Automation is nothing new to the factory floor, but as pressure mounts to speed up production and eliminate errors, manufacturers are finding that digitising physical processes is not enough. A fundamental transformation is happening behind the scenes in how machines learn, coordinate and make decisions.
Hexagon’s Manufacturing Intelligence division has launched a new suite of tools aimed not at accelerating the physical operations of manufacturing but at reprogramming how factories think about quality. The Autonomous Metrology Suite, developed on Hexagon’s Nexus cloud platform, overhauls coordinate measuring machine (CMM) workflows to help manufacturers move beyond labour-intensive programming and fragmented data.
Instead of relying on scarce metrology specialists to manually code inspection routines for each part and each machine, the suite introduces a no-code, cloud-based environment that automates programming, measurement and reporting. The software uses a digital twin of every connected CMM to synchronise inspection routines, flag environmental issues such as vibration or temperature drift, and provide traceable quality insights accessible through a unified dashboard.
The goal is not just to speed up operations but to create a continuous feedback loop between design, measurement and manufacturing, where quality becomes a shared, real-time system rather than a departmental afterthought.
Digitising inspection from design to decision
Across sectors, from aerospace to automotive, manufacturers face the same triad of pressure: product lifecycles are shorter, design changes are more frequent, and experienced programmers are harder to find. At the same time, the demand for precision and regulatory compliance has only grown, with standards such as ISO and ASME requiring consistent dimensional tolerancing across global sites.
Hexagon’s solution aims to meet this challenge with three core applications. Metrology Mentor auto-generates compliant inspection routines directly from CAD files, enforcing geometric dimensioning and tolerancing standards across teams. Metrology Reporting consolidates measurement data, regardless of source, into live dashboards showing batch analytics and complete part histories. The Metrology Asset Manager ensures that machine performance and calibration remain within operational thresholds, tracking conditions such as humidity, vibration, and temperature alongside utilisation data.
Together, these applications create a digitally closed loop for quality, where real-time data flows from measurement to decision-making and inspection routines are not tied to individual operators or machines. The system is hardware-agnostic, enabling older Hexagon models, and eventually third-party CMMs, to participate in the same digital workflow.
Notably, the suite’s design philosophy prioritises usability. Each application uses a shared, intuitive interface with drag-and-drop file handling, automated prompts and dynamic updates. Users trained on one app can quickly adapt to others, reducing onboarding time for new staff and flattening the learning curve across the factory.
Quality control becomes a shared function
At Paragon Medical, an early adopter, the impact has been significant. With 17 CMMs operating across different teams and workflows, quality management had become a bottleneck marked by manual oversight, inconsistent measurement strategies and variable training levels. By adopting the new suite, the company reports that processes which once took hours or days now take minutes, with measurable improvements in throughput and team alignment.
The software is now available to pilot customers, with full commercial availability expected later this year. Hexagon has confirmed that future iterations will further simplify metrology data acquisition and usage, using the Nexus platform’s open connectivity to support broader manufacturing analytics and decision-making.
What this move reflects is not just a product release but a shift in how quality is understood in the digital era. Factories can no longer afford for quality to live in silos, buried in spreadsheets or confined to isolated machines. As metrology becomes increasingly intertwined with automation, cloud infrastructure, and simulation, the need for intelligent, unified platforms will only continue to grow.
Manufacturing’s future will not be defined by how many robots it can deploy but by how much of its expertise it can encode, share and scale across every machine, shift and site.
