Market intelligence company ABI Research's 'Digital Factory Data' report notes that spending on smart manufacturing by factories adopting Industry 4.0 solutions, such as autonomous mobile robots, asset tracking, simulation and digital twins, will grow from $345-billion in 2021 to more than $950-billion in 2030 as manufacturers advance their digital transformation initiatives.
“While most of the revenue today is attributed to hardware, a greater reliance on analytics, collaborative industrial software and wireless connectivity will drive spending on value-added services, namely connectivity, data management and enabling platforms, to more than double over the forecast period,” explains ABI Research industrial and manufacturing research director Ryan Martin.
The top-producing manufacturing regions are China, the US, Japan and Germany, and the transportation industry, more specifically automotive manufacturing, is the top industry in terms of revenue in all regions except China, where automotive is second and electronics manufacturing is first.
These regions are also the early adopters of advanced manufacturing technology and are the most developed manufacturing economies globally. In terms of automation, the automotive industry leads, having automated close to 50% of operations, says ABI Research.
“Manufacturers and their technology partners are acutely focused on supporting the shift to digital threads for better data management and enrichment throughout the manufacturing lifecycle,” says Martin.
“A common data backbone allows manufacturers to operate more efficiently across teams and departments, and there are a range of suppliers helping manufacturers with their digital threads,” he highlights.
“Increasingly, there are more data sources, including spatial data, that can be layered and compared in real time for more contextual and predictive operations. The most advanced manufacturers are starting to think along these lines while the majority have started their digital transformation journey but have yet to fully scale,” Martin concludes.