Interpretation & Calculations
The following is an excerpt from The Quality Engineering Handbook by Thomas Pyzdek, © QA Publishing, LLC.
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 cannot 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. Using the techniques described in Chapter V, evaluate the measurement system ability to do the job. 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 twofold: 1) isolate and control as many important variables as possible and, 2) provide a mechanism for tracking variables that cannot be completely controlled. 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 logsheets and similar tools. See Chapter II.C for information on designing data collection systems.
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. Gather and analyze the data. Use one of the control charts described in this chapter, plus common sense. 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.
8. 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.
9. Estimate the process capability. One point cannot 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 goals for the process, or it can be used as an input into economic models. The Deming all-or-none rules (see VI.E.2) provide a simple model that can be used to determine if the output from a process should be sorted 100% or shipped as-is.
10. Establish a plan for continuous process improvement. Once a stable process state has been attained, steps should be taken to maintain it and improve upon it. SPC is just one means of doing this. Far more important than the particular approach taken is a company environment that makes continuous improvement a normal part of the daily routine of everyone.
Learn more about the SPC principles and tools for process improvement in Statistical Process Control Demystified (2011, McGraw-Hill) by Paul Keller, in his online SPC Concepts short course (only $39), or his online SPC certification course ($350) or online Green Belt certification course ($499).