November 1, 2015 Version 0.5.2 Date 2015-10-31 Title Statistical Process Control -Collection of Some Useful Functions Author Sven Knoth Maintainer Sven Knoth Depends R (>= 1.8.0) Description Evaluation of control charts by means of the zero-state, steady-state ARL (Average Run Length) and RL quantiles. Setting up control charts for given in-control ARL. The control charts un...

To evaluate the surveillance performance of a control chart with charting statistic sum log likelihood ratios in statistical process (SPC), this paper, we give proof procedure based on Markov chains for asymptotic estimation average run length (ARL) kind chart. The out-of-control ARL 1 </msub...

The cumulative sum (CUSUM) control chart is widely used in industry for the detection of small and moderate shifts in process location and dispersion. For efficient monitoring of process variability, we present several CUSUM control charts for monitoring changes in standard deviation of a normal process. The newly developed control charts based on well-structured sampling techniques - extreme r...

Usually, there are two phases in constructing a multivariate control chart. Phase I is to estimate the in-control process parameters and to establish control limits using historical data. Phase II is when the control limits are used to monitor the process. This paper focuses on determining the optimal number of samples in Phase I since number of samples affect the cost of quality control in pra...

In certain statistical process control applications, quality of a process or product can be characterized by a function commonly referred to as profile. Some of the potential applications of profile monitoring are cases where quality characteristic of interest is modelled using binary,multinomial or ordinal variables. In this paper, profiles with multinomial response are studied. For this purpo...

The Extended Exponentially Weighted Moving Average (extended EWMA) control chart is one of the charts and can be used to quickly detect a small shift. performance evaluated with average run length (ARL). Due deriving explicit formulas for ARL on two-sided extended EWMA trend autoregressive or AR(p) model has not been reported previously. aim this study derive as well AR(1) AR(2) models exponent...

The existing optimal design of the fixed sampling interval S2-EWMA control chart to monitor the sample variance of a process is based on the average run length (ARL) criterion. Since the shape of the run length distribution changes with the magnitude of the shift in the variance, the median run length (MRL) gives a more meaningful explanation about the in-control and out-of-control performances...

Monitoring disturbances in process dispersion using control chart is mostly based on the assumption that quality characteristic follows normal distribution, which not case many real-life situations. This paper proposes a set of new charts homogeneously weighted moving average (HWMA) scheme, for efficient detection shifts standard deviation (σ). These are variety σ estimators and investigated as...

Quality improvement is playing the key role in success of a business. Reduction variability main step for quality. Control charts are developed purpose monitoring quality characteristics with aim reducing variability. In many industries instead continuous variable categorical (ordinal) data used to measure interest. Hence developing control techniques ordinal has become recent research focus. p...

A memory-type control chart is an important tool of statistical process for monitoring small to moderate shifts in the manufacturing process. Using prior information by Bayesian approach helpful charts. In this paper, a new hybrid exponentially weighted moving average (HEWMA) suggested under theory using ranked set sampling (RSS) schemes posterior and predictive distribution with informative di...