A nonparametric double generally weighted moving average signed‐rank control chart for monitoring process location

2020 ◽  
Vol 36 (7) ◽  
pp. 2441-2458 ◽  
Author(s):  
Vasileios Alevizakos ◽  
Christos Koukouvinos ◽  
Kashinath Chatterjee
Keyword(s):  
Control Chart ◽  
Moving Average ◽  
Signed Rank ◽  
Monitoring Process ◽  
Process Location ◽  
Weighted Moving Average

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.

scholarly journals Design of SN2-NEWMA Control Chart for Monitoring Process having Indeterminate Production Data

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 742 ◽  
Author(s):  
Aslam ◽  
Bantan ◽  
Khan
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Control Chart ◽  
Moving Average ◽  
Logarithmic Transformation ◽  
Production Data ◽  
Exponentially Weighted Moving Average ◽  
Monitoring Process ◽  
Weighted Moving Average ◽  
Exponentially Weighted

The existing charts for monitoring the variance are designed under the assumption that all production data must consist of exact, precise, and determined observations. This paper presents the design of a new neutrosophic exponentially weighted moving average (NEWMA) combining with a neutrosophic logarithmic transformation chart for monitoring the variance having neutrosophic numbers. The computation of the neutrosophic control chart parameters is done through the neutrosophic Monte Carlo simulation (NMCS). The performance of the proposed chart is discussed with the existing charts.

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