Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/13055
Title: Prediction of remaining useful life of used components of systems for reuse
Researcher: Gokulachandran, J
Guide(s): Mohandas, K
Keywords: Mechanical Engineering
Environmental Protection
Green manufacturing
reuse issues
diagnostics
prognostics
Taguchi approach
Upload Date: 20-Nov-2013
University: Amrita Vishwa Vidyapeetham (University)
Completed Date: 2013
Abstract: In general, waste materials from industries are disposed of in landfills which can contaminate the environment. These waste materials consists of manufacturing scrap, avoidable waste generated due to the wrong processes chosen and the premature disposal of cutting tools and other worn-out parts. Green manufacturing is a method of manufacturing that minimises waste and pollution. These goals are often achieved through product and process design adhering to three primary strategies of Reduce, Reuse and Recycle for effectively managing materials and waste which it urn helps conserve natural resources and energy. Reusing and recycling can be thought of as two alternatives that could be tried at to reduce the environmental pollution created by the above mentioned practices.In general, materials thrown out from industries are seen to have much life potential remaining in them unused. Cutting tools, for example, are quite often discarded without using its full potential. Such discarded cutting tools are found to have some remaining useful life left. Considering these aspects, here, an attempt is being made to assess the reuse potential of used materials. Predicting remaining useful life is a step to identify the reuse potential. This aspect of the use of the tool has not been discussed sufficiently by researchers. The main objective of this research is to develop a comprehensive methodology to assess the reuse potential of carbide tipped tools. Here, experiments are conducted based on Taguchi approach and tool life values are obtained. The experimental values are used to develop the regression model, artificial neural network model, fuzzy model, neuro fuzzy model and support vector regression model for predicting tool life. The remaining useful life is determined using predicted tool life and consumed life of the tool. The remaining useful life obtained from these values is compared to ascertain the efficacy of the aforesaid models.
Pagination: xii, 119p.
URI: http://hdl.handle.net/10603/13055
Appears in Departments:Amrita School of Engineering

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01_title.pdfAttached File71.66 kBAdobe PDFView/Open
02_declaration.pdf58.95 kBAdobe PDFView/Open
03_acknowledgements.pdf59.21 kBAdobe PDFView/Open
04_certificate.pdf90.95 kBAdobe PDFView/Open
05_abstract.pdf87.88 kBAdobe PDFView/Open
06_dedication.pdf21.6 kBAdobe PDFView/Open
07_list of abbravations.pdf82.19 kBAdobe PDFView/Open
08_list of figure.pdf77.93 kBAdobe PDFView/Open
09_list of tables.pdf57.16 kBAdobe PDFView/Open
10_list of symbols.pdf76.41 kBAdobe PDFView/Open
11_list of publication.pdf2.7 MBAdobe PDFView/Open
12_contents.pdf96.05 kBAdobe PDFView/Open
13_chapter 1.pdf189.71 kBAdobe PDFView/Open
14_chapter 2.pdf236.67 kBAdobe PDFView/Open
15_chapter 3.pdf73.68 kBAdobe PDFView/Open
16_chapter 4.pdf248.86 kBAdobe PDFView/Open
17_chapter 5.pdf354.45 kBAdobe PDFView/Open
18_chapter 6.pdf452.2 kBAdobe PDFView/Open
19_chapter 7.pdf64.89 kBAdobe PDFView/Open
20_details.pdf97.17 kBAdobe PDFView/Open
21_references.pdf461.4 kBAdobe PDFView/Open
22_synopsis.pdf571.3 kBAdobe PDFView/Open


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