Tier-one automotive supplier shortens cycle time, and improves standardized work adherence on assembly line it previously considered optimized.
Drishti Technologies Inc., whose AI-powered production technology uses video analytics, data and insights to bring significant benefits to manufacturers and their employees recently concluded a 10-week proof of concept deployment with global automotive supplier HELLA.
Prasad Akella, Drishti founder and CEO, tells IndustryWeek, with the success of the pilot, the group is moving forward with a broader integration. “The first and most direct integration is with the MES, as it immediately opens up the ability to conduct fast root cause analyses using the serial numbers of parts in question,” Akella says. Understandably, COVID-19 has presented unexpected challenges, explains Akella. For example, with frozen travel, Drishti was unable to conduct plant visits. “Therefore, we have developed a remote deployment option for customers that allows them to have the full benefit of Drishti without requiring us to travel and instead leveraging the deep in-house skills of the HELLA plant facilities team,” he says.
“Standardized work is the foundation of our assembly operations, and finding opportunities to improve adherence has the potential to significantly boost our productivity,” said Marcos Aurelio Alves Junior, operational excellence and industrial engineering manager at HELLA Mexico in a statement.
Alves and his team used the AI-generated data points in Drishti’s Portal to pinpoint statistical outliers, cycles that took significantly more or less time than the others. Because of the sheer volume of cycle time data Drishti provides, these outliers were clear indicators that attention was required.
Down to details
HELLA deployed 12 Drishti cameras on an automotive component assembly line in Guanajuato, Mexico. Because HELLA has established a lean philosophy throughout the organization since 2007, the selected assembly line was already a high-performing line in the company. HELLA was intrigued by Drishti’s AI-powered production solution and challenged the company to find opportunities for improvement, even though the line was already considered optimized based on state-of-the-art, non-AI lean methodologies.
Using Drishti Trace, which allows manufacturers to use live and recorded video to learn from what has happened, and Drishti Flow, which adds AI to provide assembly data that lets manufacturers closely monitor and rapidly improve performance, the HELLA team and Drishti jointly identified a number of potential improvements. In some instances, HELLA engineers were able to verify adherence to standardized work and implement improvements to the standardized work to reduce process delays and microstops.
“Drishti Trace lets anyone with access to the Portal go back in time and see exactly what happened on the factory floor,” said Alves. “It solves a number of questions about what happened in the past, making the process to identify deviations shorter and us more assertive in attacking the correct outliers in our histograms. And it’s particularly useful during the coronavirus because it doesn’t require our team to travel to the site to know what’s happening.”
At the conclusion of the 10-week deployment, HELLA saw a significant improvement in productivity on the assembly line. A broader Drishti deployment is currently in the works.
“Drishti’s technology uniquely provides us with information about what’s happening on the factory floor, now and in the past, wherever we are,” said Michael Hammoud, vice president of operations, HELLA said in a statement. “It helps us support our lean practices with data, and use the information we get from the cameras and AI to train our operators, improving their productivity and job satisfaction at the same time. It’s a win-win for the company and our employees.”
Constant improvement
The HELLA team believed the line was already optimized, so the team wasn’t confident that Drishti would uncover more opportunities, says Akella. “However, it soon became clear that several process steps on the line were inconsistent with standardized work, and those deviations were going undetected,” he says. “Despite the previously held belief that the line was optimized, Drishti shed light on further opportunities. Changing behavior on the line is not always easy, but Drishti’s video-backed proof points make it easier to get line associates on board.”
According to Akella, the success of this deployment demonstrates that there is almost always room for improvement. And, the best results come when companies remain open minded and ready to scale.
Open minded. Your industrial engineers have optimized your lines as best they can with yesterday’s technology. Newer technologies like Drishti can shed light on issues that weren’t previously obvious. It’s analogous to imaging your lungs using a stethoscope, an ultrasound scannerA and an MRI machine. The increasing capabilities of the devices give greater insights that lead to better diagnostics. The more open-minded the team is, the more use cases that are constructed and the greater the value from new technologies. Mindset is critical.
Ready to scale. When you decide to make the investment to test new technologies, assume success and be ready to get your CFO’s approval for the broader roll out. Otherwise, you’ve invested significant resources and have no path to scale the benefits across the organization.
