Verifying EV battery components are installed correctly, reading direct part marks (DPMs) on curved, specular battery cells, and similar processes are daunting EV manufacturing challenges. An even bigger challenge is creating scalable, adaptable, and cost-effective solutions.
Swapnil Talathi, who leads machine vision and design project management at robotics and automation company Wipro PARI, knows those challenges firsthand.
“We have technical challenges every day, I’m working on numerous projects at any given time,” he said.
Talathi and his team of 25 vision engineers manage 700 machine vision systems on automotive and EV manufacturing lines across 11 countries. They develop automation solutions that improve throughput by inspecting components and guiding parts into place with vision-guided robotics.
Automakers are constantly looking to increase EV production efficiency and machine vision is critical to keeping up with the pace of market and consumer demands. Wipro PARI manufacturing solutions assemble EV battery packs in 62 seconds.
Speed is not the only factor in EV battery manufacturing. Wipro PARI solutions need to maintain extreme levels of accuracy and operate in challenging, unpredictable conditions. Talathi and his team develop solutions in a laboratory, so they can’t account for environmental factors in the field like oil, dust, and low-contrast lighting.
Cognex machine vision systems and barcode scanners help Talathi and his team deliver functional solutions, anywhere, anytime. Cognex systems have comprehensive industrial protocols that seamlessly communicate with a variety of robots while powerful vision tools account for unpredictable variables and sudden manufacturing changes.
While Talathi and his team must address a wide breadth and depth of challenges, the ideal outcome is the same. Successful solutions can be easily maintained by the customer and adapt to new variables, he said. Those are a few of the reasons Wipro PARI partners with Cognex for machine vision solutions.
In one application, Talathi and his team had to develop a verification solution for an EV manufacturer in Asia. Wipro PARI’s system used machine vision to validate a range of battery module configurations while ensuring wiring harnesses and busbars were in the correct position.
“EV battery packs consist of a lot of wiring, harnesses, and cabling,” he said. “If they’re not correct, there could be a major malfunction in the battery pack. That’s where machine vision plays a major role.”
A similar application required a solution to guide EV battery cells into a module, verify the polarity, and read direct part marks (DPMs) throughout the process. Since the location of cells in a module depends on the design of the battery system, verifying cell locations and polarities is too complex for rule-based machine vision.
Talathi and his team combined EtherInspect, PC-based vision software embedded with powerful vision tools, and Cognex industrial cameras to quickly guide cells into a module housing and validate the module’s polarity. EtherInspect allowed Talathi’s team to connect multiple cameras to a single computer, creating a standard, cost-effective solution that reduced on-site commissioning time. Using Cognex edge learning, an artificial intelligence (AI) technology, the solution learned to recognize different configurations of EV battery modules.
Cognex helps Talathi and Wipro PARI manage vision systems across the globe and deliver effective, reliable solutions on time.
“In the future, we will be managing thousands of systems, and Cognex will play a major part of that for sure,” Talathi said.