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
Subjects:	T175 Industrial research. Research and development TJ Mechanical engineering and machinery
Online Access:	http://irep.iium.edu.my/4392/ http://irep.iium.edu.my/4392/1/Proc_NCMER2010_087.pdf

id	iium-4392
recordtype	eprints
spelling	iium-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 PeerReviewed 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.
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
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/ http://irep.iium.edu.my/4392/1/Proc_NCMER2010_087.pdf
first_indexed	2023-09-18T20:12:35Z
last_indexed	2023-09-18T20:12:35Z
_version_	1777407576619614208

Knowledge based expert system application for automative piston material selection

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