《QUALITY CONTROL FOR PLASTICS ENGINEERS》求取 ⇩

INTRODUCTION1

1.THE USE OF FREQUENCY DISTRIBUTIONS IN PLASTICS MOLDING3

2.THE NORMAL FREQUENCY DISTRIBUTION9

Introduction9

Historical Background9

The Normal Frequency Distribution10

Tie-in with Industrial Processes11

A Case History13

Other Distributions15

3.CONTROL CHARTS FOR VARIABLES18

Introduction18

Bridging the Gap19

A More Reliable Approach20

How To Do It—Calculation of Limits23

Example Worked Out to Illustrate Process24

What Does It Mean?25

Symptom—Points Above or Below Control Limits27

Symptom—Runs Above or Below—Rule of Seven27

Symptom—Too Many Points Near a Control Limit28

Symptom—Non-normal Distribution—Bimodal29

Symptom—Cyclical Trends29

Symptom—Runs Above or Below30

Symptom—Runs Up or Down31

Symptom—None31

Modified Control Chart32

Median and Range Control Charts33

Where and Why?36

4.CONTROL CHARTS FOR ATTRIBUTES38

Introduction38

The Basic Assumptions39

Calculation of Control Limits42

Fraction Defective44

Defects,Not Defectives46

Modifications of Attribute Control Charts47

A Good Start in S.Q.C.48

5.SPECIFICATIONS FOR USE UNDER STATISTICAL QUALITY CONTROL50

What Constitutes a Good and Workable Specification?51

How To Improve Specifications53

What Can Be Done With Tolerance Patterns55

Control Versus Inspection59

6.SAMPLING INSPECTION62

Putting A Lot Into A Homogeneous Condition63

How Representative Is A Random Sample?64

The Numerical Risks of Sampling64

The Limiting Risk Concept67

Some Practical Sampling Plans68

Sampling by Variables71

General Specifications71

Detailed Specifications72

Operating Instructions72

Special Features80

7.STATISTICAL CORRELATION82

8.PROCESS CAPABILITY ANALYSIS91

Elements of Capability Analysis92

Making A Sample Capability Analysis94

Evaluation of Centering,Spread,Capability and Stability95

Limitations of the Simple Capability Analysis97

Dissection by Analysis of Variance104

Dissection by the Span Plan105

Summary109

9.SIGNIFICANCE110

Introduction110

“t”for Comparison of an Average With A Standard112

“t”for Comparison of One Average With Another117

“F”for Comparison of One Dispersion With Another120

“x2”for Comparison of Actual Counted Objects or Events With Expected Counts124

10.STATISTICAL EXPERIMENTS IN PLASTICS FABRICATION133

Introduction133

Increasing the Sensitivity of An Experiment134

The Factorial Experiment134

Analysis of Factorial Data135

Interpretation of Variance Analysis136

Comparison With Classical Experimentation137

New Developments in Experimental Design138

Index141