Hexagon CTO Says Trusted Measurement Underpins Autonomous Manufacturing

Metrology provides the accurate measurement data that many workers and automated systems use to make more informed decisions, Boeckem wrote. Precision measurement technologies combine advanced sensors, software, and analytics to allow organizations to optimize processes in real time. In a world where microscopic inaccuracies can have consequences at scale, trusted measurement assures quality and functions as a strategic capability for safe, efficient, and data-driven industries, according to the article.

Boeckem pointed to motorsport as an illustration. Teams from the factory to the track rely on trusted measurement data to make engineering decisions, and a 1mm difference in ride height can determine both performance and regulatory compliance, he wrote. Precision ensures every part of the car complies with regulations and helps thousands of individual components work together. In a sport where races are won by milliseconds, confidence in measurement equates to confidence in performance, according to the article.

The same principle applies in scientific research, Boeckem wrote. Scientists exploring the fundamental building blocks of the universe depend on intricate technical and engineering work, and particle discoveries would not be possible without it. Precision measurement provides assurance that every observation and experiment is built on accurate data.

Measurement also spans the workforce and supports shifts many organizations are confronting, according to the article. As experienced engineers retire and manufacturers contend with persistent skills shortages, organizations can no longer rely solely on manual inspection to maintain quality. Digital measurement technologies are helping preserve consistency while scaling productivity. By enabling faster, more reliable inspections and identifying issues before they disrupt production, precision measurement allows fewer specialists to oversee increasingly complex operations.

Safety is another factor. In sectors such as aerospace, automotive, and medical manufacturing, getting components right the first time is essential, Boeckem wrote. Safety instruments use precise data to track ground instability or structural deformation of buildings, triggering alerts for rapid incident response and protecting workers in hazardous environments. Precision measurement has evolved from an engineering support function into a strategic capability that helps organizations maintain safety and competitiveness amid growing workforce pressures, according to the article.

Boeckem also addressed AI and autonomous systems. Organizations looking to address workforce challenges can accelerate investment in AI tools and autonomous systems, which increases the need for trusted measurement data those technologies can rely on. As AI and automated systems make decisions once handled by experienced engineers, including adjusting production processes and inspecting components, the data fed into these models becomes significant. Those decisions are only as reliable as the data they are built upon, according to the article.

Without accurate, robust measurement, AI can amplify errors at scale, leading to unnecessary downtime, wasted materials, and compromised quality, Boeckem wrote. Precision measurement provides the confidence intelligent systems need to make reliable decisions. Today, precision measurement is delivered through sophisticated sensors, software, AI, and connected data working together to create a trusted digital understanding of the physical world. As industries become increasingly autonomous and data-driven, precision measurement is no longer merely an option for ensuring accuracy; it is a non-negotiable capability for unlocking the full potential of AI and the shift toward autonomous systems, according to the article.

Editor's Summary

Burkhard Boeckem, CTO at Hexagon, argues in a TechRadar Pro article that trusted measurement is becoming a strategic capability as manufacturing faces a 1.9 million job shortfall and adopts AI and autonomous systems. He cites motorsport, scientific research, and industrial safety as examples where precise data underpins decisions. The article says accuracy is necessary to prevent AI-driven errors at scale and to support safer, more efficient operations.