Process quality control: troubleshooting and interpretation of data
Troubleshooting tool for manufacturing processes.A hands-on, solutions-oriented guide, Process QualityControl, Third Edition, by Ellis R, Ott, Edward G.Schilling, and Dean V. Neubauer, gives you a systematicapproach to gathering and analyzing data fortroubleshooting manufacturing processes. This classicemphasizes short term and long term variability,particularly with regard to process capability andperformance. The third edition gives you many newanalytical methods, insights into their application, andcase studies. These techniques include toleranceintervals, a test for the comparison of long term andshort term variation, simplified attribute sample sizedetermination, and an updated discussion of sampling.You'll also find an expanded discussion of control charts,including trend charts, manual adjustment charts, andshort run charts. While the emphasis is on processcontrol, you'll also find significant material on analysis of means.
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adjustment Analysis of Means ANOM assembly assignable causes attribute data bottles caps Chap combinations computed considered control chart control limits critical values Data from Table data of Table decision lines discussed E. S. Pearson Easter lilies estimate evidence example factors histogram HISTORY important improvement independent variables indicate inspection investigation Latin Square levels looms machine main effect manufacturing measurements median methods mica mold Nickel-Cadmium Batteries NL gages nonrandomness normally distributed number of defectives number of runs observations obtained OC curves operators outlier patterns percent defective plotted points possible Pr(x probability problem procedure process average production Prto Pr(c PrW Pr(c quality characteristics quality control random rejects risk sampling plan scatter diagram Shewhart shift specifications stable process standard deviation standard given subgroups Table A-5 test sets troubleshooting tubes two-factor interaction usually variation vendor X Pr(x X PrW Pr(c