The Decade Ahead: The Changing Role of Metrology in Tomorrow’s Manufacturing
In the following article Gary Peacock, General Manager, Metrology Software, at Hexagon Manufacturing Intelligence explains his vision for the future of manufacturing metrology and how quality control is evolving for the next decade.
“As the demands of modern manufacturing grow more complex and manufacturing industries continue their digital transformation, the place of metrology is undergoing a fundamental shift as traditional approaches to quality control are being upended.”
“Data, connectivity and collaboration are central to any vision of the future of manufacturing and are the most significant change drivers for enhancing quality and productivity. These, and the accelerating ‘shift left’ in quality control, will see metrology teams taking a more central role across the entire product lifecycle as they harness cutting-edge technologies to become key drivers of innovation, integrating design, production, and quality like never before.”
From Tribal Knowledge to Industry Standards: Prioritising Data Quality
Data is at the centre of smart manufacturing – decisions about quality and productivity hinge on the availability of accurate, timely, and complete data. But, most manufacturers struggle with data quality, which hampers decision-making and effective quality strategies.
From the perspective of metrology, one of the vital requirements is to establish best measurement practices and data integrity across manufacturing by improving compliance with global industry standards such as ASME and ISO. This requires hastening the move from the unsustainable traditional reliance on the siloed expertise held by individual experts – “tribal knowledge” – which is given increasing urgency by rising manufacturing complexity and the growing skills gap due to the retirement of experienced metrology professionals.
To this end, technology providers like Hexagon are responding by focusing on software and hardware innovations that more efficiently deliver rapid, reliable, and repeatable measurements to enable manufacturers to accelerate their time-to-market while safeguarding product quality.
Simplifying the complexity inherent in metrology systems is also crucial to this effort. Making measurement, reporting, and analysis more intuitive and accessible to less experienced users, better ensures data quality and integrity while also addressing the growing skills gap.
Automation is already a key enabler here and will, of course, play an ever-expanding role. For example, we can already automate the creation of CMM measurement programs for prismatic parts directly from computer-aided design (CAD) data. As software capabilities advance towards more autonomous solutions, the trajectory is towards automating the entire measurement process for any part across all stages, from programming and executing measurement routines to reporting and analysis, minimising manual intervention and enhancing efficiency.
Many portable metrology devices can also share in the benefits of automation, paving the way for diverse, innovative applications. For example, we’ll see more in-line systems and the expanded use of metrology-assisted assembly and manufacturing systems, including laser tracker-guided robotic automation and automated guided vehicles (AGVs) in manufacturing.
Naturally, not all measurements can or should be automated; certain tasks will always best suit manual inspections, using, for example, portable measuring arms or handheld scanners.
From Reactive Measurement Centres to a Pivotal Role in Connecting and Fostering Collaboration
Manufacturers are under increasing pressure to bring better products to market quicker than ever and more sustainably. But quality challenges remain prevalent, with unanticipated quality problems and poor product quality being common issues.
This is accelerating the move from the traditional reactive model of quality control, which sees the role and place of control inspections as verifying product quality at the end of the production process, towards a much more proactive stance towards quality management.
A recent industry survey revealed that 43% of manufacturers see value in prioritising final quality and manufacturability earlier in the process. Metrology is central to this ‘shift left’ approach, which emphasises detecting and resolving potential quality issues as early as possible in the product lifecycle. Metrology data will be increasingly applied in connected digital systems that enhance quality at every stage of the manufacturing value chain, from design to final assembly.
This means, metrology offices will need to ensure an integrated technology stack of systems and processes that allow the most effective sharing and use of accurate, trustworthy quality data by teams across the value chain – both downstream and upstream. Every CMM, portable measurement device, sensor, and every piece of software in a manufacturer’s facility or facilities needs to be connected, with data as the connecting thread.
The need for connectivity and collaboration applies just as much to metrology and QA teams themselves, which are less likely to be in a single location, with many of the skills and capacity scattered across buildings, sites and countries.
For data and collaboration to deliver maximum value, they need to span the design, manufacturing and inspection phases – and even beyond to customers and their suppliers. The most immediate opportunities lie in enhancing collaboration between quality control, design, and production teams.
Metrology-Informed Simulation
One of the most exciting and fruitful areas of enhanced connectivity and shift left collaboration is the integration of real-world measurements into digital simulations and virtual prototypes. Here metrology data is used to improve and validate process re-simulations, enabling engineers to predict and compensate for factors like material deformation or geometric tolerances. This allows manufacturers to improve design for manufacturability, production processes, and predict potential quality issues before physical manufacturing begins.
There are notable examples of this now, like 3D printing geometry compensation and in virtual assembly solutions. Growing use in a variety of processes across industries in the coming years will bring hitherto unprecedented levels of control and efficiency to these manufacturing stages.
Not Only Dimensions and PMI
The scope of measurement is expanding. In the next 10 years, the metrology office will no longer focus only on dimensional accuracy but will also increasingly need to assess if a component is structurally sound.
Non-destructive evaluation techniques, like CT scanning, ultrasonics and surface roughness are therefore also a key part of the quality story. When worked into simulations, we get not only the dimensions but also the internal characteristics and features we should be measuring for and the tolerances we should be measuring against. This multilayering of dimensional and internal analysis is becoming increasingly important
AI is Transformative
Big data analytics, machine learning, and AI will, of course, be some of the most transformative forces in quality control and assurance.
AI is a critical component of our metrology journey; it’s essential to deliver the capabilities required to drive quality at the speed we need. AI is the answer to leveraging value from the massively increasing volume of available data and discovering hidden correlations to boost efficiency and keep manufacturers competitive.
AI gives a brain to automated processes: The shift from autonomy to “autonomous” centres on integrating deep learning models to create self-learning, self-adapting systems. As these systems process more data and gain experience, they progressively develop deeper expertise and domain-specific knowledge.
But more than this, the concept of autonomous extends beyond the measurement processes; it’s also about creating a closed loop that feeds insights back into the manufacturing workflow.
The ultimate goal for self-learning systems is to progress beyond predictive capabilities toward being genuinely dynamic and prescriptive. Such systems will not only find the causes of non-conformance and other quality issues but also provide clear remedial actions or implement the necessary adjustments autonomously. This level of intelligence will unlock huge improvements in quality management.
Adding AI to metrology-informed simulation workflows enables closed-loop dynamic inspection, where data-driven AI decision-making gives us a dynamic understanding of what we should inspect. It ensures we only measure what we need to measure, saving time, effort and costs.
AI In Metrology Product Development
Manufacturers are asking for more flexible and intelligent metrology apps to support the increasingly complex challenges of modern manufacturing and to help close skills gaps.
To meet these needs, we’re beginning to see an evolution from the classic types of metrology software towards new kinds of modular structures. AI is key in this transition, where it is being used to query the metrology codebase to gain a deeper understanding of what each part of the code is doing.
This understanding allows for rebuilding functionalities in myriad efficient, modular structures. It will unlock a vast ecosystem of reusable modules, allowing for quicker integration of new features and capabilities in agile development processes and enhanced collaboration with manufacturers to satisfy their specific measurement and QA requirements.
Human Expertise Remains Essential
AI systems will augment an individual’s abilities, rather than replace them. Human expertise will remain crucial, and AI will not take over everything. Experienced people bring contextual understanding and judgment – they will aid in refining the models and will still need to judge if something is sensible. AI will support quality professionals who, as domain experts, will have the time and capacity to use their abilities more strategically and concentrate on activities that bring the greatest value.
Metrology Data Will Bring Design, Manufacturing, and Inspection Phases Closer Together
As manufacturing continues to transform, the role of metrology and the metrology office is expanding in scope and influence. In line with the broader shift in how quality is perceived and best managed, metrology teams will be tasked with reshaping measurement and quality control processes into fully digitised end-to-end processes to foster a more integrated and collaborative approach to manufacturing.
They will work within an expanded value chain and much deeper integration of upstream and downstream workflows. In particular, metrology data will bring the design, manufacturing, and inspection phases closer together.
By prioritising data quality, fostering connectivity and collaboration, leveraging advanced automation and AI technologies, and maintaining a balance between these and human expertise, metrology is set to drive continuous improvement and help solve challenges across the entire value chain.
For more information: www.hexagon.com
About the author: Gary Peacock joined Hexagon in 2019 and leads the Metrology and Data Management software business Unit. He has over 30 years of commercial, operational and management experience having worked with leading providers of technology solutions across many manufacturing, metallurgical and chemical industries.
