Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/522256
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dc.coverage.spatialCharacterization and experimental investigation of pack boronizing process off various stainless steel grades using anova and machine learning approacjes
dc.date.accessioned2023-11-01T09:19:17Z-
dc.date.available2023-11-01T09:19:17Z-
dc.identifier.urihttp://hdl.handle.net/10603/522256-
dc.description.abstractStainless steels are the ideal materials for cryogenic, elevated temperature and marine applications. This is mainly due to their excellent high-temperature strength, low-temperature toughness and corrosion resistance. Stainless steels are often utilized in the manufacture of industrial valve components and pumps exposed to corrosive fluids. The service life of these components are limited as they are subjected to relative motion with the parts leading to their poor wear resistance. Typically, the valve components often have metal-to-metal contact during their operation. To extend the useful service life of components, surface treatments are applied to combat wear. In the present study, five different grades of stainless steel such as martensitic stainless steel (SS410), austenitic stainless steel (Nitronic-50 and SS316) and super duplex stainless steel (S31803 and S32750) are used in valve components considered for surface modification. Among the various methods of surface treatment, the case hardening process plays a vital role to improve the hardness and wear resistance. Boronizing is one of the case hardening process (thermo chemical diffusion process) which offers an extremely high hardness and wear resistance as compared to the conventional heat treatment process. The pack boronizing technique is a cost-effective solution that can be applied even in intricate parts. In this work, pack boronizing process was carried out using 4.5 kW Indfurr electric furnace. To study the surface characteristics, the input process parameters such as temperature, time and gas pressure were considered with three different levels in each parameter. The Taguchi L9 orthogonal array was used to design the process parameters and to evaluate the impact of pack boronizing process. From the experimentation, diffusion kinetics, activation energy, boron layer thickness growth, surface hardness and wear resistance were analyzed. iv The various testing methods like metallographic, microscopic and mechanical examinations were carried out on t
dc.format.extentxxiv,208p.
dc.languageEnglish
dc.relationp.198-207
dc.rightsuniversity
dc.titleCharacterization and experimental investigation of pack boronizing process off various stainless steel grades using anova and machine learning approacjes
dc.title.alternative
dc.creator.researcherRamakrishnan, H
dc.subject.keywordAnova
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Mechanical
dc.subject.keywordMachine learning
dc.subject.keywordStainless steel
dc.description.note
dc.contributor.guideBalasundaram, R and Lenin, K
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Mechanical Engineering
dc.date.registered
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Mechanical Engineering

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01_title.pdfAttached File660.21 kBAdobe PDFView/Open
02_prelim pages.pdf3.64 MBAdobe PDFView/Open
03_content.pdf147.26 kBAdobe PDFView/Open
04_abstract.pdf222.17 kBAdobe PDFView/Open
05_chapter 1.pdf343.28 kBAdobe PDFView/Open
06_chapter 2.pdf454.18 kBAdobe PDFView/Open
07_chapter 3.pdf1.26 MBAdobe PDFView/Open
08_chapter 4.pdf2.4 MBAdobe PDFView/Open
09_chapter 5.pdf3.13 MBAdobe PDFView/Open
10_chapter 6.pdf2.99 MBAdobe PDFView/Open
11_chapter 7.pdf895.52 kBAdobe PDFView/Open
12_annexures.pdf193.34 kBAdobe PDFView/Open
80_recommendation.pdf1.3 MBAdobe PDFView/Open


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