The ‘manufacturing renaissance’ in the U.S. has dominated headlines in recent months, particularly in light of policies, like America First trade, that reinforce the industry’s acceleration on home soil. Although Deloitte insights show that the U.S. is set to continue growing and maintain its competitiveness, the superpower lags behind in automating manufacturing. For example, countries like South Korea and China feature the highest number of robots in their factories.
While the U.S. manufacturing output ranks second globally, contributing a massive $2.9 trillion to its economy, local manufacturers lag behind Asian companies in areas like chip production and battery manufacturing. These high-technology industries don’t just require huge amounts of raw materials and labor, but cutting-edge solutions to manufacture them at scale.
U.S. manufacturers generally lack the technology guardrails to break into these markets at the same rate as Asian manufacturers. Additionally, with Industry 4.0 fast becoming a reality, integrated automation to maximize efficiency is quickly becoming non-negotiable among leading manufacturers.
In order to come out on top, U.S. manufacturing has to bridge ongoing technology gaps, as well as empower SMEs who have been left in the lurch and still rely on legacy systems.
Outdated Techn Puts a Spanner in the Works
In manufacturing, Industry 4.0 is defined by its symbiotic relationship between humans and technology, where processes and operations are connected and intelligent thanks to solutions like AI, the Internet of Things (IoT), and big data.
Asia has long been the world’s ‘factory floor,’ and automation is becoming second nature to manufacturers in countries like Singapore, Taiwan, and Japan, where robots are an increasingly integral part of manufacturing processes. They’ve been developing the skills and systems to handle huge amounts of data and real-time analytics to deliver output at scale in a manufacturing world increasingly shaped by automated processes.
On the other hand, many U.S. manufacturers, especially SMEs, are now playing catch-up. For instance, a third of manufacturers rely on manual data entry processes. This simply doesn’t hold in an automated environment where big data is a staple.
They’re also operating on legacy systems and fragmented data. Manufacturers looking to adopt IoT tools like robots to propel automation capabilities are running before they can walk if they haven’t addressed these pain points.
The Skills Gap
The U.S. could be short of 1.9 million workers if the talent gap isn’t filled. Right now, automation cannot be achieved safely and at scale without human oversight— and the degree that’s needed to keep pace with Asian competitors means that U.S. manufacturers are short on manpower.
They’re also struggling to retain talent, which is a business hurdle for 65 percent of organizations, according to Deloitte. A unique advantage that countries like Japan have enjoyed for decades is their highly loyal workforce. Japanese employees typically stay long enough at companies to continuously improve their technological aptitude while building an innate understanding of operational processes. When workers jump jobs frequently, it’s difficult to build their knowledge and skills to a level that ensures digital fluency with specific tools and automation.
Bridging the Tech Gaps
First and foremost, U.S. manufacturers have to address interoperability issues between systems and cement strong data management in order to unlock the benefits of technology on the factory floor.
Homing in on the technology itself, it’s best to start small and specific, adopting solutions that directly align with business goals, boost operational efficiency, and address pain points. Interoperability and clear and secure data flow between systems are vital.
When adopting technology, manufacturers should explore the details of an existing workflow. Based on the new system they plan to implement, a workflow should be redesigned to ensure interoperability and safe data handling. Alongside that, manufacturers must also prepare the datasets for the new system.
Once the groundwork has been set for successful, long-term automation, manufacturers can adopt modular and scalable technologies like cloud-based enterprise resource planning (ERP) and manufacturing execution systems (MES). These tools are a powerful starting point to bridge data gaps and ensure coordination across core business functions while having a finger on the pulse for real-time updates on machinery and equipment performance. ERP and MES used alongside each other can tighten overall operations management between the warehouse and office floor, giving a holistic view of planning and execution.
Built-in cameras and IoT sensors enhance data capture across systems, alerting manufacturers to any defects or safety problems via audio communication. Visual and audio data are extremely useful in a manufacturer’s information arsenal, and automating that data capture via sensors, microphones, or cameras means as little as possible slips through the cracks. Layering these IoT tools with embodied AI, such as robots or smart machines, sets the scene for a powerfully efficient and interconnected digital ecosystem.
Besides that, generative AI (GenAI) can help manufacturers personalize training and facilitate faster knowledge sharing. Manufacturers can analyze and synthesize data on an individual basis via genAI, and it can also be applied to on-the-ground training on the factory floor. This helps nurture the needed skills for overseeing and managing automated equipment.
U.S. manufacturers can still leapfrog technological gaps and achieve Industry 4.0 by clearly identifying operational needs, defining their S-Curve goals, and adopting technology step-by-step—aligning it with business priorities and boosting workforce digital fluency.