Prediction of Recycle Method using Relevance Vector Machine

Life cycle engineering is the engineering and design of products and processes to minimize the cost and environmental impact for the life cycle phases of a product. Relevance Vector Machine method (RVM) is used to determine recycling strategy (reuse, service, remanufacture, recycle with disassembly,...

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Main Authors: M. M., Noor, M. M., Rahman, K., Kadirgama, M. A., Maleque
Format: Article
Language:en
Published: 2011
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/2221/1/Prediction_of_Recycle_Method_using_Relevance_Vector_Machine.pdf
http://umpir.ump.edu.my/id/eprint/2221/
http://www.scientific.net/AMR.264-265.943
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author M. M., Noor
M. M., Rahman
K., Kadirgama
M. A., Maleque
author_facet M. M., Noor
M. M., Rahman
K., Kadirgama
M. A., Maleque
author_sort M. M., Noor
building UMPSA Library
collection Institutional Repository
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
continent Asia
country Malaysia
description Life cycle engineering is the engineering and design of products and processes to minimize the cost and environmental impact for the life cycle phases of a product. Relevance Vector Machine method (RVM) is used to determine recycling strategy (reuse, service, remanufacture, recycle with disassembly, recycle without disassembly and disposal). Seven parameters (wear – out life, technology cycle, level of integration, number of parts, reason for redesign and design cycle) were considered as the input for the RVM model. Three electronic equipments were selected to be examined such as vacuum cleaner, washing machine, television. All the results verify previous literature study. The prediction model predicts the end of life (EOL) strategies quite closely with real industry practices.
format Article
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institution Universiti Malaysia Pahang
language en
publishDate 2011
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spelling my.ump.umpir.22212018-01-25T06:47:38Z http://umpir.ump.edu.my/id/eprint/2221/ Prediction of Recycle Method using Relevance Vector Machine M. M., Noor M. M., Rahman K., Kadirgama M. A., Maleque TJ Mechanical engineering and machinery Life cycle engineering is the engineering and design of products and processes to minimize the cost and environmental impact for the life cycle phases of a product. Relevance Vector Machine method (RVM) is used to determine recycling strategy (reuse, service, remanufacture, recycle with disassembly, recycle without disassembly and disposal). Seven parameters (wear – out life, technology cycle, level of integration, number of parts, reason for redesign and design cycle) were considered as the input for the RVM model. Three electronic equipments were selected to be examined such as vacuum cleaner, washing machine, television. All the results verify previous literature study. The prediction model predicts the end of life (EOL) strategies quite closely with real industry practices. 2011 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2221/1/Prediction_of_Recycle_Method_using_Relevance_Vector_Machine.pdf M. M., Noor and M. M., Rahman and K., Kadirgama and M. A., Maleque (2011) Prediction of Recycle Method using Relevance Vector Machine. Advanced Materials Research, 264-26. pp. 1557-1562. ISSN 1022-6680. (Published) http://www.scientific.net/AMR.264-265.943
spellingShingle TJ Mechanical engineering and machinery
M. M., Noor
M. M., Rahman
K., Kadirgama
M. A., Maleque
Prediction of Recycle Method using Relevance Vector Machine
title Prediction of Recycle Method using Relevance Vector Machine
title_full Prediction of Recycle Method using Relevance Vector Machine
title_fullStr Prediction of Recycle Method using Relevance Vector Machine
title_full_unstemmed Prediction of Recycle Method using Relevance Vector Machine
title_short Prediction of Recycle Method using Relevance Vector Machine
title_sort prediction of recycle method using relevance vector machine
topic TJ Mechanical engineering and machinery
url http://umpir.ump.edu.my/id/eprint/2221/1/Prediction_of_Recycle_Method_using_Relevance_Vector_Machine.pdf
http://umpir.ump.edu.my/id/eprint/2221/
http://www.scientific.net/AMR.264-265.943
url_provider http://umpir.ump.edu.my/