COMPARISON OF CHOSEN METAHEURISTIC ALGORITHMS FOR THE OPTIMIZATION OF THE ABRASIVE WATER JET TREATMENT PROCESS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F24%3A10256515" target="_blank" >RIV/61989100:27230/24:10256515 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mmscience.eu/journal/issues/november-2024/articles/comparison-of-chosen-metaheuristic-algorithms-for-the-optimization-of-the-abrasive-water-jet-treatment-process" target="_blank" >https://www.mmscience.eu/journal/issues/november-2024/articles/comparison-of-chosen-metaheuristic-algorithms-for-the-optimization-of-the-abrasive-water-jet-treatment-process</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17973/MMSJ.2024_11_2024098" target="_blank" >10.17973/MMSJ.2024_11_2024098</a>

Jazyk výsledku

angličtina

Název v původním jazyce

COMPARISON OF CHOSEN METAHEURISTIC ALGORITHMS FOR THE OPTIMIZATION OF THE ABRASIVE WATER JET TREATMENT PROCESS

Popis výsledku v původním jazyce

Abrasive waterjet machining (AWJ) is characterized by significantly better efficiency and better precision for difficult-to-machine materials than conventional machining technologies. However, the larger number of control parameters characterizing this process needs optimization. The study compares the performance of three nature-inspired metaheuristic algorithms, ALO, GWO, and MFO for optimizing the abrasive water jet (AWJ) treatment. The Response Surface Methodology was used to determine the cost function. The study evaluates the convergence and computational cost of the algorithms to aid future developments in this field. The study aims to maximize the cutting thickness by predicting the optimal water-abrasive cutting parameters (nozzle diameter, abrasive concentration, feed speed). For all three algorithms, the maximum cutting depth was determined to be 87.47 mm, which differs only less than 3% from the actual value. The results highlight the potential of ant-lion optimization (ALO), grey wolf optimizer (GWO), and (MFO) moth-flame optimization algorithms for resolving optimization issues in AWJ machining.

Název v anglickém jazyce

COMPARISON OF CHOSEN METAHEURISTIC ALGORITHMS FOR THE OPTIMIZATION OF THE ABRASIVE WATER JET TREATMENT PROCESS

Popis výsledku anglicky

Abrasive waterjet machining (AWJ) is characterized by significantly better efficiency and better precision for difficult-to-machine materials than conventional machining technologies. However, the larger number of control parameters characterizing this process needs optimization. The study compares the performance of three nature-inspired metaheuristic algorithms, ALO, GWO, and MFO for optimizing the abrasive water jet (AWJ) treatment. The Response Surface Methodology was used to determine the cost function. The study evaluates the convergence and computational cost of the algorithms to aid future developments in this field. The study aims to maximize the cutting thickness by predicting the optimal water-abrasive cutting parameters (nozzle diameter, abrasive concentration, feed speed). For all three algorithms, the maximum cutting depth was determined to be 87.47 mm, which differs only less than 3% from the actual value. The results highlight the potential of ant-lion optimization (ALO), grey wolf optimizer (GWO), and (MFO) moth-flame optimization algorithms for resolving optimization issues in AWJ machining.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20301 - Mechanical engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MM Science Journal

ISSN

1803-1269

e-ISSN

1805-0476

Svazek periodika

2024

Číslo periodika v rámci svazku

November 2024

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

9

Strana od-do

7678-7686

Kód UT WoS článku

001350510400001

EID výsledku v databázi Scopus

—