yieldHUB helps Raspberry Pi to high volume manufacture
Raspberry Pi is a computer company based in Cambridge, United Kingdom. Founded in 2012, the company's mission is to democratize technology for people and businesses all over the world by removing the cost burden that has been a traditional barrier to entry in computing technology.
Raspberry Pi's flagship microcontroller, RP2040, brings the company’s signature values of high performance, low cost, and ease of use to the microcontroller space. Raspberry Pi engineer Jon Matthews said he’s been using yieldHUB which has helped them as they’ve gone into volume production.
“Ensuring consistent quality in manufacturing RP2040 requires us to monitor and analyse all aspects of test results. yieldHUB fits nicely with Raspberry Pi’s IC manufacturing flow. With large volumes of test data sourced from multiple OSATs, yieldHUB automatically loads processed data into relevant databases, tagged by data source,” Mr Matthews said.
“This provides a simple overview of all test activities which can be sorted or filtered on a variety of different fields, quickly containing the volume of the information displayed. Filtering by product is a typical example.
“We are extremely pleased with yieldHUB and its ability to cope with our high production volume: over 20 million units over RP2040’s first year of production. It is a refined tool that presents information in a clear and concise manner, backed up by a suite of analysis tools.”
The manufacturing flow starts with foundry WAT data, which has a unique data format and its own database.
“Something that’s very helpful to us is the ability within yieldHUB to click and drill down, by test or by part. ”
“The “Per Site Trend” feature in yieldHUB allows us to analyze over many silicon lots in order to identify long-term trends in identical measurements and also flags any wafers with significant deviation from normal. These will be noted and observed during later manufacturing stages, potentially receiving a more in-depth examination.
“As ATE results are received, lot-to-lot comparisons of consolidated data provide a good initial overview. Ready-made graphs for trends over the last five lots are simple and very informative: great for reporting metrics to a wider company audience.
“From these graphs, it is simple to spot trends, and on many occasions we can make an initial cause diagnosis with colored site information, allowing immediate identification of issues with test or test setup.”
For every tested lot Raspberry Pi use the “Standard Report” feature with a focus on the highest failing tests.
“Typically, we will look at parametric results, reviewing distribution and building a mental image of lot behavior. Something that’s very helpful to us is the ability within yieldHUB to click and drill down, by test or by part. This is a good way to bring forward more detailed information.
“For reliability qualification and monitoring, the variance between read points is very important. After identifying tests with the largest drift, it is a simple matter to plot the read point history on a single graph.
“From a test program development perspective, the “Multi Test Histograms” are extremely useful for comparing and contrasting tests with the same units. For example, it is possible to compare different microcontroller sleep modes and verify expected behavior.”