StatisticalProcessControl(英文版)obe.pptx

Statistical Process ControlStatistical Process Controln Variability exists in everything-people,machines and naturen Purpose-to be sure that processes are performing in an acceptable manner monitor over time forecast if will still be well in future determine factors that make it out of controlStatistical Process Controln Design quality checks into the process-eliminate need for inspection build better product during design make product withstand variation-Taguchi MethodHistoryn Prior to IR craftsmen were responsible for entire process-pride of workmanshipn During 1920 s W.Shewart of Bell Labs build Control Charts-ASQ formedn During 1950 s Deming introduced QC techniques to Japanese 1961 Feigenbaum wrote Total Quality ControlStatistical Process Controln Two main subjects Acceptance Sampling-test random samples of finished goods and accept or reject whole lot Process Control-sample process output at different points in time-see if process is in control-determine cause of out-of-control behaviorStatistical Process Controln Monitor the production process in one of three places-before,during or aftern Physically examine some of the unitsn Basic issues;where do we inspect how much and how often do we inspect do we inspect variables or attributesn Balance two costs:inspection and serviceRules of thumb for where to inspect;1.Inputs-do not pay for goods that do not meet standards2.Finished Goods-protect your reputation3.Before a costly operation-do not waste time and labor4.Before an irreversible operation-rework only up to a certain point5.Before a covering operation-painting or assemblyTypes of Samplingn Defn:Attribute Sampling-check for the presence or absence of a product characteristicn Defn:Variable Sampling-product characteristics that can be measured on a continuous scaleStatistical Process Controln used to evaluate the output of a processn most processes exhibit some kind of variation random variation-natural variation,uncontrollable assignable variation-can identify causen determine whether non-random sources of variation are responsible for problemsControl Chartsn Prevent production of excessive number of defects-look for causes of variabilityn A time-ordered plot of sample statistics n Control limits-determine the difference between random and assignable variation-usually 3 n Each new sample statistic is plotted and compared to the control limitsStatisticalProcessControlTypes of Control Charts1.Variable Control chartsA.Means Chart-monitors central tendency B.Range Chart-monitors dispersion-both can be used to monitor same process-use 20-25 samples to build initial limits-take samples of 5-9 observations-reasonable amount of time and costs lessTypes of Control Charts(cont)2.Attributes Control ChartsA.P-Chart-count number of defects in sample B.C-Chart-count number of defects per unit-building control charts adds to the time and cost of production-attribute sampling is easier than variable-need larger sample sizesProcess Capabilityn Specify ranges for certain product dimensions during design Tolerances Max and min acceptable level of output Bearing for rotating shaft-diameter is 1.25 inches 0.005 Process has=0.02 inches-a 3-control chart limits are wider than tolerancesCapability Indexn Shows how well parts fit into the range specified by design limits If design limits are wider than process limits,the process can shift and still produce good parts Cpk=Capability Indexn Example-light bulbs are produced with an average life of 90 hours.The target design life is 100 hours.The UTL=120 and the LTL=80 hours.If=4.8 what is the Cpk?4Acceptance Samplingn Purposes Determine policy for accepting or rejecting a production lot of materials or components Sample quality is used to make decisionn Advantages Less handling damage Fewer inspectors Applicability to destructive testing Entire lot rejection(motivation for improvement)5Acceptance Samplingn Disadvantages Risks of accepting“bad”lots and rejecting“good”lots Added planning and documentation Sample provides less information than 100-percent inspection Acceptance Plans1.Single-Sample Plans-only one sample define n and c Operating Characteristic Curve-graphs the performance of plan Acceptable Quality Level-defines good lots Lot Tolerance Percent Defective-defines bad lots Average Outgoing Quality-the percent defects in lots leaving inspectionAcceptance Plans(cont)-Producer s Risk()-probability of rejecting good lot-Consumer s Risk()-probability of accepting a bad lot-can reduce errors by not biasing the sample and taking a larger one-use the Poisson distribution to compute probability of acceptance9Operating Characteristic Curven=99c=4AQL L TPD00.10.20.30.40.50.60.70.80.911 2 3 4 5 6 7 8 9 10 1 1 12Percent defectiveProbability of acceptanceB=.10(consumers risk)a=.05(producers risk)Acceptance Plansn Plans considers the interaction among the above criteria-it considers the objectives of the supplier and consumern The producer would like low probability of rejecting a good lot and consumer wants to not accept a bad lot HP and Japanese vendorAcceptance Plans(cont)2.Double-Sample PlansA.Draw one sampleB.if number of defects is less than a lower limit,accept lot if number of defects is greater than some upper limit reject lotC.if number of defects is between the limits,take another sample演讲完毕，谢谢观看！