scholarly journals A synthetic exponentially weighted moving average control chart to monitor process median based on ranked set sampling

2021 ◽  
Vol 36 ◽  
pp. 01002
Author(s):  
Jing Wen Ng ◽  
Voon Hee Wong ◽  
Sook Theng Pang
Keyword(s):  
Control Chart ◽  
Moving Average ◽  
Length Distribution ◽  
Ranked Set Sampling ◽  
Exponentially Weighted Moving Average ◽  
Process Mean ◽  
Run Length ◽  
Ewma Chart ◽  
Run Length Distribution ◽  
Weighted Moving Average

Exponentially Weighted Moving Average (EWMA) control charts yield insights into data in a way more comprehensible to the practitioners and researchers because of its capability in discovering small to moderate process mean shifts. EWMA control chart is incorporated with conforming run length (CRL) chart, named synthetic EWMA chart, to enhance the performance of the chart in detecting the out-of-control signal. Synthetic EWMA chart based on ranked set sampling (RSS) for monitoring process mean has been proposed as it advanced the detection of chart over a series of mean shifts. With the situation that normality assumption is scarcely attain in practice, we proposed synthetic EWMA median chart based on RSS. Rather than select average run length (ARL) as sole performance evaluating tool, the median and percentiles of run-length distribution are used to examine the performance of the proposed chart as it provides more information on the entire run-length distribution. Near-optimal parameters of the proposed chart will be acquired by setting the incontrol ARL at a designated value. The run length performances of the proposed chart are then compared with the existing charts such as EWMA median chart based on RSS.

scholarly journals PENERAPAN DIAGRAM KONTROL MEWMA DAN MEWMV PADA PENGENDALIAN KARAKTERISTIK KUALITAS AIR (Studi Kasus: Kualitas Pengolahan Air II PDAM Tirta Moedal Kota Semarang)

2018 ◽  
Vol 7 (1) ◽  
pp. 23-32
Author(s):  
Adestya Ayu Maharani ◽  
Mustafid Mustafid ◽  
Sudarno Sudarno
Keyword(s):  
Water Treatment ◽  
Control Chart ◽  
Moving Average ◽  
Process Capability ◽  
Human Consumption ◽  
Exponentially Weighted Moving Average ◽  
Process Mean ◽  
Monitoring Process ◽  
Weighted Moving Average ◽  
Exponentially Weighted

Water is one of the most important elements for human life, water treatment is done for human consumption and must fulfill the health requirements with the levels of certain parameters. Quality of Water Treatment II is the second water purification installation owned by PDAM Tirta Moedal Semarang City with production capacity of 60 l/s. Variables used in the water treatment process are correlated with each other, so used multivariate control chart. The Multivariate Exponentially Weighted Moving Average control chart is used for monitoring process mean, and the Multivariate Exponentially Weighted Moving Variance control chart is used for monitoring process variability. The variables used are colour, turbidity, organic substance, manganese and the total dissolved solid. MEWMA control chart with λ = 0.5, showed that the process mean is controlled statistically. MEWMV control chart showed that variability is controlled statistically in λ = 0.4, ω = 0.2 and L = 3.3213. MEWMA and MEWMV control chart showed that the process is not capable because it obtained the value of process capability index less than 1. Keywords: Water, Multivariate Exponentially Weighted Moving Average, Multivariate Exponentially Weighted Moving Variance, process capability.

A new double exponentially weighted moving average control chart using repetitive sampling

2018 ◽  
Vol 35 (2) ◽  
pp. 387-404 ◽  
Author(s):  
Olatunde Adebayo Adeoti
Keyword(s):  
Control Chart ◽  
Moving Average ◽  
Mean Shift ◽  
Exponentially Weighted Moving Average ◽  
Process Mean ◽  
Content Type ◽  
Design And Implementation ◽  
Average Control ◽  
Weighted Moving Average ◽  
Exponentially Weighted

Purpose The purpose of this paper is to propose a double exponentially weighted moving average control chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the efficiency of detecting small process mean shift. Design/methodology/approach The algorithm for the implementation of the proposed chart is developed and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs are presented for various process mean shift. The performance of the proposed chart is investigated in terms of the average run-length for small process mean shift and compared with the existing DEWMA control chart. Numerical examples are given as illustration of the design and implementation of the proposed chart. Findings The proposed control chart is more efficient than the existing DEWMA control chart in the detection of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift. However, the performance of the proposed chart relatively deteriorates for large smoothing constants. Practical implications The application of repetitive sampling in the control chart literature is gaining wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in the detection of small process mean shift by process control personnel. Originality/value This paper fills a gap in the literature by examining the performance of the repetitive sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in the literature, however, its use based on the DEWMA statistic has not been considered in this context.

Sign in / Sign up

Export Citation Format

Share Document