scholarly journals The Mixed CUSUM-EWMA (MCE) control chart as a new alternative in the monitoring of a manufacturing process

2019 ◽  
Vol 16 (1) ◽  
pp. 1-13
Author(s):  
Custodio Da Cunha Alves ◽  
Andréa Cristina Konrath ◽  
Elisa Henning ◽  
Olga Maria Formigoni Carvalho Walter ◽  
Edson Pacheco Paladini ◽  
...  
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Process Development ◽  
Correct Choice ◽  
Statistical Quality Control ◽  
Accurate Information ◽  
Statistical Control ◽  
Ewma Chart ◽  
Significant Difference ◽  
Practical Implications

Goal: The objective is to conclude, based on a comparative study, if there is a significant difference in sensitivity between the application of MCE and the individual application of the CUSUM or EWMA chart, i.e., greater sensitivity particularly for cases of lesser magnitude of change. Design/Methodology/Approach: These are an applied research and statistical techniques such as statistical control charts are used for monitoring variability. Results: The results show that the MCE chart signals a process out of statistical control, while individual EWMA and CUSUM charts does not detect any situation out of statistical control for the data analyzed. Limitations: This article is dedicated to measurable variables and individual analysis of quality characteristics, without investing in attribute variables. The MCE chart was applied to items that are essential to the productive process development being analysed. Practical Implications: The practical implications of this study can contribute to: the correct choice of more sensitive control charts to detect mainly small changes in the location (mean) of processes; provide clear and accurate information about the fundamental procedures for the implementation of statistical quality control; and encourage the use of this quality improvement tool. Originality/Value: The MCE control chart is a great differential for the improvement of the quality process of the studied company because it goes beyond what CUSUM and EWMA control charts can identify in terms of variability.

scholarly journals Monitoring process mean with a new EWMA control chart

Production ◽  
2011 ◽  
Vol 21 (2) ◽  
pp. 217-222 ◽  
Author(s):  
Yang Su-Fen ◽  
Tsai Wen-Chi ◽  
Huang Tzee-Ming ◽  
Yang Chi-Chin ◽  
Cheng Smiley
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Population Distribution ◽  
Average Run Length ◽  
Process Data ◽  
Ewma Chart ◽  
Ewma Control Chart ◽  
Simple Statistic ◽  
Run Lengths ◽  
Proper Values

In practice, sometimes the process data did not come from a known population distribution. So the commonly used Shewhart variables control charts are not suitable since their performance could not be properly evaluated. In this paper, we propose a new EWMA Control Chart based on a simple statistic to monitor the small mean shifts in the process with non-normal or unknown distributions. The sampling properties of the new monitoring statistic are explored and the average run lengths of the proposed chart are examined. Furthermore, an Arcsine EWMA Chart is proposed since the average run lengths of the Arcsine EWMA Chart are more reasonable than those of the new EWMA Chart. The Arcsine EWMA Chart is recommended if we are concerned with the proper values of the average run length.

scholarly journals CONTROLE ESTATÍSTICO DE QUALIDADE DA CONDUTIVIDADE HIDRÁULICA EM LUVISSOLO E NEOSSOLO COM VARIAÇÃO DA DENSIDADE DO SOLO

Irriga ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 16-24
Author(s):  
Floriano Luiz Suszek ◽  
Silvio Cesar Sampaio ◽  
Vera Lucia Antunes De Lima
Keyword(s):  
Hydraulic Conductivity ◽  
Control Charts ◽  
Density Variation ◽  
Statistical Quality Control ◽  
Agricultural Drainage ◽  
Sensitivity Index ◽  
Statistical Control ◽  
Soil Physics ◽  
Constant Head ◽  
Improving Accuracy

CONTROLE ESTATÍSTICO DE QUALIDADE DA CONDUTIVIDADE HIDRÁULICA EM LUVISSOLO E NEOSSOLO COM VARIAÇÃO DA DENSIDADE DO SOLO     FLORIANO LUIZ SUSZEK1; SILVIO CÉSAR SAMPAIO2 E VERA LÚCIA ANTUNES DE LIMA3   1Doutor em Engenharia Agrícola, Programa de Pós-Graduação em Engenharia Agrícola (PGEAGRI), Universidade Estadual do Oeste do Paraná (UNIOESTE), Rua Universitária, nº 1619 – Jd. Universitário, CEP: 85809-110, Cascavel, Paraná, Brasil, [email protected]. 2Universidade Estadual do Oeste do Paraná, Departamento de Recursos Hídricos e Saneamento Ambiental, Rua Universitária, nº 1619 – Jd. Universitário, CEP: 85809-110, Cascavel, Paraná, Brasil, [email protected]. 3Universidade Federal de Campina Grande (UFCG), Centro de Tecnologia e Recursos Naturais, Rua Aprígio Veloso, nº 882, Universitário, CEP: 58429-900, Campina Grande, Paraíba, Brasil, [email protected].     1 RESUMO   A condutividade hidráulica é um dos principais fatores para dimensionamento de sistemas de drenagem agrícola. Uma das metodologias utilizadas para a obtenção da condutividade hidráulica é o permeâmetro de carga constante. Porém a grande variação dos resultados gera necessidade de análises para melhorar a precisão destes, como o uso de gráficos de controle estatístico de qualidade. Este trabalho analisou por meio de gráficos de controle, a metodologia do permeâmetro de carga constante para dois solos diferentes na obtenção da condutividade hidráulica, variando a densidade dos solos e analisando seu índice de sensibilidade. O LUVISSOLO CRÔMICO é mais sensível à variação de densidade do solo, para a condutividade hidráulica, do que o NEOSSOLO REGOLÍTICO. Os gráficos de controle foram úteis na melhoria da precisão dos valores analisados, mostrando a variação da condutividade hidráulica e quais foram os pontos fora dos limites desejáveis.   Palavras-chave: Drenagem agrícola, propriedades físicas do solo, permeâmetro de carga constante.     SUSZEK, F. L.; SAMPAIO, S. C.; LIMA, V. L. A. de STATISTICAL QUALITY CONTROL IN HYDRAULIC CONDUCTIVITY FOR LUVISOL AND ENTISOL WITH DENSITY VARIATION     2 ABSTRACT   Hydraulic conductivity is one of the main factors for the design of agricultural drainage systems. One of the methodologies used to obtain the hydraulic conductivity is the constant head permeameter. However, the large variation of results generates the need for analyzes to improve their accuracy, such as the use of quality statistical control graphs. This work analyzed, by means of control charts, the methodology of constant head permeameter for two different soils in obtaining hydraulic conductivity, varying the density of soils and analyzing their sensitivity index. Luvisol is more sensitive to density variation, for hydraulic conductivity, than  entisol. Control graphs were useful in improving  accuracy of the analyzed values, showing the variation of hydraulic conductivity and what were the points outside the desirable limits.   Keywords: Agricultural drainage, soil physics properties, constant head permeameter.

Inspection in Process Control

1998 ◽  
Vol 42 (16) ◽  
pp. 1170-1174
Author(s):  
Somchart Thepvongs ◽  
Brian M. Kleiner
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Signal Detection ◽  
Control Chart ◽  
Control Charts ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Statistical Quality Control ◽  
Total Quality ◽  
Statistical Process

Consistent with the precepts of total quality control and total quality management, there has been a resource shift from incoming and outgoing inspection processes to statistical quality control of processes. Furthermore, process control operators are responsible for their own quality, necessitating the in-process inspection of components. This study treated the statistical process control task of “searching” control charts for out-of-control conditions as an inspection task and applied the Theory of Signal Detection to better understand this behavior and improve performance. Twelve subjects participated in a research study to examine how the portrayal of control chart information affected signal detection theory measures. The type of display did not have a significant effect on the sensitivity and response criterion of subjects. These results are discussed in terms of the applicability of Signal Detection Theory in control chart decision making as well as implications on display design.

scholarly journals Monitoring Mortality Caused by COVID-19 Using Gamma-Distributed Variables Based on Generalized Multiple Dependent State Sampling

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Muhammad Aslam ◽  
G. Srinivasa Rao ◽  
Muhammad Saleem ◽  
Rehan Ahmad Khan Sherwani ◽  
Chi-Hyuck Jun
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Average Run Length ◽  
Real Life ◽  
Quality Characteristics ◽  
Statistical Quality Control ◽  
Nonnormal Distributions ◽  
Run Lengths ◽  
Chart Design ◽  
Dependent State

More recently in statistical quality control studies, researchers are paying more attention to quality characteristics having nonnormal distributions. In the present article, a generalized multiple dependent state (GMDS) sampling control chart is proposed based on the transformation of gamma quality characteristics into a normal distribution. The parameters for the proposed control charts are obtained using in-control average run length (ARL) at specified shape parametric values for different specified average run lengths. The out-of-control ARL of the proposed gamma control chart using GMDS sampling is explored using simulation for various shift size changes in scale parameters to study the performance of the control chart. The proposed gamma control chart performs better than the existing multiple dependent state sampling (MDS) based on gamma distribution and traditional Shewhart control charts in terms of average run lengths. A case study with real-life data from ICU intake to death caused by COVID-19 has been incorporated for the realistic handling of the proposed control chart design.

Monitoring operating room turnaround time: a retrospective analysis

2016 ◽  
Vol 29 (3) ◽  
Author(s):  
Michele Scagliarini ◽  
Mariarosaria Apreda ◽  
Ulrich Wienand ◽  
Giorgia Valpiani
Keyword(s):  
Steady State ◽  
Operating Room ◽  
Control Charts ◽  
Design Methodology ◽  
Turnaround Time ◽  
Statistical Quality Control ◽  
Process Performance ◽  
State Behaviour ◽  
Practical Implications ◽  
Steady State Behaviour

Purpose Operating room turnaround time is a key process indicator for hospital business management: delays lead to a reduced surgical interventions per day with a consequent increase in costs and decrease in efficiency. This study aims to increase understanding by assessing the process’ steady-state behaviour and identifying changes that indicate either improvement or deterioration in quality. Design/methodology/approach With this purpose, we retrospectively applied Shewhart control charts and exponentially weighted moving average control charts to data extracted from an hospital information system. Findings The results showed that statistical process control is able to identify steady-state behaviour process and to detect positive or negative changes in process performance. In particular we detected a deterioration in the process performance coinciding with the change in the operanting room patient transfer staff. Practical implications This study showed that statistical quality control is a valuable tool for monitoring performance indicators. Currently, hospital managers are designing an operating room dashboard which also includes the control charts. Originality/value The article highlights the control chart application to organizational indicators allowing an objective operating room system performance assessment

scholarly journals A Study of Cumulative Quantity Control Chart for a Mixture of Rayleigh Model under a Bayesian Framework

2016 ◽  
Vol 39 (2) ◽  
pp. 185 ◽  
Author(s):  
Muhammad Aslam ◽  
Muhammad Riaz ◽  
Tabassum Naz Sindhu ◽  
Zaheer Ahmed
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Geometric Model ◽  
Mixture Distribution ◽  
Cumulative Distribution ◽  
Statistical Control ◽  
Design Structure ◽  
Weibull Models ◽  
Cumulative Count ◽  
Quantity Control

<p>This study deals with the cumulative charting technique based on a simple and a mixture of Rayleigh models. The respective charting schemes are referred as the SRCQC-chart and the MRCQC-chart. These are stimulated from existing statistical control charts in this direction i.e. the cumulative quantity control (CQC) chart, based on exponential and Weibull models, and the cumulative count control (CCC) chart, based on the simple geometricmodel. Another motivation for this study is the mixture cumulative count control (MCCC) chart based on the two component geometric model. The use of mixture cumulative quantity is an attractive approach for process monitoring. The design structure of the proposed control chart is derived by using the cumulative distribution function of simple, and two components of mixture distribution(s). We observed that the proposed charting structure is efficient in detecting the changes in process parameters. The application of the proposed scheme is illustrated using a real dataset.</p>

scholarly journals Monitoring of drippers during wastewater application through statistical quality control

2020 ◽  
pp. 551-556
Author(s):  
Flavio Daniel Szekut ◽  
Delfran Batista dos Santos ◽  
Carlos Alberto Vieira de Azevedo ◽  
Marcio Antonio Vilas Boas ◽  
Márcio Roberto Klein ◽  
...  
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Statistical Control ◽  
Negative Effects ◽  
Statistical Quality ◽  
Lateral Lines ◽  
Alternative Water ◽  
Semi Arid Region ◽  
The Moment

The use of alternative water sources for irrigation such as wastewaters, promotes innumerous benefits, but investigations must be conducted to minimize the negative effects of this technique. Clogging drippers are of the limitations. This study aimed to monitor the clogging of three models of labyrinth-type drippers subjected to irrigation with wastewater from treated domestic sewage, through statistical quality control using Shewhart charts. The drippers tested were as following: Dripper Streamline 16080 model (Netafim®); Taldrip model (Naadanjain®); and Dripper Tiran 16010 model (Netafim®). The system was installed with five lateral lines per model of dripper on a bench at the field in the Brazilian semi-arid region. The system was evaluated every 36 h of operation at eight collection points in each lateral line, totaling thirty-three evaluations at the end of the experiment, which corresponded to a total of 1188 h of operation. Dripper clogging was identified by the statistical control charts with 432, 540 and 360 h for the drippers Streamline 16080 model, Taldrip model and Tiran 16010 model, respectively, indicating the moment to apply a cleaning process. The monitoring through statistical quality control allowed simultaneously identifying the variability of the process and the reduction in flow rates, identifying the moment of clogging of the system and to carry out actions of unclog.

scholarly journals Study on Likelihood-Ratio-Based Multivariate EWMA Control Chart Using Lasso

2021 ◽  
Vol 25 (1) ◽  
pp. 3-15
Author(s):  
Takumi Saruhashi ◽  
Masato Ohkubo ◽  
Yasushi Nagata
Keyword(s):  
Covariance Matrix ◽  
Likelihood Ratio ◽  
Control Chart ◽  
Control Charts ◽  
Ewma Chart ◽  
Regularization Parameters ◽  
Multivariate Control Chart ◽  
Multivariate Control ◽  
Mean Vector ◽  
Variance Covariance Matrix

Purpose: When applying exponentially weighted moving average (EWMA) multivariate control charts to multivariate statistical process control, in many cases, only some elements of the controlled parameters change. In such situations, control charts applying Lasso are useful. This study proposes a novel multivariate control chart that assumes that only a few elements of the controlled parameters change. Methodology/Approach: We applied Lasso to the conventional likelihood ratio-based EWMA chart; specifically, we considered a multivariate control chart based on a log-likelihood ratio with sparse estimators of the mean vector and variance-covariance matrix. Findings: The results show that 1) it is possible to identify which elements have changed by confirming each sparse estimated parameter, and 2) the proposed procedure outperforms the conventional likelihood ratio-based EWMA chart regardless of the number of parameter elements that change. Research Limitation/Implication: We perform sparse estimation under the assumption that the regularization parameters are known. However, the regularization parameters are often unknown in real life; therefore, it is necessary to discuss how to determine them. Originality/Value of paper: The study provides a natural extension of the conventional likelihood ratio-based EWMA chart to improve interpretability and detection accuracy. Our procedure is expected to solve challenges created by changes in a few elements of the population mean vector and population variance-covariance matrix.

scholarly journals PENGENDALIAN KUALITAS DENGAN MENGGUNAKAN METODE STATISTICAL QUALITY CONTROL (SQC) UNTUK MEMINIMUMKAN PRODUK GAGAL PADA TOKO ROTI BAROKAH BAKERY

2017 ◽  
Vol 7 (1) ◽  
pp. 15-22 ◽  
Author(s):  
Muhammad Syarif Hidayatullah Elmas
Keyword(s):  
Quality Control ◽  
Human Factors ◽  
Control Chart ◽  
Control Charts ◽  
Field Research ◽  
Statistical Quality Control ◽  
Analysis Tool ◽  
Statistical Quality ◽  
Cause And Effect ◽  
Library Research

Quality Control is an activity (company management) to maintain and navigate to product quality (and) services companies can be maintained as planned. Quality Control used the company to minimize failed products using methods of Statistical Quality Control (SQC) so that the company can meet the quality products that have been specified businesses and consumers are satisfied in consuming the product. The purpose of that will be achieved in this research is to determine the method of Statistical Quality Control (SQC) with tekhnik control chart and diagram of cause and effect applied the company Bakery Barokah Bakery in quality control to minimize the product failed. Tekhnik data collection that is used is a library research and field research, while data analysis tool  that  is  used control  chart and  diagram  of  cause  and  effect. The  results  of  the  analysis  of control charts shows that the number of products that are examined as much as 27.710 units, the average of 0,099 product damage or 9.9%. Limitations: UCL supervision of 0,1161 or 11.61%, LCL of 0,0819 or 8,12%. Quality control on  the Bakery Barokah Bakery is  good because the  number of failed products are  still within the boundaries of fair is located between UCL and LCL. While the results from the diagram for result (fish bones), the main factor the causes of the failure of the products of bread in the Bakery Barokah Bakery namely human factors. Where people fail in the making of the bread products. So required training to minimize failed products that occurred caused by human factors.

scholarly journals HYBRID EXPONENTIALLY WEIGHTED MOVING AVERAGE (HEWMA) CONTROL CHART BASED ON EXPONENTIAL TYPE ESTIMATOR OF MEAN

2019 ◽  
pp. 187-198 ◽  
Author(s):  
Syed Muhammad Muslim Raza ◽  
Maqbool Hussain Sial ◽  
Muhammad Haider ◽  
Muhammad Moeen Butt
Keyword(s):  
Control Chart ◽  
Exponential Type ◽  
Control Charts ◽  
Average Run Length ◽  
Moving Average ◽  
Exponentially Weighted Moving Average ◽  
Ewma Chart ◽  
Weighted Moving Average ◽  
Better Than ◽  
Exponentially Weighted

In this paper, we have proposed a Hybrid Exponentially Weighted Moving Average (HEWMA) control chart. The proposed control chart is based on the exponential type estimator for mean using two auxiliary variables (cf. Noor-ul-Amin and Hanif, 2012). We call it an EHEWMA control chart because it is based on the exponential estimator of the mean. From this study, the fact is revealed that E-HEWMA control chart shows more efficient results as compared to traditional/simple EWMA chart and DS.EWMA control chart (cf. Raza and Butt, 2018). The comparison of the E-HEWMA control chart is also performed with the DS-EWMA chart. The proposed chart also outperforms the other control chartsin comparison. The E-HEWMA chart can be used for efficient monitoring of the production process in manufacturing industries.A simulated example has been used to compare the proposed and traditional/simple EWMA charts and DS.EWMA control chart. The control charts' performance is measured using the average run length-out of control (ARL1). It is observed that the proposed chart performs better than existing EWMA control charts.  

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