As the electric vehicle (EV) market matures, the demand for precision, speed, and consistency in battery manufacturing is increasing
As the electric vehicle (EV) market matures, the demand for precision, speed, and consistency in battery manufacturing is increasing. Quality control challenges in battery cells, modules, and packs are pushing OEMs and suppliers to rethink their inspection strategies, especially as production scales into the hundreds of thousands and beyond
Hexagon, a global leader in metrology and manufacturing intelligence, is at the forefront of this evolution. Leveraging industrial computed tomography (CT), software automation, and advanced analytics, Hexagon is enabling automotive manufacturers to inspect and validate critical internal battery components in a fraction of the time once required. At the heart of this transformation is VGStudio Max, Hexagon’s CT data analysis software, now integrated into cloud platforms and scalable inspection workflows.
“Automotive battery manufacturing is incredibly complex. Something as simple as the ‘exit angle’ of a cathode can make or break the performance and safety of the battery,” explains Roger Wende, senior business development manager at Hexagon. “In some cases, we’ve seen engineers spending up to an hour manually inspecting a single battery using basic tools. It’s just not sustainable when you’re trying to ramp up to production volumes.”
INTERNAL DEFECT DETECTION
Unlike traditional non-destructive testing, CT scanning allows engineers to peer into the internal structure of batteries, layer by layer, without disassembly. From detecting voids and cracks to verifying correct stacking of anode and cathode sheets, CT provides volumetric data that is essential for quality assurance.
“We’re looking at things like curvature, exit angles, and overhangs,” Wende says. “If that exit angle is too steep, it could cause short circuits or failures under stress. CT lets us quantify these variables with precision, and then our software automates the analysis.”
The data captured by CT is rich and detailed, which also means it is massive in size. This is where VGStudio Max comes in. Originally developed to visualise large datasets, the software now includes advanced modules for nominal/actual comparisons, wall thickness measurement, and porosity analysis.
AUTOMATING ANALYSIS
Not only is manual inspection slow, but it can also be inconsistent. Battery manufacturers are increasingly turning to automated CT data analysis to drive throughput and repeatability.
“Once you’ve got the CT scan, you don’t want someone sitting there clicking through 500 layers by hand,” Wende notes. “Our tools can automatically identify and measure key features like cathode overhang or anode count and then flag any anomalies based on tolerances you’ve defined.”
VGStudio Max allows users to apply tolerances directly to critical features – such as maximum curvature or minimum electrode separation – and automatically categorise parts as good or bad. The software can also generate detailed visual and statistical reports to support traceability and root cause analysis.
“What we’re most interested in is understanding why a battery fails inspection,” says Wende. “Show me the report, show me the image – let me see if it’s a real failure or not. That kind of root cause capability is a game changer.”
PROCESS OPTIMISATION
In addition to informing quality assurance, inspection data also feeds process improvement, Wende says. By tracking key performance indicators (KPIs) over time, manufacturers can detect early signs of drift, equipment wear, or material inconsistency.
“Let’s say you’re measuring the exit angle or the average thickness of the electrodes,” he explains. “You can put those KPIs on a dashboard, visualise the trends, and correlate them to upstream changes. Did something go wrong with the welding machine? Are we seeing more variation from a particular supplier? CT helps you answer those questions.”
And as manufacturers seek to improve first-time yield, software tools are evolving to support statistical process control (SPC) and machine learning. “Some of our newest developments include machine learning-based deep segmentation,” Wende adds. “That means faster defect detection and more intelligent sorting – even with noisy or complex data.”
SCALING UP
Hexagon’s software suite is increasingly cloud-enabled, designed to operate across global manufacturing networks. In particular, the integration of VGStudio Max data into enterprise systems like Q-DAS (Hexagon’s quality data management platform) is enabling batch-level and longitudinal analytics.
“Every car door manufactured in Germany probably has Q-DAS behind it,” Wende says. “Now, we’re bringing CT inspection data – originally a standalone desktop process – into the same ecosystem.”
This integration is crucial for scaling up. “We’re not just sampling one in 100 anymore,” he explains. “The goal is to scan every single battery. That’s the holy grail. But to do that, you need fast CT hardware, smart automation, and enterprise-level software to handle the data.”
Hexagon is also pushing CT into real-time workflows. With recent developments, VGStudio Max can now operate in dynamic mode, accepting laser scanner data in real-time and feeding it into live analysis routines, including surface roughness checks and weld inspection.
APPLICATIONS BEYOND AUTOMOTIVE
While automotive remains a primary driver, other industries are taking notice.
“We’ve had aerospace teams borrowing tools from automotive,” Wende says. “They’re looking at CT for similar reasons – safety, performance, and traceability – but with even tighter tolerances and lifespans.”
Even in heavy-duty applications like rail or aerospace propulsion, the same concerns apply. “You’re dealing with high current and energy density,” Wende continues. “Whether it’s a passenger EV or an aircraft battery, defects in welds or materials can be catastrophic.”
One particularly challenging component is the hairpin. These tiny copper elements, which are key to EV motor performance, must be manufactured with extreme consistency to avoid torque ripple and electrical faults.
“Every motor can have over 200 hairpins. If any of them are even slightly off, it affects performance,” Wende explains. “We do a lot of optical scanning there, but CT helps us verify internal welds and voids.”
DESIGNING FOR MANUFACTURABILITY
According to Wende, the biggest gains for OEMs come not from post-production inspection, but from designing out defects before they can occur.
“No one wants a battery to go into a car with a problem,” Wende says. “The earlier you detect and solve those issues, ideally in design or pre-production, the lower your costs and the higher your yields.”
This philosophy underpins Hexagon’s broader strategy: integrating inspection, design simulation (via tools like Digimat and Nastran), and manufacturing planning into a unified digital thread.
“Because we’re part of Hexagon, we’ve now got teams working across all domains—metrology, FEA, additive manufacturing, and so on,” Wende says. “It’s all about building smarter workflows that scale.”
As the EV industry continues to transition to high-volume production, the need for scalable, automated, and intelligent quality control systems will be critical. Industrial CT, coupled with powerful analysis software like VGStudio Max, is helping manufacturers to detect and prevent defects, optimise processes, and ultimately deliver safer and more reliable vehicles.
“We’re still immature as an industry,” Wende concludes. “Everyone talks about EVs, but actually building them – at quality, at scale – is incredibly hard. The good news is, with the right tools, it’s becoming achievable.”
