Measurement Systems

Quick reference

• 00:05 Hi, I'm Ray Sheen.
• 00:06 It should be no surprise to you that during the Measure phase of
• 00:09 a Lean Six Sigma project, the team will be measuring and
• 00:12 how that implies that there's a measurement system.
• 00:15 I wanna take a few minutes and talk about that.
• 00:18 A technique that you'll probably need to do in the Measure
• 00:22 phase is a measurement systems analysis.
• 00:25 We have an entire short course on how to set up and conduct an analysis, but
• 00:29 this time, I want to explain why it is needed.
• 00:32 I hope it's obvious to everyone by now that Lean Six Sigma relies on data.
• 00:36 And to do a full and adequate analysis, that data needs to be accurate,
• 00:40 which begs the question of whether the team can collect accurate data.
• 00:45 A Measurement System Analysis answers that question by determining the amount of
• 00:48 variation in the measurement.
• 00:50 That is due to the measurement system rather than the variation
• 00:54 in the item that is being measured.
• 00:56 If we fully understand the measurement system variation,
• 00:59 it will give us insight into the actual process or product variation.
• 01:04 Without a measurement system analysis or
• 01:05 an MSA, you could reach a wrong conclusion about the process performance.
• 01:10 Typically, it would be to say that the performance was bad and
• 01:13 out of control when it really was not.
• 01:16 Then you start trying to chase down a problem in the process, and
• 01:19 the problem is really with the measurement system being used to measure the process.
• 01:24 Because of measurement system error, you may think that the customer is experiencing
• 01:28 a problem of the result being makes too high when it is really too low.
• 01:32 We don't understand what the customer is truly experiencing.
• 01:36 So let's talk about measurement system error and it's impact.
• 01:39 I'll start with the basics.
• 01:41 All processes have variations and measuring is a process.
• 01:45 Therefore, there is some level of variation associated
• 01:49 with the measurement system.
• 01:51 The measurement variation will cause errors.
• 01:53 If the variation is large the error is large.
• 01:56 And then the process data that you collect with that measurement system is invalid.
• 02:01 I was working with a company last year who was having
• 02:04 a tremendously difficult time with some optical alignment steps in their process.
• 02:09 I had them do a measurement systems analysis,
• 02:11 and they found that the variation in the measurement system.
• 02:14 The error in the system was more than twice what was allowed for
• 02:18 the entire part variation.
• 02:20 The team's ability to ever get anything to work was just plain luck.
• 02:24 That had been the general experience with the product and was the reason for
• 02:28 the Lean Six Sigma project.
• 02:30 To understand the measurement error,
• 02:32 the team needs to understand the design of the measurement system.
• 02:35 And know the status of the maintenance of the system and
• 02:38 by maintenance, the primary item there is calibration.
• 02:41 Measurements and measurement error look like this, we have a right triangle.
• 02:46 The variation in the part that is being measured,
• 02:48 the true variation is represented by the horizontal side of the triangle.
• 02:52 And the variation in the measurement system is represented by the vertical side
• 02:56 of the triangle.
• 02:58 The actual measured variation then is the third side of the triangle.
• 03:02 If measurement error is small the vertical side of the triangle is short and
• 03:07 the measured variation almost exactly match the true part variation.
• 03:11 However, if the measurement error is large,
• 03:14 which means that the vertical side of the triangle is tall.
• 03:17 The measurement variation will be much greater than the two part variation.
• 03:22 Don't get too hung up on the math right now,
• 03:24 we will cover that in more detail in the Measurement Systems Analysis course.
• 03:29 So let's talk about the impact of measurement system error.
• 03:31 Let me use a few illustrations to explain what is happening and
• 03:34 then we can look at the implications.
• 03:37 In the first illustration, the measurement variation is in the middle of the actual
• 03:41 variation and it's much less than the actual variation.
• 03:45 The measurement variation will have little impact on the accuracy of the data.
• 03:48 The second illustration has a large measurement error,
• 03:52 nearly equal to the part variation.
• 03:54 And in particular, it will introduce a significant bias because it is not
• 03:58 centered in the same area as the part.
• 04:02 This third variation will also have a large impact.
• 04:04 While it is centered in the area of the part variation, the measurement
• 04:08 that is taken will likely have very little relation to the actual value of the part.
• 04:13 So what are the implications?
• 04:14 Well one is that we may reject parts that are actually good but
• 04:18 whose measurement values are recorded as bad.
• 04:21 That can create a great deal of wasted effort in a process
• 04:25 because you would be trying to correct or rework a specific part.
• 04:28 And often tampering with the item until it is truly out of spec.
• 04:33 The third implication is that we can have a wrong understanding of process
• 04:37 capability.
• 04:38 This will lead us to spending a lot of time and
• 04:40 effort looking for root causes and process problems that aren't there.
• 04:45 So there can't be many problems getting accurate data if you don't have
• 04:48 a good measurement system.
• 04:50 On many projects I've had to clean up the measurement system before
• 04:55 we could even begin to understand the process.
• 04:58 Accurate data is foundational in any Lean Six Sigma project, if you can't trust
• 05:03 the data you can't trust the analysis and you don't know what to change.

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