Sentence examples for moving average control from inspiring English sources

A more efficient method, called 'the geometric moving average control charts' algorithm, was proposed later by Roberts in 1965 [18].

In this paper, we propose a model of a moving average control chart (MA control chart) with a Weibull failure mechanism from an economic viewpoint.

The performances of non-cumulative and cumulative attributes control charts, Shewhart (X and X-bar) and moving average control charts were compared and a moving average control chart calculated on five consecutive samples of one unit with a sampling rate of two samples per week was chosen as a process hygiene criterion to help operators to detect a breaking in their hygiene procedures.

They proposed a control chart that combines the exponentially weighted moving average control chart based on local linear kernel smoothing and a nonparametric regression test under the assumption that observations within and between individual profiles are independent of each other.

Figure 4 shows a moving average control chart for cancer waiting times, with an expected trend and confidence intervals, based on the first year and a half, and with later observations moving strongly outside the projection.

However, control chart methods such as the MEWMA (Multivariate Exponentially Weighted Moving Average) control chart method proposed by Joner and Woodall et al[ 16], usually do not account for underlying changes such as seasonal effects.

Jiang, Tsui, and Woodall (2000) developed a control chart, called the autoregressive moving average (ARMA) control chart, which has been shown suitable for monitoring a series of autocorrelated data.

Two charts were tested to detect small deviations in production processes: the cumulative sum (CUSUM) control chart and the exponentially weighted moving average (EWMA) control chart.

When the process has minor variation, the sensitivity of the exponentially weighted moving average (EWMA) control chart is higher than the C control chart and more accurately reflects the current situation of the process on the control chart.

A nonparametric exponentially weighted moving average (NPEWMA) control chart combines the advantages of a nonparametric control chart with the better shift detection properties of a traditional EWMA chart.

Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial -autocorrelation ((partial -autocorrelation and classical series decomP ACFion and (ii) "in-control" status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma).