ISO 9000 Six Sigma Examples: Two Simple Ways to Meet Requirements

Here are some ISO 9000 Six Sigma examples of how two simple tools can be used to meet some of the requirements of ISO9004 and ISO9001.

If you’re trying to build a better organization, the ISO9000 family of standards contains a wealth of useful information about organizing and structuring your processes. ISO9004 is a broad standard that gives particular emphasis to the organization’s external environment, while ISO9001:2008 pays more attention to internal issues such as creating products or services. Have any questions about the ISO9000 family of standards? Leave us a comment below and we’d be happy to answer them.




If you’re trying to build a better organization, the ISO 9000 family of standards contains a wealth of useful information about organizing and structuring your processes. ISO 9004 is a broad standard that gives particular emphasis to the organization’s external environment, while ISO 9001:2008 pays more attention to internal issues, such as creating products or services. One of the bedrock principles of ISO 9000 is a factual approach to decision making. All other factors equal, data-driven organizations are more successful than those that are not and data and proper analysis tend to reduce the drama associated with 2decisions based on authority or the loudest voice in the room. In this video, I’ll be talking about just two simple tools that help with data analysis and factual decision-making and the ISO requirements that are based on this principle. Those requirements would include monitoring the organizations operating environment, which I’ll talk about first, and ensuring that products meet customer specifications, which I’ll talk about in a few minutes.

Now, I know that many viewers have strong opinions regarding firearms. I don’t mean to stir up a debate, but there is such an excellent example relating to firearms sales in the U.S. that all ask your indulgence for its teaching value. So, suppose for a moment that one of the external factors you need to monitor and analyze is the rate of firearm sales in the U.S. How would you go about your task? Well, the U.S. Federal Bureau of Investigation posts its monthly count of the number of fire background checks on its web page. Practically all personal purchases of new firearms require this check. While it doesn’t perfectly match the number of new firearms sold. It is highly correlated and a very good coincident indicator. Here is the chart that is very useful for monitoring and analyzing the FBI data. No data have meaning without context, so it’s beneficial that we see the data in the order that they were created with a green centerline. That lets us see the context of each month’s number. The chart also provides tests to indicate when something unusual and interesting has happened. When you see a little point outside the red limits or with a little number beside it, that’s probably an interesting event. So if you needed to know about new firearm purchases in the U.S., What does this chart tell us that we need to know? Well, the first thing we see is that whatever else is happening, the trend is relentlessly upward. The probability of getting a slope at least this strong just by random chance is practically zero. The second thing we learn is that the growth is volatile and not stable and predictable. How do we know that? We have numerous indications of unusual change. So while we should plan for growth, we should also plan for volatility. This point on the chart was November 2012, when Barack Obama was elected to his second term as President. What followed was a very statistically unusual all-time record breaking period of high sales. That’s an interesting event. The chart I’m using here is the individuals and moving range chart. You can learn much more about that at our website. It’s fundamental job is to detect extraordinary variation, but it’s also useful in several other ways, such as testing measurement systems and showing the difference before and after a change in the process, and you can plot all your data, or often you can use a much smaller random sample.

Now, let’s use the same chart for something more typical of an ISO 9001:2008 requirement. Let’s apply it to meeting a dimensional specification of a product. Suppose we have to make cuppledapups which have a specification of one inch length, plus or minus 30 thousandths of an inch, and assume that our data looks like this. We have a history of about 100 data with no indication that anything unusual is going on. That’s very good news, if we have allowed all the process input variables and opportunity to express themselves, we have long-term data. We are justified in assuming that the process is stable and predictable. If nothing disturbs that, it will continue to operate with the same center line in between the same limits. Good production processes are boring, not exciting. This is a very very boring process. Knowing that the process is probably stable and predictable lets us predict that future performance will be like past performance but it does not give us information about whether that performance will be satisfactory. After all, a process can be reliably bad. To evaluate satisfactory we, add another tool, the capability study. It uses the same data, but instead of comparing the data to the redlines generated from the data, it compares the data with one or two specification limits, which are the voice of the customer. A capability study compares the voice of the process with the voice of the customer. Our upper limit is 1 inch plus 30 thousandths of an inch or 1.03 inches and our lower limit is 1 inch minus-30 thousands or .97 inches. Entering the limits triggers calculations of PPK, CPK, Pp, and Cp and once again, you can learn much about these four indices at our website. For simplicity, let’s just look at the parts per million defective for the as-is process. Now, of course you can’t possibly predict defects down into the single-digit parts-per-million with 100 samples, not even close, but still this is very encouraging as far as we can tell, this is a Six Sigma process, and one that we can depend on. Either the defective parts per million, or PPK, would make an excellent key process indicator, or KPI.

So there you have it. Two easy tools you can apply for monitoring and analyzing your organization’s external environment and your internal processes. Whether those are expressed as product dimensions or the time required to process an important report, please visit our web page to learn much more about these and related tools you can use. Thanks for watching.

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