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Capability Analysis Guidelines

The guidelines listed below are intended to assist in performing a proper capability study for any given process.




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1. Select a candidate for the study. This step should be institutionalized. A goal of any organization should be ongoing process improvement. However, because a company has only a limited resource base and can’t solve all problems simultaneously, it must set priorities for its efforts. The tools for this include Pareto analysis and fishbone diagrams.

2. Define the process. It is all too easy to slip into the trap of solving the wrong problem. Once the candidate area has been selected in step 1, define the scope of the study. A process is a unique combination of machines, tools, methods, and personnel engaged in adding value by providing a product or service. Each element of the process should be identified at this stage. This is not a trivial exercise. The input of many people may be required. There are likely to be a number of conflicting opinions about what the process actually involves.

3. Procure resources for the study. Process capability studies disrupt normal operations and require significant expenditures of both material and human resources. Since it is a project of major importance, it should be managed as such. All of the usual project management techniques should be brought to bear. This includes planning, scheduling, and management status reporting.

4. Evaluate the measurement system. Evaluate the measurement system’s ability to do the job. All sample measurements should be made at one time and with one operator if possible to reduce measurement system noise and the effect of noise on capability. Again, be prepared to spend the time necessary to get a valid means of measuring the process before going ahead.

5. Prepare a control plan. The purpose of the control plan is threefold: 1) isolate and control as many important variables as possible, 2) provide a mechanism for tracking variables that can not be completely controlled, and 3) maintain a record of what was done incase you want to repeat the analysis on another date to insure an ‘apples-to-apples’ result. Specifics regarding the number of samples, sample frequency, sample subgroup size, facility location, equipment identification including measurement tools, time and date, etc. should be recorded to assist in continuing or a possible repeat capability study in order to make all things equal. The object of the capability analysis is to determine what the process can do if it is operated the way it is designed to be operated. This means that such obvious sources of potential variation as operators and vendors will be controlled while the study is conducted. In other words, a single well-trained operator will be used and the material will be from a single vendor. There are usually some variables that are important, but that are not controllable. One example is the ambient environment, including temperature, barometric pressure, or humidity. Certain process variables may degrade as part of the normal operation; for example, tools wear and chemicals are used. These variables should still be tracked using log sheets or other similar tools.

6. Select a method for the analysis. The SPC method will depend on the decisions made up to this point. If the performance measure is an attribute, one of the attribute charts will be used. Variables charts will be used for process performance measures assessed on a continuous scale. Also considered will be the skill level of the personnel involved, need for sensitivity, and other resources required to collect, record, and analyze the data.

7. Subgroup size must be considered or agreed before collecting samples. Short-term capability (Cp, Cpk) require subgroup size input at the time of analysis. If subgroups do not exist, the subgroup size entered into any software application must be the value “1”. If samples are collected at a rate of 5 per hour or 5 per shift, the subgroup size must be the value of “5”.

8. Choose or agree on the frequency of samples to be collected for measurement. It is preferred to collect samples from subsequent runs in order to capture variation over time.

i.e. 120 samples – 1 day, 1 run
  120 samples – 1 day, two runs of 60 each
  120 samples – 2 days, four runs of 30 each

9. Gather and analyze the data. Use a control chart when available, plus common sense. Collect the samples at the first source point, record and maintain the time sequence of manufacturer of each sample. Sequence of manufacture or order of all samples must be maintained since capability (Cpk) accounts for variation over time. It is a good idea to number the samples as they are collected. Do not collect samples from inventory or throughout various stages of in process manufacturing, after all, you are typically measuring a part of the process, not the entire process. Samples must be new manufacture and not collected from existing inventory or stock. It is usually advisable to have at least two people go over the data analysis to catch inadvertent errors in transcribing data or performing the analysis. Measurement data sequence or order must be maintained when entering the data into a computer. Randomizing or shuffling of the raw data can have a significant negative or positive effect on the resulting capability values.

10. Track down and remove special causes. A special cause of variation may be obvious, or it may take months of investigation to find it. The effect of the special cause may be good or bad. Removing a special cause that has a bad effect usually involves eliminating the cause itself. For example, if poorly trained operators are causing variability, the special cause is the training system (not the operator), and it is eliminated by developing an improved training system or a process that requires less training. However, the removal of a beneficial special cause may actually involve incorporating the special cause into the normal operating procedure. For example, if it is discovered that materials with a particular chemistry produce better product the special cause is the newly discovered material and it can be made a common cause simply by changing the specification to assure that the new chemistry is always used.

11. Estimate the process capability. One point can not be overemphasized: the process capability cannot be estimated until a state of statistical control has been achieved! After this stage has been reached, the methods described later in this chapter may be used. After the numerical estimate of process capability has been arrived at it must be compared to management’s goals for the process, or it can be used as an input into economic models. Deming’s all-or-none rules provide a simple model that can be used to determine if the output from a process should be sorted 100% or shipped as-is.

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