Get insightful content delivered right to your inbox!
Posted by Javeria Rahim
The manufacturing industry has not been the same since Covid-19. The pandemic highlighted that that the industry needs to be more resilient to weather any uncertainties that come its way and today we can see a transformation underway. The manufacturing sector is abuzz with terms such as “digital transformation, smart factories, AI as manufacturers are exploring advanced technologies to increase efficiency and productivity. In this article, we will discuss the latest manufacturing industry trends in 2024, and see where the industry is headed.
According to Reuters, the US manufacturing industry accounts for 10.4% of the economy. While the rising interest rates have dampened the demand for goods, it is expected that the activity could pick up from September onwards with revised monetary policies.
However, as per Deloitte, the manufacturing industry is also faced with challenges such as economic uncertainty, the ongoing shortage of skilled labor, and supply chain disruptions that come with the geopolitical conditions in the world. Deloitte mentions that technology is playing a central role in helping manufacturers deal with these challenges. So, it is safe to say that technology will be the main factor that will shape the manufacturing landscape.
Here are some manufacturing industry trends that you need to be aware of:
What was once just a futuristic concept has now become a tangible reality. According to Emgen Research, the global Industry 4.0 market is expected to reach $279.75 billion by 2028, and a lot of this growth would be contributed by the industrial sector.
Smart factory leverages advanced technologies like AI, 5G, IoT, and data analytics to create a connected production environment, which allows manufacturers to gain real-time insights, see the entire production process clearly, and adapt quickly to changing needs. According to research, 83% of manufacturers think that within five years smart factory solutions will change the way products are produced.
A smart factory, however, is not just about implementing technologies; smart factories are self-learning systems that continuously improve over time. They utilize data to identify patterns and learn from mistakes, so they can become more efficient, adaptable, and secure over time, benefiting both the factory and its operators.
According to McKinsey, manufacturers who have already implemented smart factory solutions are reaping benefits such as 30 to 50 percent reductions in machine downtime, 10 to 30 percent increases in throughput, 15 to 30 percent improvements in labor productivity, and 85 percent more accurate forecasting.
Automation is not a new manufacturing industry trend. However, according to a recent survey conducted by McKinsey, initially manufacturers wanted to implement automation for cost reduction and increased productivity, but today manufacturers also want to improve resilience, flexibility, and sustainability.
The report highlights that advanced manufacturing technologies such as digital twins, robots capable of teaching themselves, and devices that can do their own programming—will become ubiquitous in the future—it may take 15 years or 5 years, but it will happen. The shift is happening because two technologies i.e 5G and Wi-Fi 6, which are starting to mature and manufacturers are increasingly adopting them.
McKinsey also highlights ten technologies that are already in use and will increase through 2030. The rapid adoption of these technologies will fuel industrial automation.
The market for augmented reality (AR) and virtual reality (VR) in manufacturing is booming. It was valued at $ 8.2 billion in 2022 and is expected to touch $74.1 billion by 2032. The growth highlights the potential of these technologies in the manufacturing sector and the benefits they have to offer.
One interesting application of AR especially is for on job training; manufacturers can easily make SOPs available to everyone simultaneously. Let’s see the case of Boeing. Laying wires is a complex task that requires high precision and often results in error. Initially, workers were given wiring instructions on paper manuals, and they had to figure it out with diagrams. Boeing then implemented AR and was able to reduce training time by 75% and increase accuracy by 33%. Boeing is not the only one, VR is now central to Ford production as well. The manufacturer leverages VR to create 3D models, so everyone can experience and collaborate on various aspects of production.
AR and VR can do wonders for training, especially when the manufacturing industry is facing a skill shortage. Now, there are software that project live worker guidance, so assembly workers know exactly what the next step is and get alerts if they miss one.
The world has been talking about AI for quite some time, but AI is mainstream now— it is the era of Gen AI. To understand the difference between the two, let’s put it this way: AI is a broad term encompassing any technique that enables computers to mimic human intelligence. AI in manufacturing primarily focuses on optimizing existing processes and operations. It excels at data analysis, pattern recognition, and predictive modeling. Gen AI, on the other hand, focuses on creating new content; it uses algorithms to generate text, images, and other forms of media.
Gen AI can revolutionize manufacturing by boosting productivity, predicting equipment failures, and creating clear, adaptable work instructions. It can also provide real-time assistance to operators. A key use of Gen AI is summarizing complex information. Manufacturers can use this to quickly access vital data like manuals, procedures, and incident reports, improving efficiency and reducing downtime.
The best part about Gen AI is perhaps that using digital infrastructure that can work with Gen AI doesn’t require a complete overhaul of the manufacturing floor; it can seamlessly integrate with existing MES and learn from existing knowledge bases.
Manufacturing industry generates about 1,812 petabytes (PB) of data every year, way more than communications, finance, retail and other industries. So, clearly the problem is not data collection; it is managing large amounts of data, which is becoming a concern for the sector.
As per McKinsey, manufacturers collect data from various sources, but it is often unusable due to quality concerns. Data quality is the cornerstone of machine learning operations, but issues such as faulty equipment, incomplete data, system incompatibility, slow data access, and a lack of data understanding often leads to the failure of digital transformation initiatives.
So, manufacturers today are adopting a data-centric AI approach that unlocks the potential of machine-learning models through high quality data. Consequently, data-centric AI tools are gaining popularity as they can quickly improve data quality. These tools automate tasks like labeling data, enriching data with synthetic values, and combining information from different sources.
One of the hottest manufacturing industry trends is the introduction of collaborative robots or cobots as they are called. Manufacturers have been using robots for decades now, but cobots are a new concept and they are rapidly gaining traction.
The market for cobots was valued at $1.9 billion in 2024 and is expected to touch $11.8 billion by 2030. The growth makes sense since cobots are cheaper to operate than traditional robots. Unlike traditional industrial robots that operate in caged-off areas, cobots are equipped with sensors and safety features that allow them to interact with people without posing a risk. They are often used to perform repetitive or physically demanding tasks, freeing up human workers to focus on more complex and creative activities.
Sustainability is the need of the hour rather than a manufacturing industry trend. According to the World Economic Forum, the industrial sector contributes nearly 30% to global greenhouse gas emissions. Given the drastic climate changes the world is witnessing, many countries are implementing carbon taxes or cap-and-trade systems, incentivizing emissions reduction. Moreover, standards like ISO 14001 are becoming increasingly important for market access.
Many manufacturers have already started investing in environmentally friendly initiatives. Ford recently opened a carbon neutral vehicle assembly plant in Germany. The company invested $2 billion to transform the plant that was first built in the 1930s. Ford is not the only automaker; Volvo has also pledged to reduce CO2 emissions by 75% till 2030, in addition to becoming climate neutral by 2040.
The US manufacturing industry is facing an unprecedented labor shortage. According to a report by Deloitte the manufacturing sector is going to create as many as 3.8 million jobs between 2024 and 2033. However, if manufacturers are unable to address the gap between skills and applicants, around 1.9 million jobs could go unfilled.
In the past, whenever manufacturers were faced by a skills shortage, they used to increase wages. However, money is no longer a motivator for GenZ. Research highlights that GenZ is willing to accept less compensation if they get to do meaningful work.
According to Deloitte’s Workforce Experience research, workers who feel that their organization can equip them with skills that are important for the future are 2.7 times less likely to leave their organization. Deloitte also highlights that manufacturers are partnering with organizations to form an ecosystem that can help workers learn more skills. Many are also utilizing e-learning platforms and sponsoring workshops, seminars and conferences. Many large manufacturers like Ford and Volkswagen are also investing advanced technologies and using AR and VR to train workers.
Before Covid, many manufacturers used to rely on suppliers in China. However, when COVID struck and supply chains were disrupted, it was an eye opener for manufacturers. So, the new manufacturing trend is to bring production home. According to recent research, 69% of manufacturers have started to reshore their operations and 94% of them have been successful in doing so. Apple also recently announced that it has invested over $16 million over the last five years to relocate its production away from China. While the costs of reshoring can be very high, given the global uncertainty, the trend is likely to continue in the near future.
The current manufacturing industry trends indicate that the future of manufacturing would likely look a lot different than what it is today. Manufacturers would be leveraging AI and automation a lot more, there is going to be a lot of focus on upskilling and reskilling workers and sustainability would become way more important.
Want to keep up with the future of the industry? You should consider leveraging AI for your manufacturing operations. Retrocausal’s manufacturing AI Copilots: Assembly Copilot and Kaizen Copilot can help you transform your manufacturing processes, improve product quality and increase efficiency. See them in action with a demo!
Brandin and his team help our customers with setting up the Pathfinder platform and getting up-to-speed on all the features and functionalities, in addition to assisting them with standardizing their processes where needed.
Brandin is a seasoned manufacturing leader, who has spent more than a decade designing and setting up assembly lines in both the US and China, optimizing them, and working with human operators to maximize productivity and quality.
Jesse works closely with our marquis customers to understand their needs, and figures out the best solution that immediately adds dollars to their bottom line.
Jesse has two decades of enterprise sales experience. He has held sales leadership roles at pioneering technology startups.
Andrey takes inventions and converts them into innovations. He leads our product engineering team to turn our scientific prototypes into robust customer-facing products.
Andrey co-founded and successfully exited a startup to immigrate to the US. He spent his next eight years building the core data science infrastructure for Amazon’s supply chain planning team, and the CV/ML infrastructure for Microsoft’s HoloLens organization.
Zeeshan focuses on delighting our customers by understanding their needs and defining product and strategy to meet and exceed these needs. He works closely with our sales leadership to grow our customer base.
Zeeshan was a scientific leader at Microsoft’s HoloLens division, where he invented AI technologies to assist frontline workers across industries. Earlier, he shipped IoT platforms and visual defect detection software for manufacturers at Siemens and MVTec GmbH.
Huy takes our product roadmap and figures out what’s achievable with today’s AI advances, and what we need to invent to solve our customers’ pain points.
Huy led teams of scientists and engineers at NEC and invented technologies for driver assistance systems that are part of 500,000+ Honda cars. He is an inventor on more than 20 US patents, and his research papers are cited by every lab from MIT, Stanford, and CMU to Apple, Google, and Baidu.
