Industry 4.0, AI and Automation: Smart Manufacturing in 2024
A roundtable of smart manufacturing predictions for 2024
The evolution of Industry 4.0 is causing an increase in smart manufacturing technologies, as businesses prioritize automation solutions to ease ongoing pressures on a dwindling workforce and supply chain issues.
With COVID demonstrating the inadequacies of rigid, monolithic processes, businesses have turned their attention to flexible, adaptable systems that favor plug-and-play and interoperability, and tech innovators are rising to meet this changing need.
IoT World Today collected smart manufacturing predictions from companies across industries, looking into how they expect the industry to change in the coming year, what technologies are set to emerge and how businesses can adapt to meet the changing landscape.
Roman Freidel, Global CoE Leader for Manufacturing Industry, Syntax
“Smart manufacturing is boosted for transformative changes in the coming year. We are placing much more significant emphasis on real-time data monitoring, predictive analytics and automation as a direct response to the increasing demand for market adoption to support personalization, flexibility and speed.
“One of the noticeable changes we anticipate is the accelerated adoption of Industry 4.0 technologies. Central to this evolution is the Industrial Internet of Things (IIoT). As more devices and systems get connected every day, smart factories will become more integrated, networked and ultimately more intelligent. With this will come enhancements in sensor technology, wireless networking and edge computing.
“In addition, Artificial Intelligence (AI) and Machine Learning (ML) are also set to drive changes by empowering more informed decision-making, optimizing efficiency and enabling predictive maintenance routines. With such technologies, smart manufacturing is not only about streamlining processes but also about achieving self-optimization and self-learning capabilities.
We also anticipate a great deal of attention dedicated to cybersecurity as companies move towards a more interconnected, data-driven model.”
“Technologies that enable remote operation and virtual training, like Augmented Reality (AR) and Virtual Reality (VR) will gain popularity and potentially shape the future workforce of smart factories.
“Despite the exciting opportunities these technologies offer, the journey towards fully-fledged smart manufacturing is not without challenges. One of the leading challenges companies are expected to face is the integration of their legacy systems with new technologies. For many customers, this will involve strategic planning and investment to ensure a smooth transition and continuous daily operation. Cybersecurity is another big concern. As factories increasingly connect their machines, assets and processes they become more vulnerable to cyber threats.
“Another challenge is the skills gap. With new technologies come new competencies. Not only will businesses need workers trained in these new technologies, but they will also need to focus on continuous learning environments to keep abreast with the rapidly evolving tech landscape.
“However, despite these challenges, the potential benefits far outweigh the hurdles. It's an exciting time in the world of smart manufacturing and we look forward to being part of the journey to deliver the digital factory as a service.”
Roger Sands, CEO, Wyebot
“Innovative network automation solutions are used to improve user experiences, boost operational efficiency and deliver lasting benefits to an organization, however, these solutions are sometimes only adopted when companies realize they’re experiencing network issues. In the manufacturing industry, enterprises will thrive by utilizing automated Wi-Fi monitoring to streamline every process that depends on Wi-Fi, where answers to any network performance issues are delivered in real time.
“In 2024, manufacturing enterprises will accelerate the adoption of network automation similar to other verticals with business-critical Wi-Fi deployments. Manufacturing organizations are leveraging inventory management solutions via barcode scanners along with robots for automating operations which are both dependent on high availability WiFi connectivity.
“We expect to see network automation become mainstream given the dynamic nature of these environments (IoT explosion, mobile connectivity and evolving Wi-Fi technologies). There will be early adopters deploying cellular networks to complement Wi-Fi.
“Companies can ensure they’re remaining ahead of the changes by adopting network automation solutions. Companies adopting new automation solutions is important, but also ensuring that while doing so, they are also adding in any necessary new infrastructure, devices and/or software to further support the technology adoption.
“Security continues to be an important element of networking and customers should continue to ensure their networks are locked down to complement the ongoing automation. In addition, as new Wi-Fi infrastructure technologies are deployed (i.e. Wi-Fi 6E), clients have to be updated to take advantage of the new technology.
“Contrary to the popular standard narrative surrounding supply chains, in 2024, supply chains will no longer be the primary obstacle hindering manufacturing networks when transitioning to Wi-Fi 6E. Instead, the biggest obstacle will be the time it will take to ensure WiFi 6E is widespread enough to support successful implementation.
Tom Shoemaker, Vice President of Product Marketing, Propel Software.
“We expect 2024 to be an important year for manufacturers as they explore the potential of AI in their businesses.
“Manufacturers will use AI to analyze demand trends from multiple data sources. Finding the earliest leading demand indicators allows them to update products, secure suppliers, and adjust order quantities before competitors do. With enhanced demand visibility, OEMs can adopt better-informed procurement and design strategies to maximize profit.
“Given past product performance and a stream of IoT data from instrumented products in the field, AI can monitor usage patterns to predict when machines and equipment are likely to fail, allowing for preventive maintenance. This reduces downtime and helps bolster customer satisfaction.
“AI can help companies determine if their supply chain is at risk from a variety of factors, including part availability, end-of-life, supplier quality and regulatory compliance. Reducing risk means less chance of failing to meet customer commitments, critical launch windows or having products held up in production.
“By analyzing customer feedback, supplier performance, and product operational data, AI can inform sustaining engineering or the design of future products, leading to continual improvements in quality.