نتایج جستجو برای: control charts

تعداد نتایج: 1341773  

2002
Willem Albers

Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approac...

2011
Marianne Frisén

Industrial production requires multivariate control charts to enable monitoring of several components. Recently there has been an increased interest also in other areas such as detection of bioterrorism, spatial surveillance and transaction strategies in finance. In the literature, several types of multivariate counterparts to the univariate Shewhart, EWMA and CUSUM methods have been proposed. ...

Statistical process control ($SPC$), an internationally recognized technique for improving product quality and productivity, has been widely employed in various industries. $SPC$ relies on the use of control charts to monitor a manufacturing process for identifying causes of process variation and signaling the necessity of corrective action for the process. Fuzzy data exist ubiquitously in the ...

Journal: :مدیریت صنعتی 0
مهدی عباسی عباس ابراهیمی علی جمالی

nowadays statistical control process plays an important role in quality control of products. so wide variety of methods are utilized to do so. but since the most percentage of available information in the discrete control charts are verbal terms, fuzzy and vague ,in most cases it is difficult for us to refine them into the quantitative data. thus in this article we are to change these verbal da...

1998
Stefan H. Steiner

Control charts such as X and R charts are widely used in industry to monitor quality. These charts are effective in detecting large departures from the in-control condition. Other process monitoring methods, such as Cumulative Sum (CUSUM) charts are sequential in nature as they accumulate information from previous observations. CUSUM charts are good at detecting more moderate presistent process...

Journal: :Production Engineering Archives 2013

Saghaei, A., Shokrizadeh, R., Yaquninejad , Y.,

When the objective is quick detection both small and large shifts in the process mean with normal distribution, the generalized likelihood ratio (GLR) control charts have better performance as compared to other control charts. Only the fixed parameters are used in Reynolds and Lou’s presented charts. According to the studies, using variable parameters, detect process shifts faster than fixed pa...

2005
Willem Albers Wilbert C. M. Kallenberg

Standard control charts are very sensitive to estimation effects and/or deviations from normality. Hence a program has been carried out to remedy these problems. This is quite adequate in most circumstances, but not in all. In the present paper, the remaining complication is attacked: what to do if a nonparametric approach is indicated, but too few Phase I observations are available? It is show...

Journal: :Infection control and hospital epidemiology 1994
J T Lee

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. ...

Considering profiles as functional variables, two control charts are proposed for their monitoring in phase II. Due to its conformity with the nature of real-world profiles, applying functional model leads to proposed control charts obtained through functional data analysis techniques with desired features. These include simplicity in calculation and possibility of using them for different prof...

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