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There is no direct relationship between control limits and specification limits. By saying that I mean that one measure has no effect on the other. However, the comparison of these two ranges can tell you a lot about your ability to meet specification.
These terms are most often used, and are thus easiest to explain, in terms of manufacturing a part. Let us assume that we need to cut a piece of metal bar to a length of one inch.
Specification limits tell us what variance is acceptable, either to us or our customer, when we produce the said part. The request for such a part would be accompanied by tolerances and might look something like 1.00" +/- 0.005". This means a part that is between 0.995" and 1.005" in length would be considered acceptable. The two acceptable extremes just cited would be our spec limits. Subtracting one from the other we arrive at a spec width of 0.010".
Now, control limits are strictly a function of the natural variation of the process in question and are calculated using the measured standard deviation of that process. If the control limits fall inside the spec width, let us say we have an LCL of 0.998" and an UCL of 1.002" for our example, then we have process that is very capable of producing in spec parts almost every time. However, if the control limits fall outside the spec limits, maybe 0.990" and 1.010", then the natural variation present in our process causes us to make many parts that will not fall within the required specification. In other words, the process is not capable.
The question about the relationship between spec limits and control limits really comes down to a question about process capability. This was just the briefest of intros to the subject. I suggest further reading (or googling) on the subject of capability (Cp &Cpk).
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What is The distance between consecutive lower class limits is called the?
They are the class widths.
What is the benefit of knowing 3 standard deviations above and below the mean of data from a process?
If the process can be assumed to follow a Gaussian distribution then 99.7% of the outputs of the process will lie between those two limits. That may be of benefit in quality control if it is a production process.
What are the limits on outliers?
there are no limits to outliers there are no limits to outliers
When is the best time to use a histogram?
When you are unsure what to do with a large set of measurements presented in a table, you can use a Histogram to organize and display the data in a more user- friendly format. A Histogram will make it easy to see where the majority of values falls in a measurement scale, and how much variation there is. It is helpful to construct a Histogram when you want to do the following (Viewgraph 2): ! Sum m arize large data sets graphically. When you look at Viewgraph 6, you can see that a set of data presented in a table isn't easy to use. You can make it much easier to understand by summarizing it on a tally sheet (Viewgraph 7) and organizing it into a Histogram (Viewgraph 12). ! Com pare process results with specification lim its. If you add the process specification limits to your Histogram, you can determine quickly whether the current process was able to produce "good" products. Specification limits may take the form of length, weight, density, quantity of materials to be delivered, or whatever is important for the product of a given process. Viewgraph 14 shows a Histogram on which the specification limits, or "goalposts," have been superimposed. We'll look more closely at the implications of specification limits when we discuss Histogram interpretation later in this module. ! Com m unicate inform ation graphically. The team members can easily see the values which occur most frequently. When you use a Histogram to summarize large data sets, or to compare measurements to specification limits, you are employing a powerful tool for communicating information. ! Use a tool to assist in decision m aking. As you will see as we move along through this module, certain shapes, sizes, and the spread of data have meanings that can help you in investigating problems and making decisions. But always bear in mind that if the data you have in hand aren't recent, or you don't know how the data were collected, it's a waste of time trying to chart them. Measurements cannot be used for making decisions or predictions when they were produced by a process that is different from the current one, or were collected under unknown conditions.
What is class limit according to statistics?
The lower and upper limits of a class interval are known as Class Limits.
