Today, Automakers face unprecedented change and challenges in their industry, from inflationary pressures, supply chain and production issues, and a shift to electronic vehicles. Then there’s the digitization of the automobile itself, autonomous driving.

These, among other competitive pressures, are why automakers keep pouring investments into smart manufacturing. According to Vantage Market Research, the total smart manufacturing market size was estimated at $103 billion in 2022 and is expected to reach $383 billion by 2030. These investments are aimed at manufacturers deploying IoT, AI/ML, and automation technologies to optimize their manufacturing processes and supply chains.

According to the recent research released by Rockwell Automation, 97% of automotive manufacturers currently use or evaluate smart manufacturing technologies, up from 85% last year. The expected benefits include reducing costs and improving quality, though the cost of smart manufacturing investments is also seen as the most significant barrier to adoption.

Automotive firms generate the most return from plant connectivity and efficiency investments, including 5G, manufacturing execution systems, and programmable logic controllers.

Automakers are hoping for smart manufacturing to cut costs in the long term through data-driven services such as predictive maintenance, remote diagnostics, and performance analytics offered to customers. This data will be collected and analyzed from auto sensors, connected Internet of things devices, and factory-floor sensors and equipment to improve quality, optimize supply chains and inventory, and overall production improvements.

The top cited external obstacles to the industry’s smart manufacturing objectives are cybersecurity and rising energy costs.

Data Usage and Cybersecurity Concerns

Automotive leaders use data to fuel AI/ML for process optimization and cybersecurity initiatives. Of course, increased data and data-related services mean an increased attack surface, making cybersecurity a top concern for automakers. However, less than half of the collected data is currently effectively utilized by automotive manufacturers.

Internal obstacles are quite different, as the report found “budget constraints are dampening growth, closely followed by organizational change management. While retaining and upskilling existing employees is a top three concern, the sector is less challenged by recruitment than other industries,” the report states.

As part of the new business models in the industry, and due to government mandates for more intelligent transportation systems, automakers are incorporating increasing smarts into their vehicles — which is also raising security concerns.

“The good thing is that the automakers and the auto suppliers are shifting left and incorporating security into their designs,” says Josh Kolleda, transport assurance practice director for North America at consultancy NCC Group. “While they’re developing with a more secure design lifecycle, the more features the vehicles have, the greater the risk for security flaws and misconfigurations creeping in,” says Kolleda.

The top five planned automotive investments, according to the survey, are in the industrial/metaverse (46%), generative or casual AI (42%), wearables (40%), robots (37%), and machine learning/artificial intelligence (36%).

That level of technological investment will require a workforce with emerging and specialized skills, but traditional people skills are also needed. “Automotive employers believe employees who can work well in teams and are flexible and analytical will help drive the industry forward. These so-called ‘soft skills’ are rated more highly than technical abilities around maintenance, repair, and smart technology,” the report states.

The workforce skills automakers report seeking the most, in order, include communication/teamwork skills (84%), flexibility and adaptability (84%), knowledge of smart technology (83%), analytical thinking (79%) and maintenance/installation/repair skills (76%).

Not everyone is as bullish in the short term, when it comes to broad adoption of smart manufacturing. Forrester analyst Paul Miller predicts that such technology investments as generative AI and metaverse will be scaled back this year “as the painful realities of grappling with issues such as technical debt, legislation, and global supply chains bite.”