Optimisation of metal microstructure using a population adaptive based immune algorithm

Gaffour, Sidahmed and Mahfouf, Mahdi and Chen, Jun (2010) Optimisation of metal microstructure using a population adaptive based immune algorithm. In: 18th Mediterranean Conference on Control and Automation, 23-25 June 2010, Congress Palace Hotel, Marrakech, Morocco.

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Official URL: http://dx.doi.org/10.1109/MED.2010.5547778

Abstract

A new optimal design method and a systematic scheduling approach for a laboratory-scale Hot-Rolling Mill are presented. The proposed design is based upon 1. metallurgical principles, which sufficiently consider the behaviour of workpiece material and the mechanics of the manufacturing process and 2. a modified version for multi-objective optimization of a Population Adaptive based Immune Algorithm (PAIA), physically-based models and symbiotic modelling approach to carry-out an optimal search for the best microstructural parameters. This methodology processes adequate capabilities for finding effective and best microstructural parameters such as the ferrite grain size and the volume fraction of pearlite that satisfy the requirements for mechanical properties. Hence, the overarching aim of this research work is to integrate knowledge about both the stock and the rolling process to find optimal hot-deformation profiles that will be used as information in order to compute the most suitable rolling schedule and systemise the optimal route for processing and achieve a ‘right-first-time’ production of the desired properties.

Item Type:Conference or Workshop Item (Paper)
Additional Information:A new optimal design method and a systematic scheduling approach for a laboratory-scale Hot-Rolling Mill are presented. The proposed design is based upon 1. metallurgical principles, which sufficiently consider the behaviour of workpiece material and the mechanics of the manufacturing process and 2. a modified version for multi-objective optimization of a Population Adaptive based Immune Algorithm (PAIA), physically-based models and symbiotic modelling approach to carry-out an optimal search for the best microstructural parameters. This methodology processes adequate capabilities for finding effective and best microstructural parameters such as the ferrite grain size and the volume fraction of pearlite that satisfy the requirements for mechanical properties. Hence, the overarching aim of this research work is to integrate knowledge about both the stock and the rolling process to find optimal hot-deformation profiles that will be used as information in order to compute the most suitable rolling schedule and systemise the optimal route for processing and achieve a ‘right-first-time’ production of the desired properties.
Keywords:optimisation, hybrid systems, biologically inspired systems
Subjects:H Engineering > H131 Automated Engineering Design
H Engineering > H650 Systems Engineering
H Engineering > H130 Computer-Aided Engineering
Divisions:College of Science > School of Engineering
ID Code:2873
Deposited By: Rosaline Smith
Deposited On:16 Jul 2010 09:18
Last Modified:17 Jul 2014 10:58

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