Lot acceptance and compliance testing using the sample mean and an extremum |
190:Y |
QCAS / 48 / 1 / 34 |
On new and modified ranked set sampling procedures |
210:Y |
QCAS / 48 / 1 / 41 |
Safety sampling: A case study |
210:Y |
QCAS / 48 / 1 / 43 |
A review of empirical research on total quality management using scale developing methods: An Australian perspective |
230:Y |
QCAS / 48 / 1 / 45 |
Understanding the cognitive processes of open-ended categorical questions and their effects on data quality |
230:Y |
QCAS / 48 / 1 / 47 |
Virtual inspection: Optimum sample size for POD experiment |
240:Y |
QCAS / 48 / 1 / 49 |
Development of a generic quality function deployment matrix |
323:Y |
QCAS / 48 / 1 / 57 |
Creating a regional learning environment for accelerating company development and growth |
331:Y |
QCAS / 48 / 1 / 63 |
Motivation for ISO 14000 certification: Development of a predictive model |
342:Y |
QCAS / 48 / 1 / 67 |
Customers: A love/hate relationship? |
350:Y |
QCAS / 48 / 1 / 69 |
Under-developed applications: Can end users assess quality? |
359:Y |
QCAS / 48 / 1 / 73 |
On the use of process management in the third world |
410:Y |
QCAS / 48 / 1 / 75 |
Organizational change through quality deposits |
490:Y |
QCAS / 48 / 1 / 79 |
Statistical modeling: The two cultures |
510:Y |
QCAS / 48 / 1 / 81 |
Data fusion and data grafting |
519:Y |
QCAS / 48 / 1 / 83 |
A class of experimental designs for estimating a response surface and variance components |
525:Y |
QCAS / 48 / 1 / 85 |
On today’s menu: Quality |
690:Y |
QCAS / 48 / 1 / 95 |
Process mapping’s next step |
740:Y |
QCAS / 48 / 1 / 99 |
A survey of maintenance policies of deteriorating systems |
840:Y |
QCAS / 48 / 1 / 103 |
Producing reliable software: An experiment |
850:Y |
QCAS / 48 / 1 / 107 |
Assignable causes and auto correlation: Control charts for observations or residuals? |
110:Y |
QCAS / 47 / 6 / 601 |
An accurate algorithm to compute the run length probability distribution, and its convolutions, for a CUSUM chart to control normal mean |
110:Y |
QCAS / 47 / 6 / 605 |
Improvement of process capability through neural networks and robust design: A case study |
120:Y |
QCAS / 47 / 6 / 609 |
SPC – a team effort for process improvement across four Area Control Centers |
190:Y |
QCAS / 47 / 6 / 615 |
CUSUM-based person-fit statistics for adaptive testing |
190:Y |
QCAS / 47 / 6 / 617 |
Generalized case-cohort sampling |
210:Y |
QCAS / 47 / 6 / 623 |
Monitoring of a batch continuous process using mass re-sampling |
210:Y |
QCAS / 47 / 6 / 625 |
Minimum average fraction inspected for TCSP-1 plan |
220:Y |
QCAS / 47 / 6 / 629 |
Multistage ranked set sampling |
220:Y |
QCAS / 47 / 6 / 631 |
Using the sample range as a basis for calculating sample size in power calculations |
240:Y |
QCAS / 47 / 6 / 637 |
Comparison of the 14 deadly diseases and the business excellence model |
311:Y |
QCAS / 47 / 6 / 641 |
Widening the Six Sigma concept: An approach to improve organizational learning |
339:Y |
QCAS / 47 / 6 / 651 |
ISO 9000 certification: The financial performance implications |
342:Y |
QCAS / 47 / 6 / 653 |
It might not be your product |
350:Y |
QCAS / 47 / 6 / 655 |
Customer relationships with service personnel: Do we measure closeness, quality or strength? |
350:Y |
QCAS / 47 / 6 / 657 |
Organizational quality management in emerging economies |
410:Y |
QCAS / 47 / 6 / 663 |
An analysis of quality costs in Australian manufacturing firms |
440:Y |
QCAS / 47 / 6 / 667 |
Accelerated sequential risk-efficient estimation of the mean |
512:Y |
QCAS / 47 / 6 / 669 |
The robustness of the likelihood ratio chi-square test for structural equation models: A meta-analysis |
512:Y |
QCAS / 47 / 6 / 673 |
Optimal estimating equations in mixture distributions accommodating instantaneous or early failures |
512:Y |
QCAS / 47 / 6 / 677 |
Models of association versus causal models for contingency tables |
516:Y |
QCAS / 47 / 6 / 681 |
Improving nonparametric methods by bagging and boosting |
549:Y |
QCAS / 47 / 6 / 683 |
Nonparametric density and regression estimation |
549:Y |
QCAS / 47 / 6 / 685 |
A nonparametric test for size-biasedness in the data |
551:Y |
QCAS / 47 / 6 / 687 |
The strategic function of quality in the management of innovation |
640:Y |
QCAS / 47 / 6 / 693 |
Quality-based synchronization methods of multimedia objects |
670:Y |
QCAS / 47 / 6 / 697 |
Development of a scaling factor identification method using design of experiments for product-family-based product and process design |
690:Y |
QCAS / 47 / 6 / 701 |
The geometric CUSUM chart with sampling inspection for monitoring fraction defective |
110:Y |
QCAS / 47 / 5 / 481 |
The autoregressive T2 chart for monitoring univariate autocorrelated processes |
110:Y |
QCAS / 47 / 5 / 485 |
Relative probability index Crp: An alternative process capability index |
120:Y |
QCAS / 47 / 5 / 489 |
Process capability indices – A review, 1992-2000 |
120:Y |
QCAS / 47 / 5 / 491 |
Sociotechnical reasons for the de-evolution of statistical process control |
190:Y |
QCAS / 47 / 5 / 497 |
Controlling change: Process monitoring and adjustment during transition periods |
190:Y |
QCAS / 47 / 5 / 499 |
Estimators for a Poisson parameter using ranked set sampling |
210:Y |
QCAS / 47 / 5 / 501 |
Quality management system design: A visionary approach |
310:Y |
QCAS / 47 / 5 / 505 |
Design for Six Sigma: 15 lessons learned |
319:Y |
QCAS / 47 / 5 / 509 |
Knowledge dissemination and advancement of organizational excellence |
334:Y |
QCAS / 47 / 5 / 513 |
Communities of practice and organizational performance |
334:Y |
QCAS / 47 / 5 / 515 |
Overview of quality management practices in selected Asian countries |
410:Y |
QCAS / 47 / 5 / 527 |
Total quality management in the West, East and Russia: Are we different? |
410:Y |
QCAS / 47 / 5 / 529 |
A multiple test for comparing two treatments with control: Interval hypotheses approach |
511:Y |
QCAS / 47 / 5 / 531 |
Coupling Bayesian inference and Monte Carlo methods in error propagation |
512:Y |
QCAS / 47 / 5 / 535 |
A diagnostic for assessing the influence of cases on the prediction of missing data |
512:Y |
QCAS / 47 / 5 / 537 |
Variance component testing in multilevel models |
515:Y |
QCAS / 47 / 5 / 541 |
Experimental designs when there are one or more factor constraints |
520:Y |
QCAS / 47 / 5 / 545 |
Switching-one-column follow-up experiments for Plackett-Burman designs |
520:Y |
QCAS / 47 / 5 / 549 |
Sequence-leveled experimental designs at work |
520:Y |
QCAS / 47 / 5 / 551 |
Regression estimators in extreme and median ranked set samples |
540:Y |
QCAS / 47 / 5 / 553 |
Flexible regression modeling with adaptive logistic basis functions |
543:Y |
QCAS / 47 / 5 / 557 |
A study on the effect of power transformation in the ARMA (p, q) model |
544:Y |
QCAS / 47 / 5 / 561 |
A framework for evaluation and prediction of software process improvement success |
730:Y |
QCAS / 47 / 5 / 575 |
Integrating scenario-based and measurement-based software product assessment |
730:Y |
QCAS / 47 / 5 / 577 |
The relationship between ISO/IEC 15504 process capability levels, ISO 9001 certification and organization size: An empirical study |
730:Y |
QCAS / 47 / 5 / 579 |
An empirical evaluation of the ISO/IEC 15504 assessment model |
730:Y |
QCAS / 47 / 5 / 583 |
Foresight with Delphi surveys in Japan |
740:Y |
QCAS / 47 / 5 / 587 |
Six Sigma rolled throughput yield |
790:Y |
QCAS / 47 / 5 / 589 |
A computer program to calculate two-stage short-run control chart factors for (X̄, R) charts |
111:Y |
QCAS / 47 / 4 / 361 |
Median rankit control chart for Weibull distribution |
111:Y |
QCAS / 47 / 4 / 365 |
On the two stage p-chart |
112:Y |
QCAS / 47 / 4 / 369 |
Large-sample interval estimators for process capability indices |
120:Y |
QCAS / 47 / 4 / 371 |