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Genetic algorithms solution to the single-objective machining process optimization time model
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Title: Genetic algorithms solution to the single-objective machining process optimization time model

Creator:

Patrick Ejebheare Amiolemhen ; Joshua Ahurome Eseigbe

Date:

2019

Type:

artykuł w czasopiśmie

Description:

Minimum Production Time model of the machining process optimization problem comprising seven lathe machining operations were developed using Genetic Algorithms solution method. The various cost and time components involved in the minimum production cost and minimum production time criteria respectively, as well as all relevant technological/practical constraints were determined. An interactive, user-friendly computer package was then developed in Microsoft Visual Basic.Net environment to implement the developed models. The package was used to determine optimal machining parameters of cutting speed, feed rate and depth of cut for the seven machining operations with twenty-three technological constraints in the conversion of a cylindrical metal bar stock into a finished machined profile. The result of the single-objective machining process optimization models shows that the minimum production time is 21.84 min.

Place of publishing:

Koszalin

Publisher:

Publishing House of the Koszalin University of Technology

Format:

application/pdf

Identifier:

oai:dlibra.tu.koszalin.pl:1518

Language:

eng

Is part of:

Journal of Mechanical and Energy Engineering. Vol.3 (43), nr 1, s. 13-24

Rights:

Biblioteka Politechniki Koszalińskiej

Access rights:

internet

License:

Creative Commons BY 4.0

Exlibris

Subject and keywords:

production time optimization machining model genetic algorhithms development

Object collections:

Last modified:

Nov 6, 2023

In our library since:

Jun 22, 2022

Number of object content hits:

45

All available object's versions:

https://dlibra.tu.koszalin.pl/publication/1522

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Edition name Date
Patrick Ejebheare Amiolemhen, 2019, Genetic algorithms solution to the single-objective machining process optimization time model Nov 6, 2023

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