scholarly journals Uniformity microsprinkler irrigation system using statistical quality control

2017 ◽  
Vol 47 (4) ◽  
Author(s):  
Maurício Guy de Andrade ◽  
Marcio Antonio Vilas Boas ◽  
Jair Antonio Cruz Siqueira ◽  
Mireille Sato ◽  
Jonathan Dieter ◽  
...  
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Irrigation System ◽  
Process Capability ◽  
Process Capability Index ◽  
Statistical Quality Control ◽  
Uniformity Coefficient ◽  
Statistical Quality ◽  
Capability Index ◽  
Shewhart Control

ABSTRACT: The objective of this study was to evaluate the use of statistical quality control tools in the analysis of the uniformity of a microsprinkler irrigation system. For the analysis of irrigation Christiansen uniformity coefficient (CUC) and the distribution uniformity coefficient (DU) were statistically analyzed by means of the Shewhart control charts and process capability index (Cp). For the experiment 25 tests were carried out with a single micro sprinkler and subsequently seven different spacing between micro sprinklers were simulated. Control charts contributed to the diagnosis of the treatments to be under control and with satisfactory uniformity outcomes. Increase in process capability index was directly proportional to the average of CUC and DU.

scholarly journals Statistical Quality Control in Uniformity of Drip Irrigation With Different Slopes

2019 ◽  
Vol 11 (16) ◽  
pp. 195
Author(s):  
Allan Remor Lopes ◽  
Marcio Antonio Vilas Boas ◽  
Felix Augusto Pazuch ◽  
Luciano Dalla Corte ◽  
Diane Aparecida Ostroski ◽  
...  
Keyword(s):  
Quality Control ◽  
Drip Irrigation ◽  
Irrigation System ◽  
Statistical Quality Control ◽  
Statistical Control ◽  
Control Zone ◽  
Uniformity Coefficient ◽  
Statistical Quality

The topography directly influences the functioning of an irrigation system, being necessary the determination of the uniformity to verify its performance. Statistical quality control is a powerful tool for verifying the quality of a process. Thus, it was aimed to use the statistical control of quality in the evaluation of the uniformity of a drip irrigation system in different slopes. The Christiansen’s uniformity coefficient (UC) and Uniformity of Distribution (UD) were determined and analyzed by the control graphs of Shewhart, Zones and CUSUM and by the indices of process capacity (Cp, Cpl and Cpk), in different slopes (0%, 2% and -2%). The slope irrigation was more uniform (UC = 99.03% and UD = 98.45%), however, for all the graphs studied it was out of statistical control. Zone charts were more sensitive than the CUSUM and Shewhart charts.

scholarly journals STATISTICAL QUALITY CONTROL AND ELECTRICAL CONDUCTIVITY FOR EVALUATION OF THE UNIFORMITY OF DIFFERENT DRIP FERTIGATION SOLUTIONS

Irriga ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 264-280
Author(s):  
Bruno Marcos Nunes Cosmo ◽  
Mauricio Guy de Andrade ◽  
Tatiani Mayara Galeriani ◽  
Eliane Hermes ◽  
Márcio Antônio Vilas Boas ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Quality Control ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Water Control ◽  
Uniformity Coefficient ◽  
Statistical Quality ◽  
Quality Control Charts ◽  
Randomized Design ◽  
Drip Fertigation

Population growth has led to an intensified search for ways to increase the efficiency of agricultural production, including improvements of irrigation systems. The aim of this work was to evaluate the uniformity of different drip fertigation techniques, as well as their monitoring using electrical conductivity measurements and statistical quality control charts. For this, an experiment was performed according to a fully randomized design, with six treatments: T1) water (control); T2) Forth Frutas fertilizer; T3) Fortgreen fertilizer; T4) water (control); T5) Bio Bokashi liquid fertilizer; and T6) swine production wastewater. Each treatment consisted of 25 assays (replications). For the assays, 16 collection points were selected for measurements of volume, pH, and electrical conductivity. The data were analyzed using the Christiansen uniformity coefficient, the distribution uniformity coefficient, and the coefficient of variation of the total flow, employing Tukey’s test (5% level), together with statistical quality control charts. The results revealed uniformity above 90% for irrigation and fertigation, while statistically better control was obtained for irrigation. It could be concluded that irrigation and fertigation were similar in terms of uniformity, demonstrating the feasibility of using different fertigation solutions, while the control charts enabled efficient monitoring of the uniformity of the systems.

Monitoring intensive care unit performance using statistical quality control charts

1993 ◽  
Vol 10 (3) ◽  
pp. 155-161 ◽  
Author(s):  
William H. Chamberlin ◽  
Kevin A. Lane ◽  
James N. Kennedy ◽  
Scott D. Bradley ◽  
Charles L. Rice
Keyword(s):  
Intensive Care Unit ◽  
Quality Control ◽  
Intensive Care ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Statistical Quality ◽  
Quality Control Charts ◽  
Unit Performance

scholarly journals On-the-Fly Massively Multitemporal Change Detection Using Statistical Quality Control Charts and Landsat Data

2014 ◽  
Vol 52 (6) ◽  
pp. 3316-3332 ◽  
Author(s):  
Evan B. Brooks ◽  
Randolph H. Wynne ◽  
Valerie A. Thomas ◽  
Christine E. Blinn ◽  
John W. Coulston
Keyword(s):  
Quality Control ◽  
Change Detection ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Landsat Data ◽  
Statistical Quality ◽  
Quality Control Charts

scholarly journals Control Charts: An Introduction to Statistical Quality Control.

1948 ◽  
Vol 43 (242) ◽  
pp. 343
Author(s):  
Joseph M. Juran ◽  
Mason E. Wescott ◽  
Edward S. Smith
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Statistical Quality

scholarly journals Analisis Pengendalian Kualitas Menggunakan Bagan Kendali Bivariat dengan Copula pada Industri Manufactur di Indonesia

2020 ◽  
Vol 6 (1) ◽  
pp. 27
Author(s):  
Tika Endah Lestari ◽  
Sri Susilawati Islam
Keyword(s):  
Quality Control ◽  
Distribution Function ◽  
Control Charts ◽  
Control Process ◽  
Simple Random Sampling ◽  
Statistical Quality Control ◽  
Consumer Decision Making ◽  
Manufacturing Companies ◽  
Statistical Quality ◽  
Quality Control Process

Product quality control is an important factor for the industrial world because good quality control and carried out continuously will be able to detect abnormal production results quickly, so that anticipatory action can be taken immediately. Quality is a major factor in consumer decision making before buying goods / services. The problem that occurs at this time in manufacturing companies in Indonesia is how the statistical quality control process can be applied properly. The purpose of this statistical analysis is to find out the statistical quality control process that is applied to manufacturing companies in Indonesia using bivariate control charts with copula. Copula is a function that combines a multivariate distribution function with a uniform one-dimensional marginal distribution function, in this condition the Copula used is the Archimedean Copula group. The method used in this data collection is a simple random sampling with the sample used are three manufacturing companies in Indonesia which covers the areas of Jakarta, Bandung and Makassar. The implementation of Copula in this control chart results in Frank Copula being the best Copula, this supports that the use of Copula in the quality control process has a good role

scholarly journals Statistical quality control to emission uniformity in micro sprinkler with autonomous photovoltaic pumping

2021 ◽  
Vol 10 (11) ◽  
pp. e581101119867
Author(s):  
Soni Willian Haupenthal ◽  
Marcio Antonio Vilas Boas ◽  
Jair Antonio Cruz Siqueira ◽  
Luciene Kazue Tokura ◽  
Lais Fernanda Juchem do Nascimento
Keyword(s):  
Control Charts ◽  
Irrigation System ◽  
Photovoltaic System ◽  
Statistical Quality Control ◽  
State University ◽  
Shewhart Control Charts ◽  
Pumping System ◽  
Shewhart Control ◽  
Flow Pressure ◽  
Pressure Stability

This work aimed to evaluate a microsprinkler irrigation system using photovoltaic energy without energy storage. The influence of photovoltaic pumping on irrigation was evaluated from the Emission Uniformity, Shewhart control charts and Process Capacity. The experiment consisted of two amorphous photovoltaic panels connected in parallel, directly connected to a water pump, where the flow of the pumping system was carried out through a ½” tube (main line), to the irrigation system composed of four microsprinklers. The voltage and current parameters were collected, and the power of the photovoltaic system was calculated, while for the irrigation system the pressures of the four microsprinklers were measured to later calculate the flow rate of the irrigation system. The experiment was conducted at the State University of Western Paraná, UNIOESTE, where 25 days of collection were carried out, in the open, at four different times, from 10:00 am to 11:00 am, from 11:05 am to 12:05 pm, from 2:00 pm to 3:00 pm and from 3:05 pm to 4:05 pm . Power generation presented a low coefficient of variation throughout the day, which resulted in flow and pressure stability, culminating in an Emission Uniformity (UE) value qualified as excellent (93.66%) according to the ASAE. The values of energy generation, flow, pressure, and emission uniformity presented a Process Capacity (CP) value above 1.33, defining the process as capable and adequate throughout the analyzed period.

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