“We needed systems agile enough to basically change the needs and requirements we had for fitting the products out,” confirmed Sunny Bedi, Senior Director, NPI & Program Management, Operations, NVIDIA. “We had a huge amount of touch time for the product engineering team or test engineering team to have to go into the system and update yields or test programs or any other relative data that is important for our factories to know.”
“As we are completely fabless and completely outsource manufacturing, it’s important that the information our factories have is accurate—or else we basically build the wrong part and it goes out to the customer,” Bedi added.
NVIDIA previously used several costly custom applications. The company wanted to simplify and streamline operations to maintain and update the supply chain much faster and with the agility necessary for the product lifecycle, which can be as little as six months.
It chose Serus to improve product engineering productivity, reduce manufacturing errors, increase supply chain velocity, improve chip quality and improve projected manufacturing metrics to improve decision making.
“If I had to summarize, I’d say the benefits for us are increased engineering productivity,” said Bedi. “We used to have a lot of manufacturing errors on the floor. We’d get a call in the middle of the night—China or Taiwan time—and the engineer would be on the phone fixing it. We don’t want product engineers trying to solve system or data problems. It’s a poor use of their time.”
In the end, NVIDIA’s product engineering productivity improved by 40 percent; manufacturing errors were reduced to zero; cycle time for assembly and test improved 15 to 20 percent; and chip quality was improved due to decreased manufacturing deviations.
“If your data is accurate, your information is accurate,” said Bedi. “And if your information is accurate you can make better decisions. Data accuracy is so critical and all of that has been significantly improved by this solution,” he concluded.