Knowledge based expert system application for automative piston material selection

Knowledge based systems (also known as computer-based expert systems) can be constructed by obtaining knowledge from a human expert and transforming it into a form that a computer may use to solve engineering problems. The aim of this paper is to select the optimum material for the operation of auto...

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Main Authors: Maleque, Md. Abdul, Arifutzzaman, A. K. H. A. Ma, Rahman, Md. Mustafizur
Format: Conference or Workshop Item
Language:English
Published: 2010
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Online Access:http://irep.iium.edu.my/4392/1/Proc_NCMER2010_087.pdf
http://irep.iium.edu.my/4392/
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spelling my.iium.irep.43922011-10-27T06:13:06Z http://irep.iium.edu.my/4392/ Knowledge based expert system application for automative piston material selection Maleque, Md. Abdul Arifutzzaman, A. K. H. A. Ma Rahman, Md. Mustafizur T175 Industrial research. Research and development TJ Mechanical engineering and machinery Knowledge based systems (also known as computer-based expert systems) can be constructed by obtaining knowledge from a human expert and transforming it into a form that a computer may use to solve engineering problems. The aim of this paper is to select the optimum material for the operation of automotive piston emphasizing on the substitution of this cast iron by lightweight material using the knowledge-based systems (KBS). The system is capable of selecting the most suitable material and ranks the materials with respect to their properties. Seven candidate material are proposed for the automotive piston application, such as cast iron, titanium alloy, aluminum alloy, ceramics and three different composite materials such as 20% SiC reinforced Alcomposite (AMC1), 20% SiC reinforced Al-Cu alloy (AMC2) , 7.5 wt% WC and 7.5 wt% TiC reinforced Ti-composite (TMC). Mechanical properties including, friction coefficient, wear rate, thermal conductivity and specific gravity as well as the relative cost were used as the key parameters in the material selection stage. Scale properties and unit cost of material are used for calculating the performance index and figure of merit respectively for ranking and optimum material selection using knowledge based expert system. 2010-11 Conference or Workshop Item REM application/pdf en http://irep.iium.edu.my/4392/1/Proc_NCMER2010_087.pdf Maleque, Md. Abdul and Arifutzzaman, A. K. H. A. Ma and Rahman, Md. Mustafizur (2010) Knowledge based expert system application for automative piston material selection. In: National Conference in Mechanical Engineering Research and Postgraduate Studies (2nd NCMER 2010), 3 - 4 December 2010, Pekan, Pahang.
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic T175 Industrial research. Research and development
TJ Mechanical engineering and machinery
spellingShingle T175 Industrial research. Research and development
TJ Mechanical engineering and machinery
Maleque, Md. Abdul
Arifutzzaman, A. K. H. A. Ma
Rahman, Md. Mustafizur
Knowledge based expert system application for automative piston material selection
description Knowledge based systems (also known as computer-based expert systems) can be constructed by obtaining knowledge from a human expert and transforming it into a form that a computer may use to solve engineering problems. The aim of this paper is to select the optimum material for the operation of automotive piston emphasizing on the substitution of this cast iron by lightweight material using the knowledge-based systems (KBS). The system is capable of selecting the most suitable material and ranks the materials with respect to their properties. Seven candidate material are proposed for the automotive piston application, such as cast iron, titanium alloy, aluminum alloy, ceramics and three different composite materials such as 20% SiC reinforced Alcomposite (AMC1), 20% SiC reinforced Al-Cu alloy (AMC2) , 7.5 wt% WC and 7.5 wt% TiC reinforced Ti-composite (TMC). Mechanical properties including, friction coefficient, wear rate, thermal conductivity and specific gravity as well as the relative cost were used as the key parameters in the material selection stage. Scale properties and unit cost of material are used for calculating the performance index and figure of merit respectively for ranking and optimum material selection using knowledge based expert system.
format Conference or Workshop Item
author Maleque, Md. Abdul
Arifutzzaman, A. K. H. A. Ma
Rahman, Md. Mustafizur
author_facet Maleque, Md. Abdul
Arifutzzaman, A. K. H. A. Ma
Rahman, Md. Mustafizur
author_sort Maleque, Md. Abdul
title Knowledge based expert system application for automative piston material selection
title_short Knowledge based expert system application for automative piston material selection
title_full Knowledge based expert system application for automative piston material selection
title_fullStr Knowledge based expert system application for automative piston material selection
title_full_unstemmed Knowledge based expert system application for automative piston material selection
title_sort knowledge based expert system application for automative piston material selection
publishDate 2010
url http://irep.iium.edu.my/4392/1/Proc_NCMER2010_087.pdf
http://irep.iium.edu.my/4392/
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score 13.211869