Maintenance simulation of a chemical plant in Cameroon

dc.authorid0009-0007-3075-8209
dc.authorid0009-0007-3075-8209en_US
dc.contributor.advisorJavadi, Sonyaen_US
dc.contributor.authorDibe, Sheilla Njien_US
dc.contributor.otherIşık Üniversitesi, Lisansüstü Eğitim Enstitüsü, Endüstri Mühendisliği - Yöneylem Araştırması Yüksek Lisans Programıen_US
dc.date.accessioned2023-12-13T14:06:47Z
dc.date.available2023-12-13T14:06:47Z
dc.date.issued2023-11-22
dc.departmentIşık Üniversitesi, Lisansüstü Eğitim Enstitüsü, Endüstri Mühendisliği - Yöneylem Araştırması Yüksek Lisans Programıen_US
dc.descriptionText in English ; Abstract: English and Turkishen_US
dc.descriptionIncludes bibliographical references (leaves 50-53)en_US
dc.descriptionix, 60 leavesen_US
dc.description.abstractIn the field of manufacturing, remarkable strides have been made in the development of predictive maintenance strategies. The research has incorporated cutting-edge technological innovations, such as machine learning, artificial intelligence, and the Internet of Things (IoT). Manufacturers can now proactively identify and address equipment malfunctions. This research study employs a degradation model simulation to evaluate and predict the remaining lifespan of a rotating element bearing in the manufacturing assembly line of a chemical plant situated in Cameroon. Additionally, the objective of this study is to perform a comparative analysis that seeks to assess the impact of implementing preventive and predictive maintenance strategies on the overall operational efficiency of a manufacturing system characterized by a seriesparallel configuration. The study reveals that the predictive maintenance policy is more significant in manufacturing system where addressing system throughput or implementation cost. This highlights the enhanced efficiency and cost-effectiveness associated with predictive maintenance in manufacturing operations.en_US
dc.description.abstractÜretim alanında, kestirimci bakım stratejilerinin geliştirilmesinde dikkate değer ilerlemeler kaydedilmiştir. Araştırma, makine öğrenimi, yapay zeka ve Nesnelerin İnterneti (IoT) gibi en ileri teknolojik yenilikleri içeriyor. Üreticiler artık ekipman arızalarını proaktif olarak tespit edip giderebiliyor. Bu araştırma çalışması, Kamerun'da bulunan bir kimya fabrikasının imalat montaj hattındaki döner elemanlı rulmanın kalan ömrünü değerlendirmek ve tahmin etmek için bir bozulma modeli simülasyonu kullanmaktadır. Ek olarak bu çalışmanın amacı, önleyici ve kestirimci bakım stratejilerinin uygulanmasının, seri-paralel konfigürasyonla karakterize edilen bir üretim sisteminin genel operasyonel verimliliği üzerindeki etkisini değerlendirmeyi amaçlayan karşılaştırmalı bir analiz gerçekleştirmektir. Çalışma, sistem verimi veya uygulama maliyetinin ele alındığı üretim sisteminde kestirimci bakım politikasının daha önemli olduğunu ortaya koyuyor. Bu, üretim operasyonlarında kestirimci bakımla ilişkili gelişmiş verimliliği ve maliyet etkinliğini vurgulamaktadır.en_US
dc.description.tableofcontentsMaintenance Managementen_US
dc.description.tableofcontentsPreventive Maintenanceen_US
dc.description.tableofcontentsDegradation Modellingen_US
dc.description.tableofcontentsResearch Objectiveen_US
dc.description.tableofcontentsHOLFARCAM Companyen_US
dc.description.tableofcontentsReview on Maintenanceen_US
dc.description.tableofcontentsSimulation Analysisen_US
dc.description.tableofcontentsCondition-based Maintenanceen_US
dc.description.tableofcontentsNeural Networksen_US
dc.description.tableofcontentsMarkov Processesen_US
dc.description.tableofcontentsDetermination of the RUL of the Rotating Element Bearingen_US
dc.description.tableofcontentsExperimental procedureen_US
dc.description.tableofcontentsExpression of resultsen_US
dc.description.tableofcontentsEstimation of the RULen_US
dc.description.tableofcontentsVibrational Profile of a Rotating Element Bearingen_US
dc.description.tableofcontentsEstimating Remaining Useful Lifeen_US
dc.description.tableofcontentsDescription of the Production Processen_US
dc.description.tableofcontentsSimulation and analysis of Maintenance Policies series-parallel workstationen_US
dc.description.tableofcontentsManufacturing Systemen_US
dc.description.tableofcontentsSystem Reliabilityen_US
dc.description.tableofcontentsThe Simulation Modelen_US
dc.description.tableofcontentsManufacturing System Sub modelen_US
dc.description.tableofcontentsMeans and Standard deviations, pertaining to the frequency replacements for failure observed within different levels of reliabilityen_US
dc.description.tableofcontentsMeans and Standard deviations, pertaining to the frequency replacements for failure observed within different levels of reliability(more)en_US
dc.description.tableofcontentsMeans and Standard deviations, pertaining to the frequency replacements for planned failure observed within different levels of reliabilityen_US
dc.description.tableofcontentsMean and Standard deviations explaining the total maintenance cost at different percentages of reliabilitiesen_US
dc.description.tableofcontentsMean and Standard deviations the different policy production throughput and their reliability percentagesen_US
dc.description.tableofcontentsReactive Maintenance Illustrationen_US
dc.description.tableofcontentsIllustration of Preventive Maintenanceen_US
dc.description.tableofcontentsPredictive Maintenance Illustrationen_US
dc.description.tableofcontentsLinear Degradation Simulationen_US
dc.description.tableofcontentsExponential Degradation Modelen_US
dc.description.tableofcontentsRotating Element Bearingen_US
dc.description.tableofcontentsRotating Element Bearing Vibrational Signalen_US
dc.description.tableofcontentsRemaining Useful Life for Rotating Element Bearingen_US
dc.description.tableofcontentsProduction Process for Solution Concentrateen_US
dc.description.tableofcontentsHOLFARCAM Sarl Manufacturing Systemen_US
dc.description.tableofcontentsIllustration of Series-Parallel Configurationen_US
dc.description.tableofcontentsFailure Routine Sub modelen_US
dc.description.tableofcontentsSystem Maintenance Sub modelen_US
dc.description.tableofcontentsFrequency replacement for Failureen_US
dc.description.tableofcontentsFrequency Replacement for Planned Failuresen_US
dc.description.tableofcontentsTotal Maintenance Costen_US
dc.description.tableofcontentsWorkstation utilisationen_US
dc.description.tableofcontentsSystem throughputen_US
dc.identifier.citationDibe, S. N. (2023). Maintenance simulation of a chemical plant in Cameroon. İstanbul: Işık Üniversitesi Lisansüstü Eğitim Enstitüsü.en_US
dc.identifier.urihttps://hdl.handle.net/11729/5813
dc.institutionauthorDibe, Sheilla Njien_US
dc.language.isoenen_US
dc.publisherIşık Üniversitesien_US
dc.relation.publicationcategoryTezen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectPredictive maintenanceen_US
dc.subjectDegradation modelen_US
dc.subjectRemaining useful lifeen_US
dc.subjectSimulationen_US
dc.subjectKestirimci bakımen_US
dc.subjectBozunma modelien_US
dc.subjectKalan faydalı ömüren_US
dc.subjectSimülasyonen_US
dc.subject.lccTS192 .D53 2023
dc.subject.lcshPlant maintenance -- Cameroon.en_US
dc.subject.lcshChemical plant -- Maintenance and repair -- Cameroon.en_US
dc.subject.lcshChemical plants -- Equipment and supplies -- Deterioration.en_US
dc.subject.lcshChemical plants -- Remodeling.en_US
dc.titleMaintenance simulation of a chemical plant in Cameroonen_US
dc.title.alternativeKamerun'daki bir pestisit üretim tesisi için öngörüsü bakım simülasyonuen_US
dc.typeMaster Thesisen_US
dspace.entity.typePublication

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