# DFM for Non-PhD's: Part 2 - Reliability

### David Abercrombie

Posted Jun 19, 2009

One of the fundamental questions everyone asks about DFM is “why should I do it?”

On the one hand this always strikes me as a funny question. I always look at DFM in the same way I think of automobile safety. Statistically, most people never get in a serious accident. So why would you spend so much money on airbags, antilock brakes, better seat belts, side door reinforcements, traction control, etc. It probably adds 20% to the cost of the car and makes it take longer to get cool new designs to the market. The reason is, you don’t want to be the one in the tail of that statistical distribution.

My previous blog talked about the risk of yield variability due to manufacturing interactions with the design. I talked alot about the two or three designs on my chart that were having issues. However, did you notice that the large majority of the designs followed the curve as expected? You aren’t doing DFM because you will get a yield problem, you are doing DFM because you might get one. It is always a matter of statistical probability. Doing DFM just moves you farther from the tail of the distribution.

The other thing I did want to clarify with this blog was that it is not only a matter of yield. Yield seems to be what everyone brings up when discussing DFM. I think it is just easy to relate yield to the bottom line. One of the other areas that DFM can have a really important effect is in reliability. I have been working with several customers who are in the automotive or military product space, and reliability means alot more to them than yield. However, I don’t think a customer return for quality ever helps anyone in any product space.

When I used to work at LSI Logic we did some big studies in the yield and reliability space and there was some really good material published on the results. It was primarily focused on improving test coverage but I think it is very applicable to the DFM subject. The following chart shows a correlation over three process nodes in which we tracked the defect density (lower Dd equals higher yield) and reliability failures.

Correlation over three process nodes of yield to reliability

You can see that as the defect density decrease (yield got better) in each technology node the reliability failures (EFR – Early Fail Rate0 also decreased accordingly.  It suggested a strong correlation between the two. So to investigate further we did a controlled split experiment.

Die that "almost failed" test ended up failing in burn-in reliability screening

In the wafer map in the bottom right of this picture you can see a map of some of the parametric tests that were done at wafer sort. This is a map of the min-VDD voltage at which the die would function properly. All these die passed the test, but you can see a strong variation from one side of the wafer to the other. This is typical of systematic variation in the processing of the wafer in which etch, photo or other process cause slight variations in gate length or other things that cause the chips to behave slightly differently. What is interesting are the four die that are circled. They are no worse than the die on the left of the wafer and they pass the test. However, in their “neighborhood” of other die they are clearly outliers. In the table on the right of this picture, we split the “normal” passing die from the “outlier” passing die on 14 different wafer lots of the same product. We then ran burn-in reliability stress testing on both groups. In the “Total” row you can see that the “normal” group failed 0.22% of the time and the “outlier” group failed 10.72% of the time!!!

The key is that these outliers are die that almost failed. The TEM cross section picture in the upper left of the picture shows the failure analysis result from one of these “outlier” die that passed wafer sort test but failed reliability testing. You can see that the tungsten was missing from the via, but the liner was pretty much in tact. It conducted current, but very poorly. With the accelerated stress of burn-in the liner broke down and it failed. The bottom line is that the “outlier” die are those ones that needed the extra safety gear in the car. The same things that help make you robust for yield, also make you robust for reliability.

So who thinks a seat belt is worth the extra time and money now?

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Hi, nice explanation on the relevance of DFM for yield and reliability. I like the extended analogy to car safety gear. But one minor nit pick is that DFM is more like anti-lock brakes or traction control than say seat belts. I mean seat belts are for after the fact whereas the other devices may prevent you from getting into a jam. If I'm thinking about this correctly, DFM also pushes you away from the bad zone but it will do nothing for you if you already suffer from yield or reliability problems.

Dae-Jin Kim
4:19 AM Jun 25, 2009

Thanks for the feedback! You are correct in your clarification. You can't do DFM after the design is in production! Like health care in real life it is difficult to get people to invest in preventative care. They always wait until the emergency room and then ask for the cure.

David Abercrombie
5:38 AM Jun 25, 2009

hello David, Nice reading here. do you have screen shots of some of the defects which are caused by only following normal DRC's. Or some statistical data showing how following certain DFM rule helps early warnings in design cycle.

Mahendra
9:39 AM Aug 18, 2009

hello david, can you share some of the screenshots of the defects actually seen while doing fabrication, which otherwise would not occur if proper DFM rules are used. if you can share the statistics of design going through fabrication process much ease with DFM rules applied in Physical verification?

Mahendra
6:42 AM Aug 19, 2009

Mahendra, Thanks for the question. I just posted a new installment call DFM for Non-PhD's: Part 3 - Real Life Examples. I hope this fulfills your request.

David Abercrombie
8:57 PM Aug 20, 2009