Statistical process control (SPC) is widely used in industrial settings to monitor processes for shifts in their distributions. SPC is generally thought of in two distinct phases: Phase–I, in which historical data is analyzed in order to establish an in–control process, and Phase–II, in which new data is monitored for deviations from the in–control form. Traditionally, SPC had been used to moni...

Most statistical process control (SPC) methods are not suitable for monitoring nonlinear and statedependent processes. This article introduces the context-based SPC (CSPC) methodology for statedependent data generated by a finite-memory source. The key idea of the CSPC is to monitor the statistical attributes of a process by comparing two context trees at any monitoring period of time. The firs...

PT Alis Jaya Ciptatama (AJC) is a company engaged in the furniture industry, where products are exported. One of from AJC wine bottle rack. In production racks at AJC, many product defects were found. Therefore, it necessary to conduct further research determine quality product, so that correct improvement obtained. The purpose this study was limits statistical control and factors causing provi...

Statistical process control (SPC) is a method for improving the quality o f products. Control charting plays a most important role in SPC. SPC control charts arc used for monitoring and detecting unnatural process behaviour. Unnatural patterns in control charts indicate unnatural causes for variations. Control chart pattern recognition is therefore important in SPC. Past research shows that alt...

To cite: Fretheim A, Tomic O. BMJ Qual Saf 2015;24: 748–752. INTRODUCTION Time series plots are widely used, across sectors and media, probably because many find them easy to understand. Figure 1 is a time series plot of how the readmission rate in a hospital changed over time (constructed data set). Statistical process control (SPC) and interrupted time series (ITS) designs are two closely rel...

This paper consider an MMLE (Modified Maximum Likelihood Estimation) based scheme to estimate software reliability using exponential distribution. The MMLE is one of the generalized frameworks of software reliability models of Non Homogeneous Poisson Processes (NHPPs). The MMLE gives analytical estimators rather than an iterative approximation to estimate the parameters. In this paper we propos...

background : few studies have focused on syndromic data to determine levels of alarm thresholds to detection of meningitis outbreaks. the purpose of this study was to determine threshold levels of meningitis outbreak in hamadan province, west of iran . methods : data on both confirmed and suspected cases of meningitis (fever and neurological symptom) form 21 march 2010 to 20 march 2012 were use...

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. ...

Chemical process variables are always driven by random noise and disturbances. The closed-loop control yields process measurements that are auto & cross correlated. The influence of auto & cross correlations on statistical process control (SPC) is investigated in detail. It is revealed both auto and cross correlations among the variables will cause unexpected false alarms. Dynamic PCA and ARMA-...