Quality Control• Interchangeability of parts • Avoid selective assembly ... • Permanent...

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Quality Control

Dr. Richard Jerz

© 2010 rjerz.com1

Specifying Quality

• Tolerances• Fits

• Applies to manufacturing• Applies to service, too

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Purpose of Tolerances

• Impossible to make all parts to exact dimension• Interchangeability of parts• Avoid selective assembly• Different degrees of size (toys versus jets)• Quality depends upon repeatability and sizing• Loose and tight fit

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Fit Types (Parts)

• Clearance• Always a clearance

• Interference• Always interference• Press fits

• Transition• Clearance or interference depends upon specific parts

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Clearance Fit

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Standard Inch Fits

• Use of a symbols• Typically not shown on drawings, dimensions are typically shown

• Symbols: RC, LC, LT, LN, FN• Numbers – degree of fit• Complete Description ‐ Two letters and number• Example: RC2

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Design Suggestion

• Shafts rotating under 600 rpm with ordinary loads; >RC5

• Shafts rotating over 600 rpm with heavy loads; < RC5

• Shafts sliding freely; approx. LC• Push fits with keyed shafts and clamp, no fitting; LT• Parts assembled with some basic fitting; LN• Permanent assembly with no freely moving parts; FN1

• Permanent assembly with severe loading effects; FN3• Permanent assembly with press needed for assembly; FN5

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Tolerance Example1” RC7 

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Table 17

Matching Specs to Processes

• Capability analysis

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Tolerances and Machining Processes 

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Example: Robot Repeatability Data 

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Inspection Questions

• How Much/How Often• Where/When • Centralized vs. On‐site

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Inputs Transformation Outputs

Acceptancesampling

Processcontrol

Acceptancesampling

Inspection Costs

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Cos

t

OptimalAmount of Inspection

Cost of inspection

Cost of passingdefectives

Total Cost

Methods of Assuring Quality

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Acceptancesampling

Processcontrol

Continuousimprovement

Inspectionbefore/afterproduction

Correctiveaction duringproduction

Quality builtinto theprocess

The leastprogressive

The mostprogressive

Where to Inspect in the Process 

• Raw materials and purchased parts• Finished products• Before a costly operation• Before an irreversible process• Before a covering process

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Examples of Inspection Points

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Type ofbusiness

Inspectionpoints

Characteristics

Fast Food CashierCounter areaEating areaBuildingKitchen

AccuracyAppearance, productivityCleanlinessAppearanceHealth regulations

Hotel/motel Parking lotAccountingBuildingMain desk

Safe, well lightedAccuracy, timelinessAppearance, safetyWaiting times

Supermarket CashiersDeliveries

Accuracy, courtesyQuality, quantity

Acceptance Sampling

• Form of inspection applied to lots or batches of items before or after a process, to judge conformance with predetermined standards (supplemental Chapter)

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Statistical Process Control

• Statistical evaluation of the output of a process during production• Define• Measure• Compare to a standard• Evaluate• Take corrective action• Evaluate corrective action

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What to Inspect?

• Variables

• Attributes

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Error Conditions

• Type 1• Type 2

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Mean

LCL UCL

/2 /2

Probabilityof Type I error

Type 1 and Type 2

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Statistical Process Control

• Variations and Control• Random variation: Natural variations in the output of process, created by countless minor factors

• Assignable variation: A variation whose source can be identified 

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Process Capability

• Tolerances (design)• specifications

• Process variability• Natural variability in a process

• Process capability• Process variability relative to specification

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Control Charts

• Statistics• Normal distribution• Central limit theorem• “Out of control”

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Normal Distribution

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Mean

95.44%

99.74%

Standard deviation

Control Limits

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Samplingdistribution

Processdistribution

Mean

Lowercontrol

limit

Uppercontrol

limit

Control Chart

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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

UCL

LCL

Sample number

Mean

Out ofcontrol

Normal variationdue to chance

Abnormal variationdue to assignable sources

Abnormal variationdue to assignable sources

Figure 10-8

Mean and Range Charts

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UCL

LCL

UCL

LCL

R-chart

x-Chart Detects shift

Does notdetect shift

(process mean is shifting upward)

SamplingDistribution

Control Charts

• Warning conditions• Two successive points near limit• Run of five above or below mean• Trend• Erratic behavior

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Industry Trends

• Continuous Improvement• In process inspection• 100% inspection• Use of statistical quality control• Deming concepts• Automate control of equipment

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