controlling a system with minimum information and regardless of dynamic equations which dominate systems is the aim of intelligent control. one of the common approaches for process control is applying shewhart's quality control charts. neuro-fuzzy networks, as one of the branches of artificial intelligence (ai), can play an effective role in the enforcement of process control's common...

An outbreak of invasive aspergillosis among allogeneic bone marrow transplants: a case-control study. Infect Confvol1985;6:347-355. 3. Sherertz RJ, Belani A, Kramer BS. et al. Impact of air filtration on nosocomialA@ergil-lus infections. Unique risk of bone marrow transplant recipients. A discriminant scorecard for diagnosis of invasive pulmonary asper-gillosis in patients with acute leukemia. ...

In this paper, first the available single charting methods, which have been proposed to detect simultaneous shifts in a single process mean and variance, are reviewed. Then, by designing proper simulation studies these methods are evaluated in terms of in-control and out-ofcontrol average run length criteria (ARL). The results of these simulation experiments show that the EWMA and EWMS methods ...

Two independent methods for improving quality are engineering process control (EPC) and statistical process control (SPC). The first method tries to minimize variability by handling process variables so as to keep the outputs of the process on target. While the latter method, SPC does the same basic task of minimizing variability by supervising and eradicating the assignable causes of variation...

To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in hypothesis testing and SPC that point to key char...

Control limits in traditional Multivariate Quality Control Charts (MQCC), such as Hotelling's T control chart, Multivariate Cumulative Sum (MCUSUM) and Multivariate Exponentially-Weighted Moving Average (MEWMA) control charts are based on multivariate normal assumption. This assumption is not usually satisfied, especially in real life applications. The purpose of a control chart based on suppor...

The Engineering and Fabrication Branch of the Technical Services Department provides a wide range of engineering, design, and fabrication services for the Applied Physics Laboratory. The Branch routinely practices a technique known as "statistical process control" in the design, fabrication, testing, calibration, and quality control phases of its work to ensure the quality of designed and fabri...

In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected...

As pointed out by Woodall and Montgomery (1999), there are a number of disputes in the area of statistical quality control (SQC). There are differences of opinion in all areas of statistical science, but disagreements tend to be more common and more intense in the quality area. This could be due in part to the diversity of those working in the quality field, including quality gurus and their fo...

When performing process monitoring, the classical approach of multivariate statistical process control (MSPC) explicitly assumes the normal operating conditions (NOC) to be distributed normally. If this assumption is not met, usually severe out-of-control situations are missed or incontrol situations can falsely be seen as out-of-control. Combining mixture modelling with MSPC (MM-MSPC) leads to...