Gage R&R. Variation. Allow us to explain with a simple diagram.

Transcription

1 Gage R&R Variation We ve learned how to graph variation with histograms while also learning how to determine if the variation in our process is greater than customer specifications by leveraging Process Capability studies. To be sure, being able to attack variation is an extremely important aspect of continuous improvement. Variation is a tricky opponent. The variation we see isn t always what we think it is. Allow us to explain with a simple diagram. At the top, we see the observed process variation. In other words, this is the data that we d use to conduct a Process Capability Study where obviously, we re interested in understanding how our process variation is behaving. Gage R&R GembaAcademy.com 1

2 Unfortunately, there are actually two things that make up our total observed process variation, the actual process variation and the measurement variation. In other words, it s entirely possible that the variation we re observing is mostly due to the measurement system and continuing to attack the actual process variation won t help at all. Our actual process variation consists of short term, long term, and part to part variation. Measurement variation consists of several characteristics including accuracy, repeatability, reproducibility, stability, and resolution. Measurement System Characteristics Let s spend some time discussing each of these important measurement system characteristics. First, accuracy is the ability of the gage to measure the true value of a part on average. In other words, it s possible for a measurement system to have high variability but still be accurate so long as the average value of the measurements are close to the true value. For example, let s assume we re aiming for the bulls eye and even though we don t hit the actual bulls eye, the average of our shots are, on average, close to the middle meaning our shots are accurate. Next, repeatability, which is a component of precision, is attained when the same person takes multiple measurements and gets the same, or similar, results each time. In our dartboard example, we now see where our four shots are highly accurate and precise. The fact the shots are so tightly grouped together is what makes them precise and repeatable. In this example, the four shots are no longer accurate, since their average position isn t close to the bulls eye, but the shots are still precise and highly repeatable since they are close to one another. Gage R&R GembaAcademy.com 2

3 A close cousin to repeatability is reproducibility, the second component of Precision. Reproducibility is attained when other people get the same, or similar results, you do when measuring the same item. While repeatability focuses on how well you measure something, reproducibility compares your measurement performance to other people s measurement performance. Next, stability is attained when measurements taken by the same person, or gage, vary little over time. In other words, it shouldn t matter what day of the week or time of day it is. We should always be able to measure in an accurate and repeatable manner. Last, but certainly not least, sufficient resolution means that your measurement system provides at least five, more preferably, distinct values in the range you re measuring. Sufficient Resolution For example, let s say we wanted to measure the heights of these three children with a scale that only measures to the nearest foot. When we did this, our results were 3 feet for child 1, 4 feet for child 2, and 5 feet for child 3. In other words, we only had three distinct values. As it turns out, the key to ensuring we have adequate resolution is by determining the amount of discrimination our scale needs. Discrimination refers to the number of decimal places that can be measured by the system. Increments of measure should be approximately one- tenth of the width of the product specification or process variation. For example, let s say that we re working with a process that has an upper customer specification limit of 80 mm and a lower customer specification limit of 60 mm. Gage R&R GembaAcademy.com 3

4 When we subtract 60 from 80, we learn that our tolerance is 20 mm. In other words, this measurement system needs to be able to discriminate to at least 2 mm since 20 mm divided by 10 is 2 mm. We ve covered a lot of terms and concepts so far which may make you feel a little overwhelmed. The good news is we have an extremely powerful tool at our disposal that wraps everything that we ve discussed up into a single statistical tool called Measurement Systems Analysis, or MSA for short. Measurement Systems Analysis Defined, MSA is used to quantify the amount of variation attributed to the measurement system rather than the product or process being studied. In other words, MSA allows us to understand how much of our observed variation is being caused by the measurement system. When we re working with variables or continuous data, we ll conduct what are called Gage R&R studies which is short for Gage Repeatability and Reproducibility Studies. Gage R&R GembaAcademy.com 4

5 When we re working with attribute data, we ll conduct Attribute Agreement Analysis. To be sure, MSA can be used throughout the DMAIC process. In fact, you don t even need to be doing a formal DMAIC project to conduct an MSA. As it relates to the DMAIC roadmap, MSA s are usually done during the measure, analyze, or improve phases. Anytime you re relying on data to make decisions, you should verify the measurement system can be trusted. In fact as an aside, I once worked with a team to improve the performance of a visual measurement system. We spent around seven hours on the issue and the results were extraordinary, since as it turned out, this company was scrapping hundreds of thousands of dollars each week since their measurement system was rejecting good parts. Let s spend some time working through an actual example where we re going to imagine we work for a company that produces nuts and bolts. For this particular study, we want to know if we re able to trust the measurement system used to measure the widths of the nuts that have a process tolerance of 0.5 mm. Gage R&R Study Since measuring the width of anything results in variables, or continuous data, we ll be performing a Gage R&R Study. For this study, we ve chosen three operators, Bill, Kristen, and Tom, who will all use the same digital caliper to measure the widths of the 15 nuts that were selected. All three operators will measure these 15 parts two different times. In summary, we have three operators, 15 parts, and two trials. Setting up a Gage R&R study is important so here are some suggestions. First, you should randomly select between two and four operators. We find three to work extremely well. Next, the number of parts used should be enough so that when we multiply P, the number of parts, by O, the number of operators, the result is greater than 15. Gage R&R GembaAcademy.com 5

6 If this isn t possible or practical, you ll want to increase the number of trials accordingly. We must do at least two trials, but for example, if P times O is less than 15, we d want to do three trials. We can use some simple math to ensure we set things up properly, but we can t use math to help with what we feel is the single most important aspect of an MSA, and that s setting the operators' minds at ease. If an operator has never been part of a formal MSA study, chances are very good they re going to be extremely nervous. Some may be downright scared. It s absolutely critical that you let them know the point of the study is to better understand the process and that no one will be in trouble if they do poorly. To give you an idea of how this type of study is actually done, let s watch one of the operators, Kristen, measure a few parts. Once all three operators have completed both trials, we ll use Minitab to calculate the results. Calculating Within Minitab The first part of the Minitab output is a standard ANOVA table like we ve seen in previous lessons. The Part P- value is 0.0 which means that the Part to Part variation is statistically significant. The interaction of Part x Operator is also statistically significant since its P- value is.016. First, the % Contribution section summarizes the percent of the variation that each component contributes to the total variation. The % Study Variation section summarizes the standard deviation percentage of each source to the total standard deviation. And the % Tolerance section summarizes the percentage of variation of each source compared to the part tolerance. While every organization will need to determine this for themselves, the Automotive Industry Action Group has come up with some suggestions as to how to interpret these values. Gage R&R GembaAcademy.com 6

7 Specifically, they suggest that % Contribution values less than 1% represent an acceptable system. While % Contributions between 1% and 9% represent marginally acceptable systems. Anything over 9% is considered unacceptable. For % Study Variation and % Tolerance, acceptable values are anything less than 10%, while marginal systems will be between 10% and 30%, and anything over 30% is considered unacceptable. When we look at the results of this study, we see a Total Gage R&R Percentage Contribution value of 3.5% which could be considered marginally acceptable since it s between 1% and 9%. Minitab also shows us how this value is derived, namely 2.31% is due to repeatability, or within operator variation, while 1.19% is due to reproducibility, or between operator variation. These values can help us understand where to focus our attention as we work to improve the system. Minitab also breaks the reproducibility values down by operator and the operator by Part interaction in this section. Finally, the Part to Part variation is noted here. Since our goal is to ultimately measure individual parts, we want to see this variation figure high since this means we re able to distinguish the difference between parts. In the next section, we see our % Study Variation is 18.71% and our % Tolerance is 13.85% which means again, we re working with a marginally acceptable measurement system. Minitab also breaks these values down into finer increments here just like we saw in the section above. Last, but certainly not least, our number of distinct categories is seven. Again we d like to see this value greater than five which this value obviously is. In addition to these statistics, Minitab provides some nice graphs of this same data. Gage R&R GembaAcademy.com 7

8 In the components of variation section, we see a graphical view of the different variation sources. Again, we want to see our Part to Part variation higher than everything else since that means we re able to distinguish between parts. Here we see an R Chart by Operator. This is helpful as it can tell us where individual operators struggled. You can see where Tom, the third operator, obviously struggled with two parts so we may want to visit with him in order to better understand what may have caused this issue. In a perfect world, we don t want to see any special cause variation in this R chart, but as long as we intend to identify and counter the root cause of this variation, it s normally okay to press on unless we see wildly out of control variation across all operators. The Xbar Chart by Operator graph is an interesting one since contrary to any other control chart we ve ever looked at in this course, we actually prefer to see special cause variation since this represents part to part variation, which again, is what we ultimately want to measure. In this graph, we see Data by Part. This can help us identify if one part was harder to measure than another. For example, it seems like part 14 has the most variation. Perhaps there s something about this part that makes it hard to measure. In this section, we see the Data by Operator, which again, can be very useful information to help us work with each operator when applicable. Finally, here we see the Part x Operator Interaction graph. If we remember, we saw a P- Value of.016 for this interaction which means it is statistically significant. As we can see in this graph, it seems like the operators struggled a bit with part 9 and 14 so we d definitely want to take a look at these parts to see if there is anything we can learn and improve. Conclusion In summary after looking at the results of this Gage R&R, we d conclude that this measurement system is marginally capable. Some next steps may include Gage R&R GembaAcademy.com 8

9 investigating the measurements with high ranges while also trying to understand why some parts were harder to measure than others. We d then want to repeat this study as needed. For example, if we gained an understanding of what made part 14 so hard to measure and we're able to implement a countermeasure, we could repeat the study and see how we do. We d also want to repeat the study with different operators while also doing the study with this same group at a later date to ensure that the measurement process is stable over time. Gage R&R GembaAcademy.com 9