# Statistical quality control

副标题：无

作 者：[美]Eugene L. Grant，[美]Richard S. Leavenworth著

分类号：F406.3

ISBN：9787900641984

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简介

本书是工业工程专业统计质量控制的经典教材，已经出到第7版。与前几版的做法一样，对上一版的改进一是体现在基本原理的表述上，二是使各种主题更接近时代。
本书简要概述了质量控制的意义和历史发展过程，重点讲解了各种类型的控制图和抽样检验体系和过程，而对概率和统计知识的介绍非常直观和简单。作者认为这种方式对工程和商业领域的学生非常重要，这是因为虽然他们的工业经验不多，但是他们将来可能要对操作员和检验员进行统计质量控制的课程培训。
本书的第4部分颇具特色，主要涉及质量决策的经济因素、质量管理和问题解决的模式等内容。
随着经济的发展和学科的交叉，工业工程所涉猎的主题已不仅仅局限于制造业。本书作者之一尤金·L·格兰特（Eugege·L·Grant）曾是美国斯坦福大学的工程经济学教授，作为该领域的权威，他的视野较之一般专攻制造领域的教授更为宽广，所以该书作为工业工程专业统计质量控制的教材非常合适。

目录

list of examples

preface

part one introduction

1 introduction and overview

1.1 the meaning of quality / 1.2 the focus of this book / 1.3 the control-chart viewpoint / 1.4 scientific sampling / 1.5 use of examples / 1.6 meanings and usage of the words defective and defect / 1.7 many economy studies call for the viewpoint of statistical quality control / 1.8 statistical quality control may have useful by-products / 1.9 reasons for the use of the adjective statistical/ 1.10 four different levels of understanding statistical quality control/ 1.11 nonmanufacturing applications of statistical quality control techniques/ 1.12 some topics covered in part four of this book

part two statistical process control

2 directions for simple x and r charts

2.1 setting up and operating control charts for x and r / 2.2 checklist of necessary steps in using x and r charts / 2.3 some comments on computer software for statistical process control / problems

3 why the control chart works; some statistical concepts

3.1 the need for understanding statistical principles/3.2 description of patterns of variation/3.3 graphic representation of a frequency distribution / 3.4 averages and measures of dispersion / 3.5 sampling statistics and universe parameters / 3.6 the normal curve / 3.7 other frequency curves / 3.8 what the average and standard deviation of a set of numbers really tell/problems

4 why the control chart works; some examples

4.1 the use of control charts to judge whether or not a constant system of chance causes is present / 4.2 use of the control chart in interpretation of a frequency distribution / 4.3 contribution of the control chart to elimination of causes of trouble / 4.4 changes in universe average / 4.5 shift in universe dispersion with no change in universe average / 4.6 changes in universe average and universe dispersion / 4.7 a possible view of the question answered by a control chart / 4.8 nonproduct applications of control charts for variables / 4.9 conflicting expressions for the standard deviation of a set of numbers / problems

5 some fundamentals of the theory of probability

5.1 probability has a mathematical meaning / 5.2 modern concepts of probability theory / 5.3 some theorems of the theory of probability / 5.4 infinite and finite universes / 5.5 the hypergeometric probability distribution / 5.6 the binomial as a probability distribution / 5.7 the poisson law as a probability distribution / 5.8 the normal distribution / 5.9 deciding on the method to be used for calculating probabilities in industrial sampling problems / 5.10 relationship between control charts and certain other statistical techniques / 5.11 random variables / 5.12 point estimates and estimators / 5.13 the problem of selecting a parameter to describe universe dispersion and of choosing an estimator for that parameter / 5.14 sampling from a normal distribution / 5.15 theory of extreme runs / problems

6 the control chart for fraction rejected

.6.1 some practical limitations of control charts for variables / 6.2 control charts for attributes / 6.3 the control chart for fraction rejected / 6.4 the binomial as a probability law that determines the fluctuations of fraction rejected / 6.5 control limits for the p chart / 6.6 problems introduced by variable subgroup size / 6.7 checklist of necessary steps in connection with control chart for fraction rejected / 6.8 sensitivity of the p chart / 6.9 nonproduct applications of p and up charts / 6.1o p charts are not suitable for all data on fraction rejected / problems

7 the control chart for nonconformities

7.1 the place of the c chart in statistical process control / 7.2 distinction between a nonconforming article and a nonconformity / 7.3 limits for the c chart are based on the poisson distribution / 7.4 the combination of poisson distributions / 7.5 conditions favorable to the economic use of the control chart for nonconformities / 7.6 adaptations of the c chart to variations in 1he area of opportunity for a nonconformity / 7.7 probability limits for c and u charts / 7.8 the u chart for nonconformities per multiple units / 7.9 listing individual nonconformities on the form containing a c or u chart / 7.10 the introduction of a control chart may motivate quality improvement / 7.11 classification of nonconformities and their weighting / 7.12 q charts for quality scores and d charts for demerit classifications / 7.13 use of 3 c for approximate calculation of control limits in situations involving the binomial distribution / 7.14 applicability of c chart technique in fields other than statistical process control / problems

8 rational subgrouping

8.1 the information given by the control chart depends on the basis used for selection of subgroups / 8.2 two schemes involving order of production as a basis for subgrouping / 8.3 question addressed by the shewhart control chart / 8.4 sources of variability / 8.5 order of production is not always a sufficient basis for subgrouping / 8.6 need for discrimination in the selection of subgroups / 8.7 identification on a control chart of different sources of subgroups / 8.8 precision, reproducibility and accuracy of methods of measurement / 8.9 relationship between the variability of measured values and the precision of the method of measurement / problems

9 statistical analysis of process capability and for process improvement

9.1 process capability as a step toward process improvement / 9.2 process capability and performance indexes / 9.3 quality by design: design and inspection specifications / 9.4 statistical methods may help in setting better specification limits / 9.5 some common methods of interpretation of a pilot run as a basis for setting tolerances / 9.6 two statistical theorems of great importance in the interrelationship of tolerances / 9.7 experimentation / problems

10 some special process control procedures

10.1 some miscellaneous topics / 10.2 some special topics on shewhart control charts for variables / 10.3 some related special procedures / 10.4 a general test for homogeneity / 10.5 probability limits on control charts for variables / 10.6 control charts for moving averages / 10.7 x chart with a linear trend / 10.8 narrow limit gaging / 10.9 working with short production runs / 10.10 a success chart for production runs of extremely high quality / 10.11 combining process control and product acceptance / 10.12 cumulative sum control chart for averages / problems

part three scientific sampling

11 some fundamental concepts in scientific sampling

11.1 the importance of sampling / 11 .2 some weaknesses of certain traditional practices in acceptance sampling / 11.3 purpose of this chapter / 11.4 lot-by-lot acceptance using single sampling by attributes / 11.5 oc curve of an ideal sampling plan / 11.6 the indexing of acceptance plans by a single point on the oc curve / 11.7 average outgoing quality and the aoql / 11.8 double sampling / 11.9 choosing a sampling plan to minimize average total inspection / 11.10 multiple and sequential sampling / 11.11 randomness in acceptance sampling / problems

12 an aql system for lot-by-lot acceptance sampling by attributes

12.1 selecting an acceptance inspection procedure / 12.2 a historical note regarding acceptance sampling systems based on the aql concept / 12.3 some decisions made in the original establishment of the aql as a quality standard / 12.4 some aspects of the master tables reproduced from the abc standard / 12.5 determining the sample size code letter / 12.6 oc curves under normal, tightened. and reduced inspection / 12.7 single, double, and multiple sampling plans in aql systems / 12.8 classification of defects / 12.9 the formation of inspection lots / 12.10 acceptance based on numbers of defects / 12.11 a systematic record of quality history is an important aspect of statistical acceptance procedures / 12.12 selecting an acceptance plan for an isolated lot / 12.13 importance of aoql values in sampling plans based on the aql / problems

13 other procedures for acceptance sampling by attributes

13.1 two useful volumes of standard tables / 13.2 the dodge-romig tables / 13.3 some reasons for not basing a quality standard on a provision for screening inspection / 13.4 designing single sampling plans for stipulated producer's and consumer's risks / 13.5 a simple aql system proposed by dodge / 13.6 design of a sequential plan having an oc curve passing through two designated points l 13.7 dodge's chain sampling inspection plan / problems

14 systems for acceptance sampling from continuous production

14.1 dodge's aoql plan for continuous production-csp-1/14.2 multilevel continuous sampling plans (csp-m) / 14.3 the mil-std-1235 system for sampling from continuous production / 14.4 aoq functions of some continuous sampling schemes / 14.5 skip-lot sampling / 14.6 further comment on continuous sampling plans / 14.7 unique features of csp plans as guides for spc sampling / problems

15 systems for acceptance sampling by variables

15.1 some advantages and limitations of acceptance sampling by variables l 15.2 some different types of acceptance criteria involving variables / 15.3 using plotted frequency distributions in acceptance sampling / 15.4 use of control charts to identify grand lots / 15.5 computing the oc curve for a known-sigma variables sampling plan based on the assumption of a normal distribution i 15.6 some general aspects of military standard 414 l 15.7 numerical data to illustrate normal inspection under mil-std-414 / 15.8 tightened inspection in mil-std-414 l 15.9 reduced inspection in mil-std-414 / 15.10 an upper specification limit in mil-std-414 / 15.11 two-sided specifications in mll-std-414 / 15.12 the relationship among sample sizes under the standard deviation method, the range method, and the procedures assuming known variability / 15.13 some comments on table 15.4 / 15.14 the choice between unknown-sigma and known-sigma plans / 15.15 some sources of oc curves for variables plans based on the assumption of normality / 15.16 comment on the assumption of a normal distribution in known-sigma and unknown-sigma plans / 15.17 acceptance/rejection plans may be devised to accept on variables criteria but to reject only on attributes criteria / 15.18 international and commercial standards corresponding to mil-std-414 / problems

16 some aspects of life testing and reliability

16.1 purpose of this chapter / 16.2 a conventional model of the probability of equipment failure / 16.3 some modem definitions of reliability / 16.4 the relationship between a constant failure rate and mean life or mean time between failures / 16.5 an experiment to illustrate certain aspects of a constant failure rate / 16.6 the "exponential" reliability function that results from the assumption of a constant failure rate / 16.7 principal u.s. government documents that treat life testing under the assumption of a constant failure rate / 16.8 the broad general usefulness of sampling and tasting standards / problems

part four some related topics

17 some economic aspects of quality decisions

17.1 problems of business altematives are problems in economy / 17.2 some basic concepts in engineering economy / 17.3 three general classes of consequences that should be recognized in making certain quality decisions / 17.4 taguchi's loss function / 17.5 some economic aspects of the margin of safety in design specifications / 17.6 some special difficulties of estimating indirect costs in economy studies / 17.7 did it pay to use statistical quality control? / 17.8 the increasing importance of costs related to product liability / problems

18 some significant events in the development of statistical quality control

18.1 quality and standardization / 18.2 the two architects of statistical quality control / 18.3 quality assurance science and world war ii / 18.4 japan's recovery as a worldclass industrial power / 18.5 the quality cultural revolution in the united states / 18.6 u.s. awards for quality and productivity improvement / 18.7 quality system standards and standardization / 18.8 an apology to those not mentioned

19 models for quality management and problem solving

19.1 evolution of the "quality wheel" / 19.2 names used to describe the quality management movement / 19.3 the baldrige criteria as a quality management model / 19.4 comparing the baldrige criteria and iso 9000 requirements / 19.5 problem-solving models compared to management models / 19.6 the "seven basic tools of statistical process control" / 19.7 tracking and celebrating quality

20 demonstrating the operation of systems of chance causes

20.1 use of group experiments in introducing the subjects of control charts and acceptance sampling procedures / 20.2 demonstrating frequency distributions and control charts for variables / 20.3 demonstrating acceptance sampling by attributes / 20.4 deming's red bead experiment

appendixes

1 glossary of symbols

2 bibliography

3 tables

name index

subject index

preface

part one introduction

1 introduction and overview

1.1 the meaning of quality / 1.2 the focus of this book / 1.3 the control-chart viewpoint / 1.4 scientific sampling / 1.5 use of examples / 1.6 meanings and usage of the words defective and defect / 1.7 many economy studies call for the viewpoint of statistical quality control / 1.8 statistical quality control may have useful by-products / 1.9 reasons for the use of the adjective statistical/ 1.10 four different levels of understanding statistical quality control/ 1.11 nonmanufacturing applications of statistical quality control techniques/ 1.12 some topics covered in part four of this book

part two statistical process control

2 directions for simple x and r charts

2.1 setting up and operating control charts for x and r / 2.2 checklist of necessary steps in using x and r charts / 2.3 some comments on computer software for statistical process control / problems

3 why the control chart works; some statistical concepts

3.1 the need for understanding statistical principles/3.2 description of patterns of variation/3.3 graphic representation of a frequency distribution / 3.4 averages and measures of dispersion / 3.5 sampling statistics and universe parameters / 3.6 the normal curve / 3.7 other frequency curves / 3.8 what the average and standard deviation of a set of numbers really tell/problems

4 why the control chart works; some examples

4.1 the use of control charts to judge whether or not a constant system of chance causes is present / 4.2 use of the control chart in interpretation of a frequency distribution / 4.3 contribution of the control chart to elimination of causes of trouble / 4.4 changes in universe average / 4.5 shift in universe dispersion with no change in universe average / 4.6 changes in universe average and universe dispersion / 4.7 a possible view of the question answered by a control chart / 4.8 nonproduct applications of control charts for variables / 4.9 conflicting expressions for the standard deviation of a set of numbers / problems

5 some fundamentals of the theory of probability

5.1 probability has a mathematical meaning / 5.2 modern concepts of probability theory / 5.3 some theorems of the theory of probability / 5.4 infinite and finite universes / 5.5 the hypergeometric probability distribution / 5.6 the binomial as a probability distribution / 5.7 the poisson law as a probability distribution / 5.8 the normal distribution / 5.9 deciding on the method to be used for calculating probabilities in industrial sampling problems / 5.10 relationship between control charts and certain other statistical techniques / 5.11 random variables / 5.12 point estimates and estimators / 5.13 the problem of selecting a parameter to describe universe dispersion and of choosing an estimator for that parameter / 5.14 sampling from a normal distribution / 5.15 theory of extreme runs / problems

6 the control chart for fraction rejected

.6.1 some practical limitations of control charts for variables / 6.2 control charts for attributes / 6.3 the control chart for fraction rejected / 6.4 the binomial as a probability law that determines the fluctuations of fraction rejected / 6.5 control limits for the p chart / 6.6 problems introduced by variable subgroup size / 6.7 checklist of necessary steps in connection with control chart for fraction rejected / 6.8 sensitivity of the p chart / 6.9 nonproduct applications of p and up charts / 6.1o p charts are not suitable for all data on fraction rejected / problems

7 the control chart for nonconformities

7.1 the place of the c chart in statistical process control / 7.2 distinction between a nonconforming article and a nonconformity / 7.3 limits for the c chart are based on the poisson distribution / 7.4 the combination of poisson distributions / 7.5 conditions favorable to the economic use of the control chart for nonconformities / 7.6 adaptations of the c chart to variations in 1he area of opportunity for a nonconformity / 7.7 probability limits for c and u charts / 7.8 the u chart for nonconformities per multiple units / 7.9 listing individual nonconformities on the form containing a c or u chart / 7.10 the introduction of a control chart may motivate quality improvement / 7.11 classification of nonconformities and their weighting / 7.12 q charts for quality scores and d charts for demerit classifications / 7.13 use of 3 c for approximate calculation of control limits in situations involving the binomial distribution / 7.14 applicability of c chart technique in fields other than statistical process control / problems

8 rational subgrouping

8.1 the information given by the control chart depends on the basis used for selection of subgroups / 8.2 two schemes involving order of production as a basis for subgrouping / 8.3 question addressed by the shewhart control chart / 8.4 sources of variability / 8.5 order of production is not always a sufficient basis for subgrouping / 8.6 need for discrimination in the selection of subgroups / 8.7 identification on a control chart of different sources of subgroups / 8.8 precision, reproducibility and accuracy of methods of measurement / 8.9 relationship between the variability of measured values and the precision of the method of measurement / problems

9 statistical analysis of process capability and for process improvement

9.1 process capability as a step toward process improvement / 9.2 process capability and performance indexes / 9.3 quality by design: design and inspection specifications / 9.4 statistical methods may help in setting better specification limits / 9.5 some common methods of interpretation of a pilot run as a basis for setting tolerances / 9.6 two statistical theorems of great importance in the interrelationship of tolerances / 9.7 experimentation / problems

10 some special process control procedures

10.1 some miscellaneous topics / 10.2 some special topics on shewhart control charts for variables / 10.3 some related special procedures / 10.4 a general test for homogeneity / 10.5 probability limits on control charts for variables / 10.6 control charts for moving averages / 10.7 x chart with a linear trend / 10.8 narrow limit gaging / 10.9 working with short production runs / 10.10 a success chart for production runs of extremely high quality / 10.11 combining process control and product acceptance / 10.12 cumulative sum control chart for averages / problems

part three scientific sampling

11 some fundamental concepts in scientific sampling

11.1 the importance of sampling / 11 .2 some weaknesses of certain traditional practices in acceptance sampling / 11.3 purpose of this chapter / 11.4 lot-by-lot acceptance using single sampling by attributes / 11.5 oc curve of an ideal sampling plan / 11.6 the indexing of acceptance plans by a single point on the oc curve / 11.7 average outgoing quality and the aoql / 11.8 double sampling / 11.9 choosing a sampling plan to minimize average total inspection / 11.10 multiple and sequential sampling / 11.11 randomness in acceptance sampling / problems

12 an aql system for lot-by-lot acceptance sampling by attributes

12.1 selecting an acceptance inspection procedure / 12.2 a historical note regarding acceptance sampling systems based on the aql concept / 12.3 some decisions made in the original establishment of the aql as a quality standard / 12.4 some aspects of the master tables reproduced from the abc standard / 12.5 determining the sample size code letter / 12.6 oc curves under normal, tightened. and reduced inspection / 12.7 single, double, and multiple sampling plans in aql systems / 12.8 classification of defects / 12.9 the formation of inspection lots / 12.10 acceptance based on numbers of defects / 12.11 a systematic record of quality history is an important aspect of statistical acceptance procedures / 12.12 selecting an acceptance plan for an isolated lot / 12.13 importance of aoql values in sampling plans based on the aql / problems

13 other procedures for acceptance sampling by attributes

13.1 two useful volumes of standard tables / 13.2 the dodge-romig tables / 13.3 some reasons for not basing a quality standard on a provision for screening inspection / 13.4 designing single sampling plans for stipulated producer's and consumer's risks / 13.5 a simple aql system proposed by dodge / 13.6 design of a sequential plan having an oc curve passing through two designated points l 13.7 dodge's chain sampling inspection plan / problems

14 systems for acceptance sampling from continuous production

14.1 dodge's aoql plan for continuous production-csp-1/14.2 multilevel continuous sampling plans (csp-m) / 14.3 the mil-std-1235 system for sampling from continuous production / 14.4 aoq functions of some continuous sampling schemes / 14.5 skip-lot sampling / 14.6 further comment on continuous sampling plans / 14.7 unique features of csp plans as guides for spc sampling / problems

15 systems for acceptance sampling by variables

15.1 some advantages and limitations of acceptance sampling by variables l 15.2 some different types of acceptance criteria involving variables / 15.3 using plotted frequency distributions in acceptance sampling / 15.4 use of control charts to identify grand lots / 15.5 computing the oc curve for a known-sigma variables sampling plan based on the assumption of a normal distribution i 15.6 some general aspects of military standard 414 l 15.7 numerical data to illustrate normal inspection under mil-std-414 / 15.8 tightened inspection in mil-std-414 l 15.9 reduced inspection in mil-std-414 / 15.10 an upper specification limit in mil-std-414 / 15.11 two-sided specifications in mll-std-414 / 15.12 the relationship among sample sizes under the standard deviation method, the range method, and the procedures assuming known variability / 15.13 some comments on table 15.4 / 15.14 the choice between unknown-sigma and known-sigma plans / 15.15 some sources of oc curves for variables plans based on the assumption of normality / 15.16 comment on the assumption of a normal distribution in known-sigma and unknown-sigma plans / 15.17 acceptance/rejection plans may be devised to accept on variables criteria but to reject only on attributes criteria / 15.18 international and commercial standards corresponding to mil-std-414 / problems

16 some aspects of life testing and reliability

16.1 purpose of this chapter / 16.2 a conventional model of the probability of equipment failure / 16.3 some modem definitions of reliability / 16.4 the relationship between a constant failure rate and mean life or mean time between failures / 16.5 an experiment to illustrate certain aspects of a constant failure rate / 16.6 the "exponential" reliability function that results from the assumption of a constant failure rate / 16.7 principal u.s. government documents that treat life testing under the assumption of a constant failure rate / 16.8 the broad general usefulness of sampling and tasting standards / problems

part four some related topics

17 some economic aspects of quality decisions

17.1 problems of business altematives are problems in economy / 17.2 some basic concepts in engineering economy / 17.3 three general classes of consequences that should be recognized in making certain quality decisions / 17.4 taguchi's loss function / 17.5 some economic aspects of the margin of safety in design specifications / 17.6 some special difficulties of estimating indirect costs in economy studies / 17.7 did it pay to use statistical quality control? / 17.8 the increasing importance of costs related to product liability / problems

18 some significant events in the development of statistical quality control

18.1 quality and standardization / 18.2 the two architects of statistical quality control / 18.3 quality assurance science and world war ii / 18.4 japan's recovery as a worldclass industrial power / 18.5 the quality cultural revolution in the united states / 18.6 u.s. awards for quality and productivity improvement / 18.7 quality system standards and standardization / 18.8 an apology to those not mentioned

19 models for quality management and problem solving

19.1 evolution of the "quality wheel" / 19.2 names used to describe the quality management movement / 19.3 the baldrige criteria as a quality management model / 19.4 comparing the baldrige criteria and iso 9000 requirements / 19.5 problem-solving models compared to management models / 19.6 the "seven basic tools of statistical process control" / 19.7 tracking and celebrating quality

20 demonstrating the operation of systems of chance causes

20.1 use of group experiments in introducing the subjects of control charts and acceptance sampling procedures / 20.2 demonstrating frequency distributions and control charts for variables / 20.3 demonstrating acceptance sampling by attributes / 20.4 deming's red bead experiment

appendixes

1 glossary of symbols

2 bibliography

3 tables

name index

subject index

Statistical quality control

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