In today’s increasingly digitized industrial landscape, the science of measurement — metrology — is experiencing something of a renaissance. Modern businesses, from smart factories to hyperscale computing, are profoundly data-driven; precision, calibration, and traceability are all critical to their success.
The future must be calibrated. There's increasing demand for more power in more extreme circumstances, from massive data centers to fusion energy research. Shown here is Sandia National Labs' Z Machine. Credit: Sandia National Labs
As a result, metrology is undergoing its own digital transformation. To keep pace with the ever-growing demand for high-speed, high-volume precision measurements, metrologists are increasingly interested in harnessing the power of artificial intelligence.
Rising Demands from Industry
It’s hard to overstate the level of demand for precision calibration. In fact, for modern industry, precision isn’t optional: it’s a requirement.
As industrial systems become more interdependent, even the smallest measurement errors can create cascading failures. Production lines are disrupted; regulatory compliance is compromised; supply chains are snarled. Calibrated, traceable measurements are now mission-critical for most facets of modern industry, whether it’s maintaining power quality in a data center, or pressure accuracy in a hydrogen fueling system. Metrology’s reach and scope are expanding exponentially.
At the same time, the stakes are higher than ever. The future of the science will be defined by this dual expansion — and AI will be a key factor in successfully meeting the challenges ahead.
Expanding the Calibration Model with AI
AI has the potential to transform calibration processes, creating dynamic models that expand the field’s capabilities. Predictive calibration, for example, could use equipment performance data to forecast drift and optimize service schedules. Briefly, this means that AI algorithms would analyze vast data sets of usage history, trends in measurement data, and environmental conditions. Calibration would then be triggered based on need so that instruments receive interventions on time or even ahead of time, enabling targeted use of resources.
Adaptive calibration entails using AI to customize calibration processes for individual instruments, based on historical data, usage, and environmental factors. By creating individualized processes for each instrument, AI could extend their useful life and ensure resources are used to their fullest.
Automating and Streamlining Compliance Processes
Recent years have seen an expansion in the regulatory landscape, with an increased demand for calibration documentation and traceability. AI holds the potential to streamline this sometimes-overwhelming process, automating key elements of compliance and freeing up teams to focus on more complex tasks like long-term planning, compliance interpretation, and continuous improvement.
AI automation could speed up the audit process through smart certificate processing: rapidly extracting, verifying, and logging data from digital calibration certificates (DCCs). AI-powered automated risk scoring tools could also facilitate regulatory compliance. And AI tools could conduct anomaly detection, flagging emerging signs of instrument drift in real-time for early corrective action.
A Shift in the Workforce
The infusion of AI into metrology is, by necessity, transforming the workforce and enabling a more agile, strategic approach to metrology. Technicians are shifting into new roles as data interpreters and systems managers, developing new skills in the process. Calibration teams are increasingly equipped with AI dashboards and digital twins. Organizations are adopting Calibration-as-a-Service models that integrate AI, cloud platforms, and remote monitoring — all of which help prepare for the challenges and transformations of the future.
Conclusion: Challenges and Opportunities
As AI matures, industries will need to adopt a sustainable model for integrating it into existing metrology norms and building trust in the new technology. AI has the capability to deliver precision, reliability, and compliance at a massive scale, meeting the needs of modern manufacturing.
The fundamentals of metrology will not change — they are well-served by the detail-oriented, agnostic, pattern-driven nature of AI. However, integrating this new technology into the toolkit will give organizations the competitive advantage they need to face the demanding realities of today’s market.