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Download marina-yarberry | 2017-08-12 | General Chapter 10. MIS 373: Basic Operations Management. Additional content from Jeff . Heyl. Learning Objectives. After this lecture, students will be able to . Explain the need for quality control. .. List and briefly explain the elements of the control process. ID: 578219

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Slide1

Quality Control

Chapter 10

MIS 373: Basic Operations Management

Additional content from Jeff Heyl

Slide2

Learning Objectives

After this lecture, students will be able to Explain the need for quality control.List and briefly explain the elements of the control process.Explain Type I and Type II errorsExplain how control charts are used to monitor a process and the concepts that underlie their use.

MIS 373: Basic Operations Management

2

Slide3

Background Knowledge

How many of you have had at least one statistics course?

Normal distribution?

Standard deviation?

Z score?

Slide4

Motivations

Making Beer Better With Quality and Statistics

http://

videos.asq.org/making-beer-better-with-quality-and-statistics

Quality for Life: Psychic Pizza

http://

videos.asq.org/quality-for-life-psychic-pizza

Slide5

What is Quality Control?

Quality ControlA process that evaluates output relative to a standard and takes corrective action when output doesn’t meet standardsIf results are acceptable no further action is requiredUnacceptable results call for correction actionPhases of Quality Assurance

MIS 373: Basic Operations Management

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Slide6

Inspection

InspectionAn appraisal activity that compares goods or services to a standardInspection issues:What to inspectCount number of times defect occursMeasure the value of a characteristicHow much to inspect and how oftenAt what points in the process to inspectRaw materials and purchased partsFinished productsBefore a costly operationBefore an irreversible processCostly, possibly destructive, and disruptive – non value-addingFull inspection vs. Sampling

MIS 373: Basic Operations Management

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Slide7

How Much to Inspect

MIS 373: Basic Operations Management

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Slide8

How Much to Inspect

MIS 373: Basic Operations Management

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1 defect in 1 thousand unites

1 defect in 1 million unites

1 defect in 1 billion unites

Trying to catch:

Slide9

Centralized vs. On-Site Inspection

Effects on cost and level of disruption are a major issue in selecting centralized vs. on-site inspectionCentralizedSpecialized tests that may best be completed in a labMore specialized testing equipmentMore favorable testing environmentOn-SiteQuicker decisions are renderedAvoid introduction of extraneous factorsQuality at the source

MIS 373: Basic Operations Management

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Slide10

Statistical Process Control (SPC)

Quality control seeksQuality of ConformanceA product or service conforms to specificationsA tool used to help in this process:SPC Statistical evaluation of the output of a processHelps us to decide if a process is “in control” or if corrective action is needed“In control” means that the variation in the provided products/services is tolerable

MIS 373: Basic Operations Management

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Slide11

Process Variability

Two basic questions: concerning variability:Issue of Process ControlAre the variations random? If nonrandom variation is present, the process is said to be unstable. Variations randomly distributed within control limitsIssue of Process CapabilityGiven a stable process, is the inherent variability of the process within a range that conforms to performance criteria? The control limits satisfy the design specification

MIS 373: Basic Operations Management

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Slide12

Variation

VariationRandom (common cause) variation: Natural variation in the output of a process, created by countless minor factorsAssignable (special cause) variation: A variation whose cause can be identified. A nonrandom variationIllustration: M&M’sSizeColor

MIS 373: Basic Operations Management

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Slide13

Variation

Common causeInappropriate proceduresPoor designPoor maintenance of machinesLack of clearly defined standard operating proceduresPoor working conditions, e.g. lighting, noise, dirt, temperature, ventilationSubstandard raw materialsMeasurement errorQuality control errorVibration in industrial processesAmbient temperature and humidityNormal wear and tearVariability in settings

Special causePoor adjustment of equipmentOperator falls asleepFaulty controllersMachine malfunctionFall of groundComputer crashPoor batch of raw materialPower surgesHigh healthcare demand from elderly peopleBroken partAbnormal traffic (click fraud) on web adsExtremely long lab testing turnover time due to switching to a new computer systemOperator absent

MIS 373: Basic Operations Management

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Slide14

Sampling and Sample Distribution

SPC involves periodically taking samples of process output and computing sample statistics:Sample meansThe number of occurrences of some outcomeSample statistics are used to judge the randomness of process variation

MIS 373: Basic Operations Management

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Slide15

Sampling and Sample Distribution

Sampling DistributionA theoretical distribution that describes the random variability of sample statisticsThe normal distribution is commonly used for this purposeCentral Limit TheoremThe distribution of sample averages tends to be normal regardless of the shape of the underlying process distribution

MIS 373: Basic Operations Management

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Slide16

Demo

Use simulation to test the Central

Limit

Theorem

Slide17

The Normal Distribution

MIS 373: Basic Operations Management

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Slide18

Control Process

Sampling and corrective action are only a part of the control processSteps required for effective control:Define: What is to be controlled?Measure: How will measurement be accomplished?Compare: There must be a standard of comparisonEvaluate: Establish a definition of out of controlCorrect: Uncover the cause of nonrandom variability and fix itMonitor results: Verify that the problem has been eliminated

MIS 373: Basic Operations Management

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Slide19

Control Charts: The Voice of the Process

Control ChartA time ordered plot of representative sample statistics obtained from an ongoing process (e.g. sample means), used to distinguish between random and nonrandom variabilityControl limitsThe dividing lines between random and nonrandom deviations from the mean of the distributionUpper and lower control limits define the range of acceptable variationUpper control limit = UCL = mean + zσLower control limit = LCL = mean + zσ

MIS 373: Basic Operations Management

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Slide20

UCL

LCL

Mean

Control

Chart Example

Each point on the control chart represents a sample of

n

observations

MIS 373: Basic Operations Management

Sample number

| | | | | | | | | | | |

1 2 3 4 5 6 7 8 9 10 11 12

Variation due to assignable causes

Variation due to assignable causes

Variation due to natural causes

Out of control

Out of control

20

Slide21

Errors

Type I errorNarrow control limitsConcluding a process is not in control when it actually is.Manufacturer’s RiskType II errorWide control limitsConcluding a process is in control when it is not.Consumer’s Risk

MIS 373: Basic Operations Management

Alarm

No Alarm

Process

In-Control

Process

Out-of-Control

Type I

Type II

n

o-error

no-error

21

Slide22

Errors Illustration

Q: I always get confused about Type I and II errors. Can you show me something to help me remember the difference?

Source:

Effect

Size FAQs

 

by

Paul Ellis

Slide23

Control Charts

MIS 373: Basic Operations Management

Every process displays variation in performance: normal or abnormalControl charts monitor process to identify abnormal variation Do not tamper with a process that is “in control” with normal variation Correct an “out of control” process with abnormal variationControl charts may cause false alarms – too narrow - (or missed signals – too wide) by mistaking normal (abnormal) variation for abnormal (normal) variation

Out of Control In Control Improved

LCL



UCL

23

Slide24

Control Charts

Data that are measured“x-bar” charts (Mean)Used to monitor the central tendency of a process.R charts (Range)Used to monitor the process dispersion

MIS 373: Basic Operations Management

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Slide25

x-bar (sample average) chart Control Limits

MIS 373: Basic Operations Management

)k = number of samplesn = sample sizecommonly: z = 3

 

25

Slide26

X-bar Chart

Mean = 5.5.STD = 0.4 ft 99.74% within ± 3 STD(random) 9 students {6.5, 6.4, 6.6, 6.3, 6.7, 6.5, 6.6, 6.4, 6.5} each within “normal”  average = 6.5 ftSample control limits  tighter than populationUCL= = =5.9 ft.GROUP above “normal” (outside control limits)

 

MIS 373: Basic Operations Management

5.5

6.7

4.3

5.1

5.9

5.5

6.5

26

Slide27

R-Chart: Control Limits

Range charts or R-charts are used to monitor process dispersion

MIS 373: Basic Operations Management

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Slide28

Mean and range charts

MIS 373: Basic Operations Management

(a)

These

sampling distributions result in the charts below

(Sampling mean is shifting upward but range is consistent)

R-chart

(

R

-chart does not detect change in mean)

UCL

LCL

x

-chart

(

x

-chart detects shift in central tendency)

UCL

LCL

28

Slide29

Mean and range charts

MIS 373: Basic Operations Management

R

-chart

(

R

-chart detects increase in dispersion)

UCL

LCL

(b)

These sampling distributions result in the charts below

(Sampling mean is constant but dispersion is increasing)

x

-chart

(

x

-chart does not detect the increase in dispersion)

UCL

LCL

29

Slide30

Run Tests

Even if a process appears to be in control, the data may still not reflect a random processAnalysts often supplement control charts with a run testRun testA test for patterns in a sequenceRunSequence of observations with a certain characteristic

MIS 373: Basic Operations Management

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Slide31

Run Tests

MIS 373: Basic Operations Management

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A: Above

B: Below

U: Upward

D: Downward

Slide32

Patterns in Control Charts

MIS 373: Basic Operations Management

UCL

Target

LCL

Erratic behavior.

UCL

Target

LCL

Run of 5 above (or below) central line.

UCL

Target

LCL

Two plots very near lower (or upper) control

.

Normal behavior. Process is “in control.”

UCL

Target

LCL

UCL

Target

LCL

One plot out above (or below).

Process

is “out of control.”

UCL

Target

LCL

Trends in either direction, 5 plots.

Progressive

change.

32

Slide33

Demo

ASQ Control chart template

http://

asq.org/learn-about-quality/data-collection-analysis-tools/overview/asq-control-chart.xls

Slide34

Key Points

All processes exhibit random variation. Quality control's purpose is to identify a process that also exhibits nonrandom (correctable) variation on the basis of sample statistics (e.g., sample means) obtained from the process.Control charts and run tests can be used to detect nonrandom variation in sample statistics. It is also advisable to plot the data to visually check for patterns.

MIS 373: Basic Operations Management

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