Relationship between specification limits and control chart

Specification Limits: Proceed with Caution | iSixSigma

relationship between specification limits and control chart

This article upon Relationship Control Limit Specification Limit is posted to have a better understanding for the students. Control Limits are the Limits of Variation that is expected from a process when the Control Chart. Figure 1 shows how a control strategy based on specification limits works: Good the yellow polynomial fitting line in the chart – could be reduced to short-term. What happens if the spec limits fall between the control limits control charts and the difference between specification limits and control limits.

Notice how this function continually drives a process at its target under conditions of minimum variation. Typically, this function is multiplied by a constant, which turns the loss into estimated dollars used here.

Control Limits and Specification Limits - SAP Documentation

The Taguchi Loss Function is an easily calculated, production-run metric that reflects both process variation over the course of the run and the quality of its targeting. An Under-control Process The following example helps show the differences in process management between specification-based and statistically based strategies.

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Figure 3 is a typical Shewhart chart used for monitoring and controlling the relative viscosity RV of a nylon 66 polymer. Generally, the RV measurement system itself is a very good one, contributing just 2.

Note too, that none of these data points — RV measurements made every 12 hours — fell outside the specification limits.

relationship between specification limits and control chart

In-process Relative Viscosity Data Production management is usually happy with a run like this, as nothing was produced outside specs. However, depending on their tolerance for variation, the customer might not be happy. Initially, the customer could receive a polymer with an RV well above target area B in Figure 3followed by a polymer with an RV well below target, and then again above target area C.

The circled regions in Figure 3 each had data points falling outside the control limits; If the process was being managed statistically, these regions would allow the line engineer to make adjustments to re-target the process.

relationship between specification limits and control chart

The capability metrics of the process tell the story. Its Cp, or the voice of the process, is a very capable 1.

relationship between specification limits and control chart

Finally, the quality of the process targeting is evident in the Taguchi Loss Function Figure 4which is clearly asymmetrical — it is weighted to the high side of target. This is a crucial distinction that is frequently confused.

The differences between control limits and spec (specification) limits

Basically, specification limits have to do with the voice of the customer while control limits have to do with the voice of the process. First off, what are the specifications? Specifications define the allowable deviation from target or nominal.

relationship between specification limits and control chart

Target and nominal are frequently, but not always, the same. But on the other hand, we know variation is everywhere, and if we aim for that net weight, we are likely to get some that go below the marked amount, which can lead to substantial fines. How is the nominal determined? Strictly speaking, the true nominal is the point at which the process losses to both you and your customer and end-users are at a minimum. In my experience, however, the difficulty of performing this calculation means it usually is not done and the supplier ends up determining the nominal based on internal losses or using an industry standard nominal.

relationship between specification limits and control chart

The allowable variation around the nominal is also ideally based on losses. The specification limits should be placed at the point s where the losses due to the variation at the supplier, customer, and end-user are equal to the benefit of the product. Again in practice, this is sometimes difficult to quantify.