Page 209 - The Handbook for Quality Management a Complete Guide to Operational Excellence
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196    P r o c e s s   C o n t r o l                                                                                                                           Q u a n t i f y i n g   P r o c e s s   Va r i a t i o n    197



                                          UCL                                          +3σ
                                               A
                                                                                       +2σ
                                               B
                                                                                       +1σ
                                              C
                                            =                                          µ
                                            X
                                              C
                                                                                       –1σ
                                               B
                                                                                       –2σ
                                               A
                                          LCL                                          –3σ

                                Figure 9.26  Normal distribution zone lines on a control chart.


                                Of course, any point beyond three sigma (i.e., outside of the control limit)
                                is an indication of an out-of-control process.
                                   Since the control limits are at plus and minus three standard devia-
                                tions, finding the one and two sigma lines on a control chart is as simple
                                as dividing the distance between the grand average and either control
                                limit into thirds, which can be done using a ruler. This divides each half
                                of the control chart into three zones. The three zones are labeled A, B, and
                                C as shown on Fig. 9.26.
                                   Based on the expected percentages in each zone, sensitive run tests can
                                be developed for analyzing the patterns of variation in the various zones.
                                Remember, the existence of a nonrandom pattern means that a special
                                cause of variation was (or is) probably present. The averages, np, and c
                                control chart run tests are shown in Fig. 9.27.


                      Using Specifications for Process Control
                                The control charts for differentiating between common and special causes
                                of variation were invented nearly 100 years ago, yet there are many orga-
                                nizations that believe their processes are quite well controlled without
                                them. Unfortunately, in most cases, they are mistaken.
                                   The alternative offered by most practitioners is a standard trend chart,
                                which looks much like the individual control chart, but uses specification
                                limits in place of the calculated control limits. (Specification limits refer to
                                customer  or  management  requirements,  defined  as  an  upper  bound,  a
                                lower bound, or both. Observations outside the specifications are referred
                                to as defects.)
                                   Consider an operator using this type of chart to monitor a production
                                line. A sample is taken from the process and compared with the specifica-
                                tion. If the sample is close to the specification, the operator may decide to
                                adjust the process, usually by re-locating it by the same distance the latest








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