Statistical quality control

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