CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: Pareto chart analysis</title> <meta name="description" content="Search results for: Pareto chart analysis"> <meta name="keywords" content="Pareto chart analysis"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="Pareto chart analysis" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Pareto chart analysis"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 28068</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Pareto chart analysis</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28068</span> Taguchi Approach for the Optimization of the Stitching Defects of Knitted Garments</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adel%20El-Hadidy">Adel El-Hadidy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For any industry, the production and quality management or wastages reductions have major impingement on overall factory economy. This work discusses the quality improvement of garment industry by applying Pareto analysis, cause and effect diagram and Taguchi experimental design. The main purpose of the work is to reduce the stitching defects, which will also minimize the rejection and reworks rate. Application of Pareto chart, fish bone diagram and Process Sigma Level/and or Performance Level tools helps solving those problems on priority basis. Among all, only sewing, defects are responsible form 69.3% to 97.3 % of total defects. Process Sigma level has been improved from 0.79 to 1.3 and performance rate improved, from F to D level. The results showed that the new set of sewing parameters was superior to the original one. It can be seen that fabric size has the largest effect on the sewing defects and that needle size has the smallest effect on the stitching defects. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=garment" title="garment">garment</a>, <a href="https://publications.waset.org/abstracts/search?q=sewing%20defects" title=" sewing defects"> sewing defects</a>, <a href="https://publications.waset.org/abstracts/search?q=cost%20of%20rework" title=" cost of rework"> cost of rework</a>, <a href="https://publications.waset.org/abstracts/search?q=DMAIC" title=" DMAIC"> DMAIC</a>, <a href="https://publications.waset.org/abstracts/search?q=sigma%20level" title=" sigma level"> sigma level</a>, <a href="https://publications.waset.org/abstracts/search?q=cause%20and%20effect%20diagram" title=" cause and effect diagram"> cause and effect diagram</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20analysis" title=" Pareto analysis"> Pareto analysis</a> </p> <a href="https://publications.waset.org/abstracts/95883/taguchi-approach-for-the-optimization-of-the-stitching-defects-of-knitted-garments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95883.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">165</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28067</span> The Variable Sampling Interval Xbar Chart versus the Double Sampling Xbar Chart</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michael%20B.%20C.%20Khoo">Michael B. C. Khoo</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20L.%20Khoo"> J. L. Khoo</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20C.%20Yeong"> W. C. Yeong</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20L.%20Teoh"> W. L. Teoh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Shewhart Xbar control chart is a useful process monitoring tool in manufacturing industries to detect the presence of assignable causes. However, it is insensitive in detecting small process shifts. To circumvent this problem, adaptive control charts are suggested. An adaptive chart enables at least one of the chart’s parameters to be adjusted to increase the chart’s sensitivity. Two common adaptive charts that exist in the literature are the double sampling (DS) Xbar and variable sampling interval (VSI) Xbar charts. This paper compares the performances of the DS and VSI Xbar charts, based on the average time to signal (ATS) criterion. The ATS profiles of the DS Xbar and VSI Xbar charts are obtained using the Mathematica and Statistical Analysis System (SAS) programs, respectively. The results show that the VSI Xbar chart is generally superior to the DS Xbar chart. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20charts" title="adaptive charts">adaptive charts</a>, <a href="https://publications.waset.org/abstracts/search?q=average%20time%20to%20signal" title=" average time to signal"> average time to signal</a>, <a href="https://publications.waset.org/abstracts/search?q=double%20sampling" title=" double sampling"> double sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=charts" title=" charts"> charts</a>, <a href="https://publications.waset.org/abstracts/search?q=variable%20sampling%20interval" title=" variable sampling interval"> variable sampling interval</a> </p> <a href="https://publications.waset.org/abstracts/45295/the-variable-sampling-interval-xbar-chart-versus-the-double-sampling-xbar-chart" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45295.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">286</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28066</span> Analytical Hierarchical Process for Multi-Criteria Decision-Making</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Luis%20Javier%20Serrano%20Tamayo">Luis Javier Serrano Tamayo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research on technology makes a first approach to the selection of an amphibious landing ship with strategic capabilities, through the implementation of a multi-criteria model using Analytical Hierarchical Process (AHP), in which a significant group of alternatives of latest technology has been considered. The variables were grouped at different levels to match design and performance characteristics, which affect the lifecycle as well as the acquisition, maintenance and operational costs. The model yielded an overall measure of effectiveness and an overall measure of cost of each kind of ship that was compared each other inside the model and showed in a Pareto chart. The modeling was developed using the Expert Choice software, based on AHP method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytic%20hierarchy%20process" title="analytic hierarchy process">analytic hierarchy process</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision-making" title=" multi-criteria decision-making"> multi-criteria decision-making</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20analysis" title=" Pareto analysis"> Pareto analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=Colombian%20Marine%20Corps" title=" Colombian Marine Corps"> Colombian Marine Corps</a>, <a href="https://publications.waset.org/abstracts/search?q=projection%20operations" title=" projection operations"> projection operations</a>, <a href="https://publications.waset.org/abstracts/search?q=expert%20choice" title=" expert choice"> expert choice</a>, <a href="https://publications.waset.org/abstracts/search?q=amphibious%20landing%20ship" title=" amphibious landing ship"> amphibious landing ship</a> </p> <a href="https://publications.waset.org/abstracts/11178/analytical-hierarchical-process-for-multi-criteria-decision-making" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11178.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">548</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28065</span> A Flexible Pareto Distribution Using α-Power Transformation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shumaila%20Ehtisham">Shumaila Ehtisham</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In Statistical Distribution Theory, considering an additional parameter to classical distributions is a usual practice. In this study, a new distribution referred to as α-Power Pareto distribution is introduced by including an extra parameter. Several properties of the proposed distribution including explicit expressions for the moment generating function, mode, quantiles, entropies and order statistics are obtained. Unknown parameters have been estimated by using maximum likelihood estimation technique. Two real datasets have been considered to examine the usefulness of the proposed distribution. It has been observed that α-Power Pareto distribution outperforms while compared to different variants of Pareto distribution on the basis of model selection criteria. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=%CE%B1-power%20transformation" title="α-power transformation">α-power transformation</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20estimation" title=" maximum likelihood estimation"> maximum likelihood estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=moment%20generating%20function" title=" moment generating function"> moment generating function</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20distribution" title=" Pareto distribution"> Pareto distribution</a> </p> <a href="https://publications.waset.org/abstracts/89859/a-flexible-pareto-distribution-using-a-power-transformation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89859.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">215</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28064</span> Enzymatic Hydrolysis of Sugar Cane Bagasse Using Recombinant Hemicellulases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lorena%20C.%20Cintra">Lorena C. Cintra</a>, <a href="https://publications.waset.org/abstracts/search?q=Izadora%20M.%20De%20Oliveira"> Izadora M. De Oliveira</a>, <a href="https://publications.waset.org/abstracts/search?q=Amanda%20G.%20Fernandes"> Amanda G. Fernandes</a>, <a href="https://publications.waset.org/abstracts/search?q=Francieli%20Colussi"> Francieli Colussi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ros%C3%A1lia%20S.%20A.%20Jesu%C3%ADno"> Rosália S. A. Jesuíno</a>, <a href="https://publications.waset.org/abstracts/search?q=Fabr%C3%ADcia%20P.%20Faria"> Fabrícia P. Faria</a>, <a href="https://publications.waset.org/abstracts/search?q=Cirano%20J.%20Ulhoa"> Cirano J. Ulhoa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Xylan is the main component of hemicellulose and for its complete degradation is required cooperative action of a system consisting of several enzymes including endo-xylanases (XYN), β-xylosidases (XYL) and α-L-arabinofuranosidases (ABF). The recombinant hemicellulolytic enzymes an endoxylanase (HXYN2), β-xylosidase (HXYLA), and an α-L-arabinofuranosidase (ABF3) were used in hydrolysis tests. These three enzymes are produced by filamentous fungi and were expressed heterologously and produced in Pichia pastoris previously. The aim of this work was to evaluate the effect of recombinant hemicellulolytic enzymes on the enzymatic hydrolysis of sugarcane bagasse (SCB). The interaction between the three recombinant enzymes during SCB pre-treated by steam explosion hydrolysis was performed with different concentrations of HXYN2, HXYLA and ABF3 in different ratios in according to a central composite rotational design (CCRD) 23, including six axial points and six central points, totaling 20 assays. The influence of the factors was assessed by analyzing the main effects and interaction between the factors, calculated using Statistica 8.0 software (StatSoft Inc. Tulsa, OK, USA). The Pareto chart was constructed with this software and showed the values of the Student’s t test for each recombinant enzyme. It was considered as response variable the quantification of reducing sugars by DNS (mg/mL). The Pareto chart showed that the recombinant enzyme ABF3 exerted more significant effect during SCB hydrolysis, with higher concentrations and with the lowest concentration of this enzyme. It was performed analysis of variance according to Fisher method (ANOVA). In ANOVA for the release of reducing sugars (mg/ml) as the variable response, the concentration of ABF3 showed significance during hydrolysis SCB. The result obtained by ANOVA, is in accordance with those presented in the analysis method based on the statistical Student's t (Pareto chart). The degradation of the central chain of xylan by HXYN2 and HXYLA was more strongly influenced by ABF3 action. A model was obtained, and it describes the performance of the interaction of all three enzymes for the release of reducing sugars, and can be used to better explain the results of the statistical analysis. The formulation capable of releasing the higher levels of reducing sugars had the following concentrations: HXYN2 with 600 U/g of substrate, HXYLA with 11.5 U.g-1 and ABF3 with 0.32 U.g-1. In conclusion, the recombinant enzyme that has a more significant effect during SCB hydrolysis was ABF3. It is noteworthy that the xylan present in the SCB is arabinoglucoronoxylan, due to this fact debranching enzymes are important to allow access of enzymes that act on the central chain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=experimental%20design" title="experimental design">experimental design</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrolysis" title=" hydrolysis"> hydrolysis</a>, <a href="https://publications.waset.org/abstracts/search?q=recombinant%20enzymes" title=" recombinant enzymes"> recombinant enzymes</a>, <a href="https://publications.waset.org/abstracts/search?q=sugar%20cane%20bagasse" title=" sugar cane bagasse"> sugar cane bagasse</a> </p> <a href="https://publications.waset.org/abstracts/60314/enzymatic-hydrolysis-of-sugar-cane-bagasse-using-recombinant-hemicellulases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60314.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">229</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28063</span> The Application of Pareto Local Search to the Single-Objective Quadratic Assignment Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Alsheddy">Abdullah Alsheddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the employment of Pareto optimality as a strategy to help (single-objective) local search escaping local optima. Instead of local search, Pareto local search is applied to solve the quadratic assignment problem which is multi-objectivized by adding a helper objective. The additional objective is defined as a function of the primary one with augmented penalties that are dynamically updated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pareto%20optimization" title="Pareto optimization">Pareto optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objectivization" title=" multi-objectivization"> multi-objectivization</a>, <a href="https://publications.waset.org/abstracts/search?q=quadratic%20assignment%20problem" title=" quadratic assignment problem"> quadratic assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20search" title=" local search"> local search</a> </p> <a href="https://publications.waset.org/abstracts/9877/the-application-of-pareto-local-search-to-the-single-objective-quadratic-assignment-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9877.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">466</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28062</span> Critical Analysis of Heat Exchanger Cycle for its Maintainability Using Failure Modes and Effect Analysis and Pareto Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sayali%20Vyas">Sayali Vyas</a>, <a href="https://publications.waset.org/abstracts/search?q=Atharva%20Desai"> Atharva Desai</a>, <a href="https://publications.waset.org/abstracts/search?q=Shreyas%20Badave"> Shreyas Badave</a>, <a href="https://publications.waset.org/abstracts/search?q=Apurv%20Kulkarni"> Apurv Kulkarni</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Rajiv"> B. Rajiv</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FMEA" title="FMEA">FMEA</a>, <a href="https://publications.waset.org/abstracts/search?q=heat%20exchanger%20cycle" title=" heat exchanger cycle"> heat exchanger cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=Ishikawa%20diagram" title=" Ishikawa diagram"> Ishikawa diagram</a>, <a href="https://publications.waset.org/abstracts/search?q=pareto%20analysis" title=" pareto analysis"> pareto analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=RPN%20%28Risk%20Priority%20Number%29" title=" RPN (Risk Priority Number)"> RPN (Risk Priority Number)</a> </p> <a href="https://publications.waset.org/abstracts/70737/critical-analysis-of-heat-exchanger-cycle-for-its-maintainability-using-failure-modes-and-effect-analysis-and-pareto-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70737.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">402</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28061</span> An EWMA P-Chart Based on Improved Square Root Transformation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saowanit%20Sukparungsee">Saowanit Sukparungsee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Generally, the traditional Shewhart p chart has been developed by for charting the binomial data. This chart has been developed using the normal approximation with condition as low defect level and the small to moderate sample size. In real applications, however, are away from these assumptions due to skewness in the exact distribution. In this paper, a modified Exponentially Weighted Moving Average (EWMA) control chat for detecting a change in binomial data by improving square root transformations, namely ISRT p EWMA control chart. The numerical results show that ISRT p EWMA chart is superior to ISRT p chart for small to moderate shifts, otherwise, the latter is better for large shifts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=number%20of%20defects" title="number of defects">number of defects</a>, <a href="https://publications.waset.org/abstracts/search?q=exponentially%20weighted%20moving%20average" title=" exponentially weighted moving average"> exponentially weighted moving average</a>, <a href="https://publications.waset.org/abstracts/search?q=average%20run%20length" title=" average run length"> average run length</a>, <a href="https://publications.waset.org/abstracts/search?q=square%20root%20transformations" title=" square root transformations"> square root transformations</a> </p> <a href="https://publications.waset.org/abstracts/10613/an-ewma-p-chart-based-on-improved-square-root-transformation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10613.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">440</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28060</span> An Extended Inverse Pareto Distribution, with Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdel%20Hadi%20Ebraheim">Abdel Hadi Ebraheim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pareto%20distribution" title="pareto distribution">pareto distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=marshal-Olkin" title=" marshal-Olkin"> marshal-Olkin</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability" title=" reliability"> reliability</a>, <a href="https://publications.waset.org/abstracts/search?q=hazard%20functions" title=" hazard functions"> hazard functions</a>, <a href="https://publications.waset.org/abstracts/search?q=moments" title=" moments"> moments</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation" title=" estimation"> estimation</a> </p> <a href="https://publications.waset.org/abstracts/169013/an-extended-inverse-pareto-distribution-with-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169013.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">82</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28059</span> On Multiobjective Optimization to Improve the Scalability of Fog Application Deployments Using Fogtorch</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suleiman%20Aliyu">Suleiman Aliyu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Integrating IoT applications with Fog systems presents challenges in optimization due to diverse environments and conflicting objectives. This study explores achieving Pareto optimal deployments for Fog-based IoT systems to address growing QoS demands. We introduce Pareto optimality to balance competing performance metrics. Using the FogTorch optimization framework, we propose a hybrid approach (Backtracking search with branch and bound) for scalable IoT deployments. Our research highlights the advantages of Pareto optimality over single-objective methods and emphasizes the role of FogTorch in this context. Initial results show improvements in IoT deployment cost in Fog systems, promoting resource-efficient strategies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pareto%20optimality" title="pareto optimality">pareto optimality</a>, <a href="https://publications.waset.org/abstracts/search?q=fog%20application%20deployment" title=" fog application deployment"> fog application deployment</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=internet%20of%20things" title=" internet of things"> internet of things</a> </p> <a href="https://publications.waset.org/abstracts/175224/on-multiobjective-optimization-to-improve-the-scalability-of-fog-application-deployments-using-fogtorch" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175224.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">88</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28058</span> Statistical Design of Synthetic VP X-bar Control Chat Using Markov Chain Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Akbar%20Heydari">Ali Akbar Heydari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Control charts are an important tool of statistical quality control. Thesecharts are used to detect and eliminate unwanted special causes of variation that occurred during aperiod of time. The design and operation of control charts require the determination of three design parameters: the sample size (n), the sampling interval (h), and the width coefficient of control limits (k). Thevariable parameters (VP) x-bar controlchart is the x-barchart in which all the design parameters vary between twovalues. These values are a function of the most recent process information. In fact, in the VP x-bar chart, the position of each sample point on the chart establishes the size of the next sample and the timeof its sampling. The synthetic x-barcontrol chartwhich integrates the x-bar chart and the conforming run length (CRL) chart, provides significant improvement in terms of detection power over the basic x-bar chart for all levels of mean shifts. In this paper, we introduce the syntheticVP x-bar control chart for monitoring changes in the process mean. To determine the design parameters, we used a statistical design based on the minimum out of control average run length (ARL) criteria. The optimal chart parameters of the proposed chart are obtained using the Markov chain approach. A numerical example is also done to show the performance of the proposed chart and comparing it with the other control charts. The results show that our proposed syntheticVP x-bar controlchart perform better than the synthetic x-bar controlchart for all shift parameter values. Also, the syntheticVP x-bar controlchart perform better than the VP x-bar control chart for the moderate or large shift parameter values. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=control%20chart" title="control chart">control chart</a>, <a href="https://publications.waset.org/abstracts/search?q=markov%20chain%20approach" title=" markov chain approach"> markov chain approach</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20design" title=" statistical design"> statistical design</a>, <a href="https://publications.waset.org/abstracts/search?q=synthetic" title=" synthetic"> synthetic</a>, <a href="https://publications.waset.org/abstracts/search?q=variable%20parameter" title=" variable parameter"> variable parameter</a> </p> <a href="https://publications.waset.org/abstracts/146094/statistical-design-of-synthetic-vp-x-bar-control-chat-using-markov-chain-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146094.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">154</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28057</span> Optimal Design for SARMA(P,Q)L Process of EWMA Control Chart</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yupaporn%20Areepong">Yupaporn Areepong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20run%20length" title="average run length">average run length</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20parameters" title=" optimal parameters"> optimal parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=exponentially%20weighted%20moving%20average%20%28EWMA%29" title=" exponentially weighted moving average (EWMA)"> exponentially weighted moving average (EWMA)</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20chart" title=" control chart"> control chart</a> </p> <a href="https://publications.waset.org/abstracts/10653/optimal-design-for-sarmapql-process-of-ewma-control-chart" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10653.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">560</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28056</span> Application of Hyperbinomial Distribution in Developing a Modified p-Chart</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shourav%20Ahmed">Shourav Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Gulam%20Kibria"> M. Gulam Kibria</a>, <a href="https://publications.waset.org/abstracts/search?q=Kais%20Zaman"> Kais Zaman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Control charts graphically verify variation in quality parameters. Attribute type control charts deal with quality parameters that can only hold two states, e.g., good or bad, yes or no, etc. At present, p-control chart is most commonly used to deal with attribute type data. In construction of p-control chart using binomial distribution, the value of proportion non-conforming must be known or estimated from limited sample information. As the probability distribution of fraction non-conforming (p) is considered in hyperbinomial distribution unlike a constant value in case of binomial distribution, it reduces the risk of false detection. In this study, a statistical control chart is proposed based on hyperbinomial distribution when prior estimate of proportion non-conforming is unavailable and is estimated from limited sample information. We developed the control limits of the proposed modified p-chart using the mean and variance of hyperbinomial distribution. The proposed modified p-chart can also utilize additional sample information when they are available. The study also validates the use of modified p-chart by comparing with the result obtained using cumulative distribution function of hyperbinomial distribution. The study clearly indicates that the use of hyperbinomial distribution in construction of p-control chart yields much accurate estimate of quality parameters than using binomial distribution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=binomial%20distribution" title="binomial distribution">binomial distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20charts" title=" control charts"> control charts</a>, <a href="https://publications.waset.org/abstracts/search?q=cumulative%20distribution%20function" title=" cumulative distribution function"> cumulative distribution function</a>, <a href="https://publications.waset.org/abstracts/search?q=hyper%20binomial%20distribution" title=" hyper binomial distribution"> hyper binomial distribution</a> </p> <a href="https://publications.waset.org/abstracts/90750/application-of-hyperbinomial-distribution-in-developing-a-modified-p-chart" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90750.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">279</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28055</span> The Generalized Pareto Distribution as a Model for Sequential Order Statistics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahdy%20%E2%80%8EEsmailian">Mahdy ‎Esmailian</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahdi%20%E2%80%8EDoostparast"> Mahdi ‎Doostparast</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20%E2%80%8EParsian"> Ahmad ‎Parsian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> ‎In this article‎, ‎sequential order statistics (SOS) censoring type II samples coming from the generalized Pareto distribution are considered‎. ‎Maximum likelihood (ML) estimators of the unknown parameters are derived on the basis of the available multiple SOS data‎. ‎Necessary conditions for existence and uniqueness of the derived ML estimates are given‎. Due to complexity in the proposed likelihood function‎, ‎a useful re-parametrization is suggested‎. ‎For illustrative purposes‎, ‎a Monte Carlo simulation study is conducted and an illustrative example is analysed‎. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bayesian%20estimation%E2%80%8E" title="bayesian estimation‎">bayesian estimation‎</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20pareto%20distribution%E2%80%8E" title=" generalized pareto distribution‎"> generalized pareto distribution‎</a>, <a href="https://publications.waset.org/abstracts/search?q=%E2%80%8Emaximum%20likelihood%20%20estimation%E2%80%8E" title=" ‎maximum likelihood estimation‎"> ‎maximum likelihood estimation‎</a>, <a href="https://publications.waset.org/abstracts/search?q=sequential%20order%20statistics" title=" sequential order statistics"> sequential order statistics</a> </p> <a href="https://publications.waset.org/abstracts/26988/the-generalized-pareto-distribution-as-a-model-for-sequential-order-statistics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26988.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">509</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28054</span> A Novel Guided Search Based Multi-Objective Evolutionary Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Baviskar">A. Baviskar</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Sandeep"> C. Sandeep</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Shankar"> K. Shankar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Solving Multi-objective Optimization Problems requires faster convergence and better spread. Though existing Evolutionary Algorithms (EA's) are able to achieve this, the computation effort can further be reduced by hybridizing them with innovative strategies. This study is focuses on converging to the pareto front faster while adapting the advantages of Strength Pareto Evolutionary Algorithm-II (SPEA-II) for a better spread. Two different approaches based on optimizing the objective functions independently are implemented. In the first method, the decision variables corresponding to the optima of individual objective functions are strategically used to guide the search towards the pareto front. In the second method, boundary points of the pareto front are calculated and their decision variables are seeded to the initial population. Both the methods are applied to different constrained and unconstrained multi-objective test functions. It is observed that proposed guided search based algorithm gives better convergence and diversity than several well-known existing algorithms (such as NSGA-II and SPEA-II) in considerably less number of iterations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=boundary%20points" title="boundary points">boundary points</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithms%20%28EA%27s%29" title=" evolutionary algorithms (EA's)"> evolutionary algorithms (EA's)</a>, <a href="https://publications.waset.org/abstracts/search?q=guided%20search" title=" guided search"> guided search</a>, <a href="https://publications.waset.org/abstracts/search?q=strength%20pareto%20evolutionary%20algorithm-II%20%28SPEA-II%29" title=" strength pareto evolutionary algorithm-II (SPEA-II)"> strength pareto evolutionary algorithm-II (SPEA-II)</a> </p> <a href="https://publications.waset.org/abstracts/40983/a-novel-guided-search-based-multi-objective-evolutionary-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40983.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">277</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28053</span> Improving Overall Equipment Effectiveness of CNC-VMC by Implementing Kobetsu Kaizen</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nakul%20Agrawal">Nakul Agrawal</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20M.%20Puri"> Y. M. Puri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> TPM methodology is a proven approach to increase Overall Equipment Effectiveness (OEE) of machine. OEE is an established method to monitor and improve the effectiveness of manufacturing process. OEE is a product of equipment availability, performance efficiency and quality performance of manufacturing operations. The paper presents a project work for improving OEE of CNC-VMC in a manufacturing industry with the help of TPM tools Kaizen and Autonomous Maintenance. The aim of paper is to enhance OEE by minimizing the breakdown and re-work, increase availability, performance and quality. The calculated OEE of bottle necking machines for 4 months is lower of 53.3%. Root Cause Analysis RCA tools like fishbone diagram, Pareto chart are used for determining the reasons behind low OEE. While Tool like Why-Why analysis is use for determining the basis reasons for low OEE. Tools like Kaizen and Autonomous Maintenance are effectively implemented on CNC-VMC which eliminate the causes of breakdown and prevent from reoccurring. The result obtains from approach shows that OEE of CNC-VMC improved from 53.3% to 73.7% which saves an average sum of Rs.3, 19,000. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OEE" title="OEE">OEE</a>, <a href="https://publications.waset.org/abstracts/search?q=TPM" title=" TPM"> TPM</a>, <a href="https://publications.waset.org/abstracts/search?q=Kaizen" title=" Kaizen"> Kaizen</a>, <a href="https://publications.waset.org/abstracts/search?q=CNC-VMC" title=" CNC-VMC"> CNC-VMC</a>, <a href="https://publications.waset.org/abstracts/search?q=why-why%20analysis" title=" why-why analysis"> why-why analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=RCA" title=" RCA "> RCA </a> </p> <a href="https://publications.waset.org/abstracts/38288/improving-overall-equipment-effectiveness-of-cnc-vmc-by-implementing-kobetsu-kaizen" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38288.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">394</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28052</span> Modeling of Maximum Rainfall Using Poisson-Generalized Pareto Distribution in Kigali, Rwanda</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20Iyamuremye">Emmanuel Iyamuremye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Extreme rainfall events have caused significant damage to agriculture, ecology, and infrastructure, disruption of human activities, injury, and loss of life. They also have significant social, economic, and environmental consequences because they considerably damage urban as well as rural areas. Early detection of extreme maximum rainfall helps to implement strategies and measures, before they occur, hence mitigating the consequences. Extreme value theory has been used widely in modeling extreme rainfall and in various disciplines, such as financial markets, the insurance industry, failure cases. Climatic extremes have been analyzed by using either generalized extreme value (GEV) or generalized Pareto (GP) distributions, which provides evidence of the importance of modeling extreme rainfall from different regions of the world. In this paper, we focused on Peak Over Thresholds approach, where the Poisson-generalized Pareto distribution is considered as the proper distribution for the study of the exceedances. This research also considers the use of the generalized Pareto (GP) distribution with a Poisson model for arrivals to describe peaks over a threshold. The research used statistical techniques to fit models that used to predict extreme rainfall in Kigali. The results indicate that the proposed Poisson-GP distribution provides a better fit to maximum monthly rainfall data. Further, the Poisson-GP models are able to estimate various return levels. The research also found a slow increase in return levels for maximum monthly rainfall for higher return periods, and further, the intervals are increasingly wider as the return period is increasing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=exceedances" title="exceedances">exceedances</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title=" extreme value theory"> extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20Pareto%20distribution" title=" generalized Pareto distribution"> generalized Pareto distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=Poisson%20generalized%20Pareto%20distribution" title=" Poisson generalized Pareto distribution"> Poisson generalized Pareto distribution</a> </p> <a href="https://publications.waset.org/abstracts/127379/modeling-of-maximum-rainfall-using-poisson-generalized-pareto-distribution-in-kigali-rwanda" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127379.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">135</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28051</span> A Study on the False Alarm Rates of MEWMA and MCUSUM Control Charts When the Parameters Are Estimated</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Umar%20Farouk%20Abbas">Umar Farouk Abbas</a>, <a href="https://publications.waset.org/abstracts/search?q=Danjuma%20Mustapha"> Danjuma Mustapha</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamisu%20Idi"> Hamisu Idi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is now a known fact that quality is an important issue in manufacturing industries. A control chart is an integrated and powerful tool in statistical process control (SPC). The mean µ and standard deviation σ parameters are estimated. In general, the multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) are used in the detection of small shifts in joint monitoring of several correlated variables; the charts used information from past data which makes them sensitive to small shifts. The aim of the paper is to compare the performance of Shewhart xbar, MEWMA, and MCUSUM control charts in terms of their false rates when parameters are estimated with autocorrelation. A simulation was conducted in R software to generate the average run length (ARL) values of each of the charts. After the analysis, the results show that a comparison of the false alarm rates of the charts shows that MEWMA chart has lower false alarm rates than the MCUSUM chart at various levels of parameter estimated to the number of ARL0 (in control) values. Also noticed was that the sample size has an advert effect on the false alarm of the control charts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20run%20length" title="average run length">average run length</a>, <a href="https://publications.waset.org/abstracts/search?q=MCUSUM%20chart" title=" MCUSUM chart"> MCUSUM chart</a>, <a href="https://publications.waset.org/abstracts/search?q=MEWMA%20chart" title=" MEWMA chart"> MEWMA chart</a>, <a href="https://publications.waset.org/abstracts/search?q=false%20alarm%20rate" title=" false alarm rate"> false alarm rate</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title=" parameter estimation"> parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/106504/a-study-on-the-false-alarm-rates-of-mewma-and-mcusum-control-charts-when-the-parameters-are-estimated" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/106504.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">222</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28050</span> A Hybrid Pareto-Based Swarm Optimization Algorithm for the Multi-Objective Flexible Job Shop Scheduling Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aydin%20Teymourifar">Aydin Teymourifar</a>, <a href="https://publications.waset.org/abstracts/search?q=Gurkan%20Ozturk"> Gurkan Ozturk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a new hybrid particle swarm optimization algorithm is proposed for the multi-objective flexible job shop scheduling problem that is very important and hard combinatorial problem. The Pareto approach is used for solving the multi-objective problem. Several new local search heuristics are integrated into an algorithm based on the critical block concept to enhance the performance of the algorithm. The algorithm is compared with the recently published multi-objective algorithms based on benchmarks selected from the literature. Several metrics are used for quantifying performance and comparison of the achieved solutions. The algorithms are also compared based on the Weighting summation of objectives approach. The proposed algorithm can find the Pareto solutions more efficiently than the compared algorithms in less computational time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=swarm-based%20optimization" title="swarm-based optimization">swarm-based optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20search" title=" local search"> local search</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20optimality" title=" Pareto optimality"> Pareto optimality</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20job%20shop%20scheduling" title=" flexible job shop scheduling"> flexible job shop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a> </p> <a href="https://publications.waset.org/abstracts/72144/a-hybrid-pareto-based-swarm-optimization-algorithm-for-the-multi-objective-flexible-job-shop-scheduling-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72144.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">367</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28049</span> Optimal Bayesian Chart for Controlling Expected Number of Defects in Production Processes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=V.%20Makis">V. Makis</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Jafari"> L. Jafari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we develop an optimal Bayesian chart to control the expected number of defects per inspection unit in production processes with long production runs. We formulate this control problem in the optimal stopping framework. The objective is to determine the optimal stopping rule minimizing the long-run expected average cost per unit time considering partial information obtained from the process sampling at regular epochs. We prove the optimality of the control limit policy, i.e., the process is stopped and the search for assignable causes is initiated when the posterior probability that the process is out of control exceeds a control limit. An algorithm in the semi-Markov decision process framework is developed to calculate the optimal control limit and the corresponding average cost. Numerical examples are presented to illustrate the developed optimal control chart and to compare it with the traditional u-chart. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20u-chart" title="Bayesian u-chart">Bayesian u-chart</a>, <a href="https://publications.waset.org/abstracts/search?q=economic%20design" title=" economic design"> economic design</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20stopping" title=" optimal stopping"> optimal stopping</a>, <a href="https://publications.waset.org/abstracts/search?q=semi-Markov%20decision%20process" title=" semi-Markov decision process"> semi-Markov decision process</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20process%20control" title=" statistical process control"> statistical process control</a> </p> <a href="https://publications.waset.org/abstracts/62841/optimal-bayesian-chart-for-controlling-expected-number-of-defects-in-production-processes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62841.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">573</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28048</span> Optimum Stratiﬁcation of a Skewed Population</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20K.%20Rao">D. K. Rao</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20G.%20M.%20Khan"> M. G. M. Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20G.%20Reddy"> K. G. Reddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The focus of this paper is to develop a technique of solving a combined problem of determining Optimum Strata Boundaries (OSB) and Optimum Sample Size (OSS) of each stratum, when the population understudy is skewed and the study variable has a Pareto frequency distribution. The problem of determining the OSB is formulated as a Mathematical Programming Problem (MPP) which is then solved by dynamic programming technique. A numerical example is presented to illustrate the computational details of the proposed method. The proposed technique is useful to obtain OSB and OSS for a Pareto type skewed population, which minimizes the variance of the estimate of population mean. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=strati%EF%AC%81ed%20sampling" title="stratiﬁed sampling">stratiﬁed sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=optimum%20strata%20boundaries" title=" optimum strata boundaries"> optimum strata boundaries</a>, <a href="https://publications.waset.org/abstracts/search?q=optimum%20sample%20size" title=" optimum sample size"> optimum sample size</a>, <a href="https://publications.waset.org/abstracts/search?q=pareto%20distribution" title=" pareto distribution"> pareto distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20programming%20problem" title=" mathematical programming problem"> mathematical programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20programming%20technique" title=" dynamic programming technique"> dynamic programming technique</a> </p> <a href="https://publications.waset.org/abstracts/5894/optimum-stratification-of-a-skewed-population" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5894.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">453</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28047</span> Design Data Sorter Circuit Using Insertion Sorting Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hoda%20Abugharsa">Hoda Abugharsa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we propose to design a sorter circuit using insertion sorting algorithm. The circuit will be designed using Algorithmic State Machines (ASM) method. That means converting the insertion sorting flowchart into an ASM chart. Then the ASM chart will be used to design the sorter circuit and the control unit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=insert%20sorting%20algorithm" title="insert sorting algorithm">insert sorting algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=ASM%20chart" title=" ASM chart"> ASM chart</a>, <a href="https://publications.waset.org/abstracts/search?q=sorter%20circuit" title=" sorter circuit"> sorter circuit</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20machine" title=" state machine"> state machine</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20unit" title=" control unit"> control unit</a> </p> <a href="https://publications.waset.org/abstracts/5614/design-data-sorter-circuit-using-insertion-sorting-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5614.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">445</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28046</span> Analysis of Diabetes Patients Using Pearson, Cost Optimization, Control Chart Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Devatha%20Kalyan%20Kumar">Devatha Kalyan Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Poovarasan"> R. Poovarasan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have taken certain important factors and health parameters of diabetes patients especially among children by birth (pediatric congenital) where using the above three metrics methods we are going to assess the importance of each attributes in the dataset and thereby determining the most highly responsible and co-related attribute causing diabetics among young patients. We use cost optimization, control chart and Spearmen methodologies for the real-time application of finding the data efficiency in this diabetes dataset. The Spearmen methodology is the correlation methodologies used in software development process to identify the complexity between the various modules of the software. Identifying the complexity is important because if the complexity is higher, then there is a higher chance of occurrence of the risk in the software. With the use of control; chart mean, variance and standard deviation of data are calculated. With the use of Cost optimization model, we find to optimize the variables. Hence we choose the Spearmen, control chart and cost optimization methods to assess the data efficiency in diabetes datasets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=correlation" title="correlation">correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=congenital%20diabetics" title=" congenital diabetics"> congenital diabetics</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20relationship" title=" linear relationship"> linear relationship</a>, <a href="https://publications.waset.org/abstracts/search?q=monotonic%20function" title=" monotonic function"> monotonic function</a>, <a href="https://publications.waset.org/abstracts/search?q=ranking%20samples" title=" ranking samples"> ranking samples</a>, <a href="https://publications.waset.org/abstracts/search?q=pediatric" title=" pediatric"> pediatric</a> </p> <a href="https://publications.waset.org/abstracts/72132/analysis-of-diabetes-patients-using-pearson-cost-optimization-control-chart-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72132.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">256</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28045</span> Performance Evaluation of Karanja Oil Based Biodiesel Engine Using Modified Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20Bhushan">G. Bhushan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Dhingra"> S. Dhingra</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20K.%20Dubey"> K. K. Dubey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the evaluation of performance (BSFC and BTE), combustion (P<sub>max</sub>) and emission (CO, NO<sub>x</sub>, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title="genetic algorithm">genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=rsm" title=" rsm"> rsm</a>, <a href="https://publications.waset.org/abstracts/search?q=biodiesel" title=" biodiesel"> biodiesel</a>, <a href="https://publications.waset.org/abstracts/search?q=karanja" title=" karanja"> karanja</a> </p> <a href="https://publications.waset.org/abstracts/51865/performance-evaluation-of-karanja-oil-based-biodiesel-engine-using-modified-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51865.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">305</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28044</span> Process Monitoring Based on Parameterless Self-Organizing Map</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Young%20Jae%20Choung">Young Jae Choung</a>, <a href="https://publications.waset.org/abstracts/search?q=Seoung%20Bum%20Kim"> Seoung Bum Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=control%20chart" title="control chart">control chart</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter-less%20self-organizing%20map" title=" parameter-less self-organizing map"> parameter-less self-organizing map</a>, <a href="https://publications.waset.org/abstracts/search?q=self-organizing%20map" title=" self-organizing map"> self-organizing map</a>, <a href="https://publications.waset.org/abstracts/search?q=time-varying%20property" title=" time-varying property"> time-varying property</a> </p> <a href="https://publications.waset.org/abstracts/52108/process-monitoring-based-on-parameterless-self-organizing-map" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52108.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">275</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28043</span> Optimal Bayesian Control of the Proportion of Defectives in a Manufacturing Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Viliam%20Makis">Viliam Makis</a>, <a href="https://publications.waset.org/abstracts/search?q=Farnoosh%20Naderkhani"> Farnoosh Naderkhani</a>, <a href="https://publications.waset.org/abstracts/search?q=Leila%20Jafari"> Leila Jafari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a model and an algorithm for the calculation of the optimal control limit, average cost, sample size, and the sampling interval for an optimal Bayesian chart to control the proportion of defective items produced using a semi-Markov decision process approach. Traditional p-chart has been widely used for controlling the proportion of defectives in various kinds of production processes for many years. It is well known that traditional non-Bayesian charts are not optimal, but very few optimal Bayesian control charts have been developed in the literature, mostly considering finite horizon. The objective of this paper is to develop a fast computational algorithm to obtain the optimal parameters of a Bayesian p-chart. The decision problem is formulated in the partially observable framework and the developed algorithm is illustrated by a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20control%20chart" title="Bayesian control chart">Bayesian control chart</a>, <a href="https://publications.waset.org/abstracts/search?q=semi-Markov%20decision%20process" title=" semi-Markov decision process"> semi-Markov decision process</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20control" title=" quality control"> quality control</a>, <a href="https://publications.waset.org/abstracts/search?q=partially%20observable%20process" title=" partially observable process"> partially observable process</a> </p> <a href="https://publications.waset.org/abstracts/49751/optimal-bayesian-control-of-the-proportion-of-defectives-in-a-manufacturing-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49751.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">318</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28042</span> EWMA and MEWMA Control Charts for Monitoring Mean and Variance in Industrial Processes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=L.%20A.%20Toro">L. A. Toro</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Prieto"> N. Prieto</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20J.%20Vargas"> J. J. Vargas </a> </p> <p class="card-text"><strong>Abstract:</strong></p> There are many control charts for monitoring mean and variance. Among these, the X y R, X y S, S2 Hotteling and Shewhart control charts, for mentioning some, are widely used for monitoring mean a variance in industrial processes. In particular, the Shewhart charts are based on the information about the process contained in the current observation only and ignore any information given by the entire sequence of points. Moreover, that the Shewhart chart is a control chart without memory. Consequently, Shewhart control charts are found to be less sensitive in detecting smaller shifts, particularly smaller than 1.5 times of the standard deviation. These kind of small shifts are important in many industrial applications. In this study and effective alternative to Shewhart control chart was implemented. In case of univariate process an Exponentially Moving Average (EWMA) control chart was developed and Multivariate Exponentially Moving Average (MEWMA) control chart in case of multivariate process. Both of these charts were based on memory and perform better that Shewhart chart while detecting smaller shifts. In these charts, information the past sample is cumulated up the current sample and then the decision about the process control is taken. The mentioned characteristic of EWMA and MEWMA charts, are of the paramount importance when it is necessary to control industrial process, because it is possible to correct or predict problems in the processes before they come to a dangerous limit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=control%20charts" title="control charts">control charts</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariate%20exponentially%20moving%20average%20%28MEWMA%29" title=" multivariate exponentially moving average (MEWMA)"> multivariate exponentially moving average (MEWMA)</a>, <a href="https://publications.waset.org/abstracts/search?q=exponentially%20moving%20average%20%28EWMA%29" title=" exponentially moving average (EWMA)"> exponentially moving average (EWMA)</a>, <a href="https://publications.waset.org/abstracts/search?q=industrial%20control%20process" title=" industrial control process"> industrial control process</a> </p> <a href="https://publications.waset.org/abstracts/38377/ewma-and-mewma-control-charts-for-monitoring-mean-and-variance-in-industrial-processes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38377.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">354</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28041</span> Economic Design of a Quality Control Chart for the Proportion of Defective Items</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Encarnaci%C3%B3n%20%C3%81lvarez-Verdejo">Encarnación Álvarez-Verdejo</a>, <a href="https://publications.waset.org/abstracts/search?q=Ra%C3%BAl%20Amor-Pulido"> Raúl Amor-Pulido</a>, <a href="https://publications.waset.org/abstracts/search?q=Pablo%20J.%20Moya-Fern%C3%A1ndez"> Pablo J. Moya-Fernández</a>, <a href="https://publications.waset.org/abstracts/search?q=Juan%20F.%20Mu%C3%B1oz-Rosas"> Juan F. Muñoz-Rosas</a>, <a href="https://publications.waset.org/abstracts/search?q=Francisco%20J.%20Blanco-Encomienda"> Francisco J. Blanco-Encomienda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Many companies use the statistical tool named as statistical quality control, and which can have a high cost for the companies interested on these statistical tools. The evaluation of the quality of products and services is an important topic, but the reduction of the cost of the implantation of the statistical quality control also has important benefits for the companies. For this reason, it is important to implement a economic design for the various steps included into the statistical quality control. In this paper, we describe some relevant aspects related to the economic design of a quality control chart for the proportion of defective items. They are very important because the suggested issues can reduce the cost of implementing a quality control chart for the proportion of defective items. Note that the main purpose of this chart is to evaluate and control the proportion of defective items of a production process. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=proportion" title="proportion">proportion</a>, <a href="https://publications.waset.org/abstracts/search?q=type%20I%20error" title=" type I error"> type I error</a>, <a href="https://publications.waset.org/abstracts/search?q=economic%20plan" title=" economic plan"> economic plan</a>, <a href="https://publications.waset.org/abstracts/search?q=distribution%20function" title=" distribution function"> distribution function</a> </p> <a href="https://publications.waset.org/abstracts/42442/economic-design-of-a-quality-control-chart-for-the-proportion-of-defective-items" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42442.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">443</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28040</span> Analysis of Labor Effectiveness at Green Tea Dry Sorting Workstation for Increasing Tea Factory Competitiveness</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayu%20Anggara">Bayu Anggara</a>, <a href="https://publications.waset.org/abstracts/search?q=Arita%20Dewi%20Nugrahini"> Arita Dewi Nugrahini</a>, <a href="https://publications.waset.org/abstracts/search?q=Didik%20Purwadi"> Didik Purwadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Dry sorting workstation needs labor to produce green tea in Gambung Tea Factory. Observation results show that there is labor who are not working at the moment and doing overtime jobs to meet production targets. The measurement of the level of labor effectiveness has never been done before. The purpose of this study is to determine the level of labor effectiveness and provide recommendations for improvement based on the results of the Pareto diagram and Ishikawa diagram. The method used to measure the level of labor effectiveness is Overall Labor Effectiveness (OLE). OLE had three indicators which are availability, performance, and quality. Recommendations are made based on the results of the Pareto diagram and Ishikawa diagram for indicators that do not meet world standards. Based on the results of the study, the OLE value was 68.19%. Recommendations given to improve labor performance are adding mechanics, rescheduling rest periods, providing special training for labor, and giving rewards to labor. Furthermore, the recommendations for improving the quality of labor are procuring water content measuring devices, create material standard policies, and rescheduling rest periods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ishikawa%20diagram" title="Ishikawa diagram">Ishikawa diagram</a>, <a href="https://publications.waset.org/abstracts/search?q=labor%20effectiveness" title=" labor effectiveness"> labor effectiveness</a>, <a href="https://publications.waset.org/abstracts/search?q=OLE" title=" OLE"> OLE</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20diagram" title=" Pareto diagram"> Pareto diagram</a> </p> <a href="https://publications.waset.org/abstracts/141467/analysis-of-labor-effectiveness-at-green-tea-dry-sorting-workstation-for-increasing-tea-factory-competitiveness" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141467.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">228</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28039</span> A Hybrid Tabu Search Algorithm for the Multi-Objective Job Shop Scheduling Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aydin%20Teymourifar">Aydin Teymourifar</a>, <a href="https://publications.waset.org/abstracts/search?q=Gurkan%20Ozturk"> Gurkan Ozturk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a hybrid Tabu Search (TS) algorithm is suggested for the multi-objective job shop scheduling problems (MO-JSSPs). The algorithm integrates several shifting bottleneck based neighborhood structures with the Giffler & Thompson algorithm, which improve efficiency of the search. Diversification and intensification are provided with local and global left shift algorithms application and also new semi-active, active, and non-delay schedules creation. The suggested algorithm is tested in the MO-JSSPs benchmarks from the literature based on the Pareto optimality concept. Different performances criteria are used for the multi-objective algorithm evaluation. The proposed algorithm is able to find the Pareto solutions of the test problems in shorter time than other algorithm of the literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=tabu%20search" title="tabu search">tabu search</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristics" title=" heuristics"> heuristics</a>, <a href="https://publications.waset.org/abstracts/search?q=job%20shop%20scheduling" title=" job shop scheduling"> job shop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20optimality" title=" Pareto optimality"> Pareto optimality</a> </p> <a href="https://publications.waset.org/abstracts/71920/a-hybrid-tabu-search-algorithm-for-the-multi-objective-job-shop-scheduling-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71920.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">443</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=935">935</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=936">936</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Pareto%20chart%20analysis&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>