacturing processes?

My research on digital twins focuses on developing virtual models that replicate physical manufacturing systems, enabling real-time monitoring, predictive maintenance and streamlined decision-making. These digital twins act as a bridge between the physical and digital worlds, providing a dynamic view of operations that allows manufacturers to test and optimise changes before implementing them on the factory floor.

By integrating data from various sources, digital twins improve interoperability across diverse equipment and systems, allowing for more efficient operations, reduced downtime and enhanced adaptability. This virtual approach is reshaping manufacturing processes, making them smarter, more responsive and better equipped to meet the demands of modern production.

Could you talk about your focus on IoT and edge computing?

My research in digital transformation focuses on harnessing IoT and edge computing to create highly efficient, precise and responsive manufacturing environments. IoT enables continuous data collection from various sensors across production lines, while edge computing processes this data locally to reduce latency, allowing for real-time insights and anomaly detection. This approach minimises downtime and improves regulatory compliance by enabling immediate responses and precise inspections. By processing data closer to where it is generated, edge computing supports a scalable and responsive infrastructure that enhances operational efficiency, quality control and adaptability in modern manufacturing.

‘By combining automation with human insight, we create a robust system that leverages the strengths of both’

Why is human involvement so important in highly automated, smart systems?

Our approach to digital transformation emphasises a human-in-the-loop model to keep humans actively involved in automated or AI-driven systems, ensuring safety, adaptability and ethical decision-making. While automation is highly effective for routine tasks, human involvement remains crucial for making adaptable and ethical decisions, especially in unexpected situations.

To support this, we have developed an AI vision safety system that detects humans as they approach high-speed robotics, triggering safety measures to withdraw hazards or slow down operations. This approach balances the efficiency of automation with the flexibility and oversight that human judgment provides, ensuring that technology enhances safety and quality without eliminating the need for human involvement. By combining automation with human insight, we create a robust system that leverages the strengths of both.

How does 5G compare to other wireless options for industrial IoT?

5G stands out in wireless communications for smart manufacturing due to its high speed, low latency and ability to support a massive number of devices simultaneously (1m per sq km), which currently sets it apart from other wireless options like Wi-Fi and Bluetooth. Unlike Wi-Fi, which can become congested in dense environments, 5G’s robust connectivity and broad coverage allows for seamless, real-time data exchange across large factory floors. Bluetooth, while useful for short-range applications, lacks the range, speed and scalability needed for industrial IoT. 5G’s ultra-reliable low-latency communication (URLLC) is crucial for applications like robotics and predictive maintenance, where even slight delays can impact performance.

However, it should be said that 5G is by no means a panacea for all industrial applications as it is relatively expensive to deploy, the spectrum is not suitably equipped for non-telecommunications company deployments and there is still a scarce amount of sensors and devices that can be connected directly to a 5G private cell suitable for manufacturing environments.

How can IoT and 5G-enabled systems reduce waste, energy use, or improve resource efficiency on the factory floor?

Some examples from my work to date include IoT-enabled access control systems that streamline building management by eliminating the need for physical keys. This reduced material waste and the administrative overhead of key replacement. When integrated with building automation, these access control systems can also be used to trigger energy-saving actions – such as adjusting lighting or HVAC systems in unoccupied areas thereby enhancing overall energy efficiency.

5G connectivity significantly boosts the scalability and efficiency of IoT networks, making it possible to manage extensive networks of access control, energy-monitoring and environmental sensors across large facilities. With 5G’s high device capacity and real-time data capabilities, facilities can centralise the control of security systems, dynamically adjust energy usage and monitor environmental conditions instantly. This allows for better resource allocation, reduced energy consumption and a streamlined approach to facility management, ultimately maximising security, efficiency and sustainability across the entire building or factory floor.

Looking beyond 5G, what excites you most about the future of connectivity in smart systems and devices manufacturing?

Looking ahead, advancements like 6G, Wi-Fi 7 and AI-enhanced networks are especially exciting, as they will offer faster speeds, greater bandwidth and improved reliability, which are essential for the next evolution of digital twins. With real-time connectivity, digital twins will not only mirror manufacturing processes but also integrate AI capabilities, enabling predictive insights, automated adjustments and even autonomous decision-making. This level of connectivity will allow manufacturers to create highly intelligent, responsive systems, transforming factories into truly adaptive, data-driven environments of the future.

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