spc統(tǒng)計過程控制簡介(英文版)

1、Statistical Process ControlStatistical Process ControlnVariability exists in everything - people, machines and naturenPurpose - 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 controlSta

2、tistical Process ControlnDesign quality checks into the process - eliminate need for inspection build better product during design make product withstand variation - Taguchi MethodHistorynPrior to IR craftsmen were responsible for entire process - pride of workmanshipnDuring 1920s W. Shewart of Bell

3、 Labs build Control Charts - ASQ formednDuring 1950s Deming introduced QC techniques to Japanese 1961 Feigenbaum wrote Total Quality ControlStatistical Process ControlnTwo main subjects Acceptance Sampling - test random samples of finished goods and accept or reject whole lot Process Control - sampl

4、e process output at different points in time - see if process is in control - determine cause of out-of-control behaviorStatistical Process ControlnMonitor the production process in one of three places - before, during or afternPhysically examine some of the unitsnBasic issues; where do we inspect h

5、ow much and how often do we inspect do we inspect variables or attributesnBalance 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 tim

6、e and labor4. Before an irreversible operation - rework only up to a certain point5. Before a covering operation - painting or assemblyTypes of SamplingnDefn: Attribute Sampling - check for the presence or absence of a product characteristicnDefn: Variable Sampling - product characteristics that can

7、 be measured on a continuous scaleStatistical Process Controlnused to evaluate the output of a processnmost processes exhibit some kind of variation random variation - natural variation, uncontrollable assignable variation - can identify causendetermine whether non-random sources of variation are re

8、sponsible for problemsControl ChartsnPrevent production of excessive number of defects - look for causes of variabilitynA time-ordered plot of sample statistics nControl limits - determine the difference between random and assignable variation - usually 3 nEach new sample statistic is plotted and co

9、mpared to the control limitsUCLLCLUCLLCLUCLLCLStatisticalProcessControlTypes 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

10、 of 5 - 9 observations - reasonable amount of time and costs lessUCLXA R2LCLXA R2UCLD R4LCLD R3Types of Control Charts (cont)2. Attributes Control ChartsA. P-Chart - count number of defects in sampleB. C-Chart - count number of defects per unit-building control charts adds to the time and cost of pr

11、oduction- attribute sampling is easier than variable - need larger sample sizesUCLPZPLCLPZPUCLCZ CLCLCZ CProcess CapabilitynSpecify 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

12、 has = 0.02 inches - a 3- control chart limits are wider than tolerancesCapability IndexnShows 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 =3,3minXUTLLTLXCapability IndexnExample -

13、 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 SamplingnPurposesDetermine policy for accepting or rejecting a production lot of materials or componentsSample quality is used t

14、o make decisionnAdvantagesLess handling damageFewer inspectorsApplicability to destructive testingEntire lot rejection (motivation for improvement) 5Acceptance SamplingnDisadvantagesRisks of accepting “bad” lots and rejecting “good” lotsAdded planning and documentationSample provides less informatio

15、n 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

16、 defects in lots leaving inspectionAcceptance Plans (cont)- Producers Risk ( ) - probability of rejecting good lot- Consumers 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 acc

17、eptance9Operating Characteristic Curven = 99c = 4AQLLTPD00.10.20.30.40.50.60.70.80.9112345678910 11 12Percent defectiveProbability of acceptanceB B =.10(consumers risk) = .05 (producers risk)Acceptance PlansnPlans considers the interaction among the above criteria - it considers the objectives of the supplier and consumernThe producer would like low probability of rejecting a good lot and consumer wants to not accept a bad lot HP