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SPC Statistical Process ControlBy: Amy Ee#Table of ContentsCommon cause & special causeTroubleshootCpkLean vs Six SigmaHistogramExerciseControl ChartControl Chart Data TypesHow do you establish Control LimitsSPC RulesData TypesDefect vs DefectiveMoving RangeI ChartMR ChartX Bar ChartR ChartTypes of VariationProportion ChartConstant Proportion ChartMore CpkU Chart and C Chart#Common cause & special causeCommon cause is a natural part of the process. Minor effect on the output (e.g. minor differences in raw material, change in ambient temperature)Special cause not normally present in the process. Larger impact on process variation. Catastrophic result (e.g. miscalibrated equipment, major raw material differences, excursion caused by operator)Special cause makes output difficult to predictControl chart is used to point out the presence of special cause variation#TroubleshootSpecial or common cause?Action:If common cause reduce itIf special cause eliminate it

CPKhttp://www.isixsigma.com/tools-templates/capability-indices-process-capability/process-capability-cp-cpk-and-process-performance-pp-ppk-what-difference/In the Six Sigma quality methodology, process performance is reported to the organization as a sigma level. The higher the sigma level, the better the process is performing.Another way to report process capability and process performance is through the statistical measurements ofCp,Cpk,Pp, andPpk. Click on the link to view definitions, interpretations and calculations forCpkandPpkthough the use of forum quotations.Process has to be STABLE before Cpk and Ppk being calculatedLean vs Six SigmaLean low hanging fruitSix Sigma breakthrough (6 sigma variation)Spec limit +- tolerance (process window)Variation - range between +- toleranceHistogramSummary of variation in a set of dataNormal distribution bell curve, system leverage by normal casesPowerhouse distribution system leverage by extreme casesSKEWStandard deviation = variation from average/mean valueLow standard deviation = robustHigh standard deviation = manufacture smaller electronics partExerciseSpecial cause/common cause exampleCommon cause - minor differences in raw materialSpecial cause - miscalibrated equipmentWhat is variation deviation from standard resultNormal distribution how many % will hit +- 3 sigma: 99.73%Control chartA type of run chartAverage/Min/Target = X-barSpec limits upper & lower limitControl limits upper & lower control limits (absolute < spec limit)Some control limit can be more than spec limit due to large variation (cannot be used, control limit has to be < spec limit)

Spec limitControl limitAverageSpec limitControl limitControl Chart Data TypesIn Range (Within control limit)Outliers (Out of Control)Shift (x or more in a row either above or below average)Trend (x or more in a row either ascending or descending)STABLE if all within control limits

How do you establish Control LimitsWhen to monitor/collect data (time shifts by day, hour, shift etc.)If no past data, collect minimum 25 data points based on IPC standards (if by shifts, 25 shifts)Collect 3 subgroups per data point and plot the averageRemove out of control limit data due to special causeOnly release to production if process is stable (all data within control limits)Control limits = 3sigmaSPC RulesNelson Test for Special CausesData TypeVariableMeasureableType of chart: X bar-R, X bar-S, I-MR, X bar-MRAttributeNot measureableUsed to decide e.g. Yes/No, True/FalseType of chart: p chart, np chart, u chart, c chartDefect vs DefectiveDefects are the subset of defectives. There may be n no. of defects to have one defective product.Moving RangeRange = diff between upper and lower limitMoving range = data difference (variation) in between time (xn xn-1)Useful for equipment monitoringOne of the sample is only 6 thus bringing the average down because data was keyed in wrongly etc.The range is too big. In X Bar chart, the data is within control. This is the danger of mean, it makes the data behave like normal. (data in X Bar cannot be concluded as stable, R chart shows this fact)Types of VariationRangeMoving Range (< 10 sample size per data point)Standard Deviation (> 10 sample size per data point)More Cpk and PpkControl chart StabilityCpk CapabilityCp = mean/6*sigma //old methodCpk = (USL mean/3*sigma); (mean LSL/3*sigma) //whichever lower The bigger Cpk is, the more capable is the process, i.e. one straight line at mean ONLY. When Cpk = 2.0, we achieved 6 sigma.Ppk for long term (3 months down the road)

U Chart & C ChartArea of opportunity of defectBigger area, bigger chanceC = constant area