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by: Clemens Schamberger

StatisticsforEngineers HFE603

Clemens Schamberger
GPA 3.95


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Class Notes
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This 2 page Class Notes was uploaded by Clemens Schamberger on Thursday October 29, 2015. The Class Notes belongs to HFE603 at Wright State University taught by DavidKender in Fall. Since its upload, it has received 12 views. For similar materials see /class/231133/hfe603-wright-state-university in Engineering and Tech at Wright State University.

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Date Created: 10/29/15
Overview Process Data Data Characteristics Chronologically arranged data Nature or Shape of the Distribution Representative Value Mean Statistically Stable Within Statistical Control Measure ofVariation Standard Deviation n y random variation no patterns or cycles Pattern ofChange with respect to Time Variation Quality Control Random Variation Due to chance inherent in any process Consistency limited variation 39om unit to unit Assignable Variation Results from identi able causes Run Chart Sequential plot of individualdata values overtime Only when a process is statistically stable can the data be treated as if it came 39om a single populatIon Control Charts Quantitative amp Qualitative One method of maintaining quality is to reduce the amount of Sequential PIOt Ofaver ge Values Ver time assignable variation Control values indicate central tendency and the limits ofacceptable excursions Minimum Assignable Variation implies a stable process Upper Control Limit UCL a stable process is indicative ofa quality product or service Center Line Lower Control Limit LCL Data charts are useful tools for monitoring the stability of a Quantitative R X 5 process and hence help maintain quality Qualitative p c Quantitative Control Charts R Charts are used to monitor variation Charts Monitor Variation Range plots ofsample ranges not individual values s Charts Monitor Variation Standard Deviation Notation X Charts Monitor Means Averages 1 Size 0f eaCh sample R mean of sample ranges Qualitative Control Charts Control Limits 997 con dence intervals 3 SD s Charts Monitor Proportions ofCharacteristic Value Upper Control Limit UCL mg c Charts Monitor Number ofCharacteristic Values Note p Charts amp c Charts are olten used to track the Center Line R proportion or number of defective items per lot Lower Control Limit LCL DER Vi gm E Charts are used to monitorvariation plots of sample standard deviations Notation n size ofeach sample E mean of sample standard deviations Control Limits 997 con dence intervals 3 SD s Upper Control Limit UCL B4 Center Line 3 Lower Control Limit LCL B3 Charts are used to monitor sample means plots of sample means based on standard deviations Notation n size ofeach sample X mean ofsample means mean of all samples Control Limits 997 con dence intervals 3 SD s Upper Control Limit UCL A Center Line Lower Control LimitLCL X A X Charts are used to monitor sample means plots ofsample means based on ranges Notation size of each sample X mean of sample means mean of all samples Control Limits 997 con dence intervals 3 SD s Upper Control Limit UCL Center Line Lower Control Limit LCL X AZR c Charts are used to monitor attribute s numerical quantities plots of sample attribute numbers Notation n size ofeach sample c pooled estimate of attributes overall quantity Control Limits 997 con dence intervals 3 SD s Upper Control Limit UCL 6 36 2 Center Line E Lower Control Limit LCL c 35 2 p Charts are used to monitor attribute s proportionality plots ofsample attribute proportions Notation n size of each sample I pooled estimate of attributes overall proportion Control Limits 997 con dence intervals 3 SD s Upper Control Limit UCL 5 3 E 1 Eln 1 Center Line E Lower Control Limit LCL 5 3 E 1 5n 1W Obviously apparent nonrandom pattern trend or cycle Outlying point beyond upper or lower control limit Runof Points Rule Eight consecutive points above or below the centerline Six consecutive points all increasing or all decreasing Fourteen consecutive points alternating above and below the centerline


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