Editor's note: Prefer to listen? There's a companion podcast episode for this article. You can access it here: newequipment.com/21282172
Technology is poised to play a significant role in supporting manufacturers in taking on the challenges they may face in 2024. In fact, 54% of manufacturers plan to increase technology spending in 2024, according to Gartner's 2024 Tech Trends Survey. The reason behind this decision is technology's innate ability to help staffing shortages, improve productivity, unlock new revenue streams, optimize supply chains, and enhance market position.
These technology trends reflect ongoing advancements and innovations in the manufacturing industry, which are likely to continue shaping the future of manufacturing in 2024 and beyond. However, the actual adoption and impact of these technologies will depend on various factors, including industry-specific needs, regulatory environments, and economic conditions.
So as we barrel on into 2024, will there be much difference in the way of processes and technology for manufacturing operations, or will it be fairly the same? I lay out the main trends you can expect for the year, what that might look like, and how you can use them.
Artificial Intelligence
Artificial intelligence (AI) has exploded and will only get stronger in 2024 as AI has become synonymous with innovation, efficiency, and competitiveness. As we delve deeper into 2024, the role of AI, particularly generative AI, is evolving rapidly, reshaping how products are designed, optimized, and produced.
AI has emerged as a transformative force in manufacturing, offering a wide range of applications across various stages of the production lifecycle. AI-powered algorithms analyze vast amounts of data, identify patterns, and make autonomous decisions, enabling manufacturers to optimize processes, improve quality, and enhance productivity whether it's predictive maintenance, quality control, or supply chain management.
The next frontier will be generative AI, leveraging advanced machine learning techniques to create novel designs, solutions, and optimizations. Unlike traditional AI, which relies on predefined rules and data inputs, generative AI can generate new ideas and solutions autonomously, based on high-level objectives and constraints provided by users. It will empower manufacturers to explore more possibilities, uncovering new solutions and optimizing designs in ways that were previously unimaginable.
Generating thousands of design iterations based on specified parameters and objectives, generative AI creates diverse design possibilities and optimizes performance, cost, and sustainability to create innovative, high-quality products that meet customer needs and market demands. Manufacturers can also optimize processes by analyzing data from sensors, equipment, and production systems to identify inefficiencies and opportunities for improvement. It also has a place in supply chain management by analyzing historical data, market trends, and external factors to generate predictive models and analyze scenarios to correctly align inventory levels, minimize lead times, and mitigate supply chain risks.
Through these optimized and streamlined processes, operational efficiency will be enhanced, waste reduced, and throughput maximized, driving down costs and improving competitiveness.
The Industrial Metaverse and Smart Factories
Smart factories are nothing new, but in 2024 they will continue to be the cornerstone of modern manufacturing, driving innovation, productivity, and competitiveness to new heights. A recent Deloitte study indicated that 86% of manufacturing executives believe that smart factory solutions will be the primary drivers of competitiveness in the next five years.
The smart factory integrates advanced technologies such as AI, 5G, Internet of Things (IoT), data analytics, and cloud computing in the production environment to help provide real-time insights, end-to-end visibility, and scalable solutions. Economic upheaval, a tight labor market, rising costs, and continued supply chain stresses underline how important agility, resilience, and efficiency are in manufacturing operations. The potential benefits of smart factories range from gains in asset efficiency, labor productivity, and product quality to substantial cost reduction, along with the advancement of the cause of safety and sustainability.
What we'll see this year is smart factories adopting edge computing solutions to process data closer to the source, enabling real-time analysis and decision-making at the edge of the network to reduce latency, bandwidth requirements, and reliance on centralized data centers. Of course, AI algorithms will continue to play a big role in predictive maintenance strategies as well.
But there's also a new partner of smart factories in town reshaping the future of manufacturing: the Industrial Metaverse.
Inspired by the convergence of VR, augmented reality (AR), the IoT, and AI, the industrial metaverse represents a digital twin of the full physical manufacturing environment. It's a digital ecosystem designed to mirror the physical factory, creating a seamless interaction between physical assets, virtual simulations, and digital twins. It encompasses a spectrum of technologies, including VR, AR, mixed reality (MR), and spatial computing, that work together to create a unified, interconnected environment where humans, machines, and data interact in real time.
According to the 2023 Deloitte and MLC industrial metaverse study, over 70% of surveyed manufacturers have woven technologies such as data analytics and cloud computing into their processes, and nearly half are already harnessing the power of IoT sensors, devices, and systems. In addition, the majority of surveyed manufacturers have made significant investments in digital twins, 3D modeling, and 3D scanning, which serve as key building blocks of the 3D environments that make up the industrial metaverse. And 21% of respondents in the same study are already integrating metaverse technologies to elevate their supply chain ecosystem.
VR and AR have been integrated into the industry for a few years now but haven't taken off in a big way. A few companies have developed products centered around remote maintenance that incorporate AR technologies as well as training programs that use VR to help get new workers up to speed. But the issue with these is once again, cost and integration into processes. But now, with the emergence of the industrial metaverse, VR and AR finally have a central role to play, providing an immersive experience that bridges the gap between the physical and digital worlds of the factory.
VR enables users to enter virtual environments and interact with simulated machinery, production lines, and processes by replicating real-world scenarios, letting users gain hands-on experience, develop new skills, and enhance their knowledge of operating machinery. AR overlays digital information onto the physical world, enhancing situational awareness, training, and maintenance activities such as remote monitoring and maintenance. We will see continued adoption of AR smart glasses, removing the need for on-site presence as technicians can visualize equipment status, access maintenance instructions, and receive real-time guidance from remote experts, improving efficiency and downtime.
Of course, IoT is the backbone of this whole operation, enabling real-time monitoring and control of assets and operations. IoT sensors embedded within machinery, equipment, and infrastructure collect data on performance, condition, and energy consumption, facilitating predictive maintenance, process optimization, and quality control. AI algorithms and machine learning models power those predictive analytics through optimization algorithms and autonomous decision-making capabilities.
The industrial metaverse will foster collaboration and communication among stakeholders throughout the world. It will enable virtual meetings and shared workspaces where teams can collaborate in real time, visualize complex concepts, and troubleshoot issues more quickly and effectively, reducing the time it takes to find a solution and accelerating the decision-making process.
Additionally, 92% of surveyed manufacturers are already experimenting with or implementing at least one metaverse-related use case, and on average, they are currently running more than six use cases. According to another survey, manufacturers anticipate that the industrial metaverse could lead to a 12% gain in labor productivity, which might help address the ongoing labor shortages.
The biggest hurdle will be getting workers trained on the digital technologies themselves, creating a culture of digital literacy, and upskilling the workforce to maximize the benefits of this immersive factory world. But, by harnessing the power of these technologies, manufacturers can create agile, resilient, and interconnected manufacturing ecosystems that unlock new levels of productivity, efficiency, and value creation.
On-Demand Manufacturing
With the rise of supply chain challenges stemming from the 2020 pandemic, there has been a lot of talk about the customization of products and equipment in the manufacturing space. On-demand manufacturing has taken hold through its ability to let manufacturers produce goods quickly, efficiently, and in response to real-time demand. This approach minimizes inventory, reduces lead times, and enables businesses to tailor products to meet individual customer needs. By using real-time data analytics, predictive modeling, and supplier collaboration platforms, businesses can optimize inventory levels, mitigate supply chain risks, and ensure timely delivery of components, enabling seamless integration with on-demand production processes.
Basically, by producing goods on a per-order basis, businesses can reduce excess inventory, avoid overproduction, and respond quickly to changes in demand, optimizing working capital and cash flow.
One of the biggest drivers behind this concept is 3D printing. After many years, 3D printing is at a place where it's enabling the quick process of prototyping and customized parts and products, allowing design freedom, complexity, and speed. It lets manufacturers move away from the more timely tasks of cutting, drilling, and molding raw materials that come with subtractive manufacturing and instead build objects layer by layer using digital design files. Businesses can tailor products to individual customers by accommodating unique specifications, variations, and configurations, enhancing customer satisfaction and loyalty.
Additionally, the advancements in automation technology such as integrated software platforms, digital design tools, and automated production systems are helping to streamline manufacturing processes, from design and prototyping to production and fulfillment, reducing manual intervention and accelerating time-to-market.
On-demand manufacturing promotes sustainability and waste reduction by minimizing material waste, energy consumption, and environmental impact by producing goods only when needed, reducing excess consumption, and contributing to a more sustainable and circular economy.
Humanoid Robots
In the realm of manufacturing, the integration of robotics has long been synonymous with automation and efficiency. In 2024, we are finally witnessing a robotic shift as humanoid robots take center stage. With advancements in AI, sensor technology, and robotics, humanoid robots are set to revolutionize the industry, offering unprecedented levels of flexibility, adaptability, and collaboration alongside human workers.
Designed to resemble and mimic human-like movements and capabilities, humanoid robots have the dexterity, mobility, and cognitive capabilities to perform a wide range of complex tasks in dynamic environments. From assembly and inspection to material handling and collaborative tasks, humanoid robots are redefining the boundaries of automation and human-robot interaction in manufacturing.
At the core of their capabilities lies AI and machine learning algorithms enabling them to perceive and interpret their surroundings, learn from experience, and adapt to new tasks autonomously. By leveraging AI-powered vision systems, natural language processing, and decision-making algorithms, humanoid robots can recognize objects, understand instructions, and make real-time decisions in response to changing conditions, enhancing their versatility and efficiency in manufacturing operations.
Advanced technologies such as cameras, LiDAR, and tactile sensors enable these robots to perceive and interact with their environment with human-like precision and sensitivity. By detecting and responding to tactile feedback, visual cues, and spatial awareness, humanoid robots can navigate complex environments, manipulate objects, and interact safely with human workers creating truly seamless collaboration on the factory floor.
So why the big shift to humanoid robots as opposed to mobile robots and traditional cobots? The reason is that humanoid robots really excel at the repetitive, physically demanding tasks that human workers are at risk of injuring themselves with, creating further issues with downtime and labor shortages. By using robots to handle hazardous or physically demanding tasks such as heavy lifting or exposure to hazardous materials, human workers are protected from potential harm. The robots are also capable of reprogramming and reconfiguring to accommodate changing production requirements and product variants, allowing manufacturers to have more agility and responsiveness in dynamic market environments.
Since we're just seeing humanoid robots entering the market on a mass scale, there will still be issues with cost, integration complexity, and workforce readiness this year. However, as technology continues to advance and adoption rates increase, these robots will become increasingly ubiquitous, reshaping factories and creating new levels of productivity, efficiency, and competitiveness in the global market.
Product-as-a-Service
In 2024, PaaS has emerged as a disruptive force, revolutionizing traditional manufacturing approaches and offering a myriad of benefits for both businesses and consumers. Product-as-Service (PaaS), also known as Servitization, is a business model where manufacturers, instead of selling equipment, lease the equipment to customers. Alternatively, it could also mean providing a set of subscription-based value-added services. The idea behind PaaS is that customers can benefit by only paying for what they need on a pay-per-use or subscription basis while also getting additional support from OEMs, helping to optimize their operations.
PaaS aligns incentives between manufacturers and consumers, creating long-term relationships and encouraging sustainable consumption. It promotes a more sustainable approach by incentivizing manufacturers to design products with longevity in mind since they retain ownership of the product through its lifecycle, reducing waste and environmental impact. It allows consumers more flexibility and scalability as they can adapt as needed by having manufacturers adjust the production capabilities of the product, upgrade its features, and introduce new offerings without requiring customers to make significant investments upfront. Additionally, it allows manufacturers to remotely monitor the equipment, anticipating and addressing potential issues before they escalate, optimizing service delivery, minimizing downtime, and enhancing overall customer satisfaction.
It's a shift from one-time transactions to recurring revenue, capturing revenue throughout the equipment lifecycle. It also lets manufacturers collect equipment usage data from customers that can be used to better understand customers’ needs, optimize existing offerings, and bring new products to market.
PaaS is not brand new in the industry, but we didn't have the full set of technology to really make it work. But now IoT, AI, predictive analytics, and other technologies have matured enough to put it into practice.
Predictive Maintenance
Predictive maintenance has been at the forefront of manufacturing for some time now, and while it remained a key trend for 2023, it will look a little different in 2024. Instead of predictive maintenance, manufacturers are in the early stages adopting of predictive resolution.
Where predictive maintenance uses data analysis to identify anomalies in equipment performance and determine their root cause, predictive resolution takes this concept one step further, offering technicians insights on how to resolve those issues with greater certainty. In basic terms, predictive resolution increases the likelihood that an issue will be correctly addressed on the first try, enabling manufacturers to enhance equipment efficiency, reduce costs, and improve their first-time fix rate.
Although predictive resolution has long been a goal for manufacturers, they’ve struggled to build the necessary history to support predictive models. Recent advancements in AI, machine learning, natural language processing (NLP), and real-time data analytics have made it possible to identify, diagnose, and address issues before they even occur.
By using predictive resolution in conjunction with IIoT, manufacturers will be able to ensure that production assets and/or customer equipment operate as intended, proactively address issues before they have the chance to lead to unplanned downtime, and extend the life of machinery. It also can enhance workplace safety by identifying and mitigating potential hazards before they become a risk, creating a safer working environment, and ensuring compliance with regulatory requirements and industry standards.
This is yet another area in which Product-as-a-Service will prove essential, as the usage data customers generate will provide manufacturers with other valuable data points that they can use to build machine learning models and engage in predictive resolution.
Predictive resolution is not without its challenges, though. Manufacturers will need to overcome barriers such as data silos, interoperability issues, and organizational resistance to change to reap the full benefits. Likely the biggest hurdle is ensuring they have robust data security and privacy firewalls in place.
Conclusion
As we reflect on the advancements and industry shifts that characterized 2023, it's evident that we're in for an even bigger year in 2024.
By embracing innovation, investing in digital transformation, and fostering a culture of continuous improvement, manufacturers can position themselves for success in an increasingly digital and interconnected world.
The road ahead may be challenging, but with the right vision, strategy, and commitment to innovation, the future of manufacturing is boundless.