Yield Analysis is a Critical Driver for Profitability

One of the most important aspects of any manufacturing effort is the yield of the process. Today, the investment in facilities, equipment and materials is so high that consistently high yields are vital to the profitability of the semiconductor manufacturer. Furthermore, the engineers must get to that consistent high yield as quickly as possible to avoid product delays, A yield ramp delay of 3-6 months is extremely costly, and a 6+ month delay could be catastrophic (bad press, lost business, etc.). An example of this (although not necessarily a chip problem) is the delay that Apple is experiencing with the iPhone X. The later than expected introduction will impact holiday sales for them, resulting in a significant revenue hit. In fact, the stock price fluctuated significantly when the ship date was announced earlier this month.

Identifying and eliminating the source of yield loss is one of the most challenging activities a product or fab engineer will face in his/her job. Yield analysis is quite often high-pressure work, requiring long days and quick decisions based on an incomplete understanding of the situation. Solving a yield issue requires complex pattern recognition skills using limited amounts of data. While fab tools and test equipment generate terabytes of data, knowing what to look for in that mountain of data is a difficult task. Typically, one needs to start with a big picture understanding, by identifying what is failing (failure mode of the IC), and how the failure manifests itself in the process (spatial dependencies, lot dependencies, equipment dependencies, etc.).

The engineer must then formulate hypotheses that fit the “what” and “how”. He or she would then look through the data at hand to try and confirm or deny each hypothesis. If there is insufficient data to do this, one may have to gather additional data. Finally, if there is no data on hand that can conclusively prove an hypotheses, then the engineer would typically submit a sample of ICs for failure analysis to help provide greater understanding of the problem. Once the engineering team identifies the source of the problem, they will develop a fix and implement the fix on a set of control material. If the fix is successful, they can roll it out to the entire production line. Yield analysis is sort of like learning to ride a bike – you get better at yield analysis the more you do it. However, there are some important concepts relating to data visualization, data analysis, techniques, and the overall process for yield analysis. Semitracks has an online course that covers these concepts in more detail (they provide the course as an in-house training course as well).

If you are a product engineer that has the responsibility for maintaining the yield of an IC, if you are a fab engineer who must gather the data for yield work and fix fab-related problems, or if you are a foundry interface engineer who needs to understand yield analysis work in order to make an informed decision about what to do with your products, then going through this type of training is a must. Successful yield analysis work can save your organization millions of dollars. The stakes are simply too high to ignore this.