Image based statistical process monitoring via partial first order stochastic dominance |
190:Y |
QCAS / 69 / 1-2 / 29 |

A review of dispersion control charts for multivariate individual observations |
190:Y |
QCAS / 68 / 3-4 / 189 |

Abrupt change of process behavior: The Anderson-Darling detection tool |
190:Y |
QCAS / 65 / 1-2 / 15 |

Signed sequential rank CUSUMs |
190:Y |
QCAS / 64 / 5-6 / 373 |

Two-level augmented definitive screening designs |
190:Y |
QCAS / 64 / 1-2 / 43 |

Practitioner advice: ERLDAT-A web-based tool
to design and analyze EWMA control charts |
190:Y |
QCAS / 63 / 5-6 / 385 |

A Phase II nonparametric adaptive exponentially
weighted moving average control chart |
190:Y |
QCAS / 63 / 5-6 / 387 |

Self-starting monitoring scheme for Poisson
count data with varying population sizes |
190:Y |
QCAS / 63 / 5-6 / 391 |

The economic and economic-statistical designs
of Hotellingâ€™s T2 chart on expected average run length |
190:Y |
QCAS / 63 / 5-6 / 395 |

Statistical process control methods
for monitoring in-house reference standards |
190:B |
QCAS / 61 / 4 / 309 |

A quality by design approach for longitudinal quality
attributes |
190:Y |
QCAS / 61 / 1-2 / 17 |

Analytical procedure validation and the quality by design paradigm |
190:Y |
QCAS / 61 / 1-2 / 19 |

A distribution-free multivariate phase I location control chart
for subgrouped data from elliptical distributions |
190:Y |
QCAS / 60 / 4 / 307 |

Using SPC in conjunction with APC |
190:Y |
QCAS / 58 / 4 / 311 |

Bayesian approach to change point estimation in multivariate SPC |
190:Y |
QCAS / 58 / 3 / 185 |

Variation reduction for multistage manufacturing processes: A comparison survey of statistical-process-control vs. stream- of-variation methodologies |
190:Y |
QCAS / 56 / 5-6 / 437 |

A cumulative sum scheme for monitoring frequency and size of an event |
190:Y |
QCAS / 56 / 4 / 315 |

Linear filter model representations for integrated process control with repeated adjustments and monitoring |
190:Y |
QCAS / 56 / 3 / 187 |

A visualization decision support tool for multivariate SPC diagnosis using marginal CUSUM glyphs |
190:Y |
QCAS / 56 / 3 / 189 |

Trading machines: Using SPC to assess performance of financial trading systems |
190:A |
QCAS / 56 / 1-2 / 27 |

An industrial monitoring problem |
190:M |
QCAS / 56 / 1-2 / 29 |

Some Reflections on G.E.P. Box’s contributions to statistics and quality improvement |
190:Y |
QCAS / 56 / 1-2 / 31 |

George Box: A source of inspiration for quality and productivity |
190:Y |
QCAS / 56 / 1-2 / 33 |

The determination of economic production run length and manufacturing target by considering quality loss function |
190:A |
QCAS / 55 / 1-2 / 23 |

Statistical quality control for DNA microarray data: A model of type I error |
190:B |
QCAS / 54 / 3 / 193 |

Distorting value added: The use of longitudinal, vertically scaled student achievement data for growth based, value added accountability |
190:T |
QCAS / 52 / 3 / 267 |

Lot streaming for quality control in two-stage batch production |
190:Y |
QCAS / 51 / 6 / 607 |

A virtual system for vision based SPC |
190:Y |
QCAS / 51 / 2 / 147 |

A phenomenological taxonomy for systematizing knowledge on nonconformances |
190:Y |
QCAS / 50 / 6 / 623 |

Should observations be grouped for effective process monitoring? |
190:Y |
QCAS / 50 / 4 / 367 |

Proposal and implementation of the “Science SQC” quality control principle |
190:Y |
QCAS / 49 / 6 / 607 |

Data quality in statistical process control |
190:Y |
QCAS / 49 / 5 / 519 |

An empirical indicator of product appearance for process control |
190:Y |
QCAS / 49 / 4 / 381 |

Context-based statistical process control: A monitoring procedure for state-dependent processes |
190:Y |
QCAS / 49 / 4 / 383 |

SPC: From chaos to wiping the floor |
190:Y |
QCAS / 49 / 2 / 129 |

Statistical process control procedures for controlling the weight of packets of biscuits |
190:Y |
QCAS / 49 / 1 / 27 |

The advantages of continuous measurements over pass/fail data |
190:Y |
QCAS / 49 / 1 / 29 |

An economic inspection interval for control of defective items in a hot rolling mill |
190:M |
QCAS / 48 / 6 / 615 |

Statistical control of a Six Sigma process |
190:Y |
QCAS / 48 / 6 / 617 |

Using factor effects analysis to improve statistical process control |
190:Y |
QCAS / 48 / 3 / 253 |

Using factor effects analysis to improve statistical process control |
190:Y |
QCAS / 48 / 2 / 123 |

Lot acceptance and compliance testing using the sample mean and an extremum |
190:Y |
QCAS / 48 / 1 / 34 |

Evaluating environmental performance using statistical process control techniques |
190:Z |
QCAS / 48 / 1 / 37 |

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 |

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 |

Beyond improved quality: The motivational effects of statistical process control |
190:A |
QCAS / 47 / 4 / 379 |

Robustness of robust process optimization |
190:Y |
QCAS / 47 / 4 / 381 |

Some new classroom cases for teaching statistical quality control methods |
190:T |
QCAS / 47 / 3 / 255 |

The multivariate short-run snapshot Q chart |
190:Y |
QCAS / 47 / 3 / 257 |

The statistical monitoring of a complex manufacturing process |
190:M |
QCAS / 47 / 2 / 133 |

Multidimensional scaling used in multivariate statistical process control |
190:Y |
QCAS / 47 / 2 / 135 |

Joint estimation: SPC method for short-run autocorrelated data |
190:Y |
QCAS / 47 / 2 / 137 |

SPC: Making it work for the gas transportation business |
190:Z |
QCAS / 47 / 1 / 17 |

Understanding the hierarchy of process control |
190:Y |
QCAS / 46 / 5 / 503 |

Controversies and contradictions in statistical process control |
190:Y |
QCAS / 46 / 4 / 387 |

Transforming the exponential for SPC applications |
190:Y |
QCAS / 45 / 1 / 21 |