Optimizing end milling parameters for custom 450 stainless steel using ant lion optimization and TOPSIS analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F24%3A10254334" target="_blank" >RIV/61989100:27230/24:10254334 - isvavai.cz</a>
Result on the web
<a href="https://www.webofscience.com/wos/woscc/full-record/WOS:001157172200001" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:001157172200001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3389/fmech.2024.1353544" target="_blank" >10.3389/fmech.2024.1353544</a>
Alternative languages
Result language
angličtina
Original language name
Optimizing end milling parameters for custom 450 stainless steel using ant lion optimization and TOPSIS analysis
Original language description
The current research examines the effectiveness of cryogenically treated (CT) tungsten carbide cutting inserts on Custom450 stainless steel using multi-objective soft computing approaches. The Taguchi-based L27 orthogonal array was employed in the experiments. During milling operations, cutting force, surface roughness, and cutting temperature were measured at different spindle speeds (rpm), feed rates (mm/min), and constant depths of cut (mm). The surface roughness and chip morphology of the Custom 450 stainless steel machined by cryo-treated (CT) and untreated (UT) cutting tool inserts were compared across various responses to cutting temperature and force. This paper also carried out multi-objective optimization, employing algorithm techniques such as Grasshopper Optimization Algorithm (GHO), Grey Wolf Optimization(GWO), Harmony Search Algorithm(HAS), and Ant line Optimization (ALO). The Multi-objective Taguchi approach and TOPSIS were first used to optimize the machining process parameters (spindle speed, feed rate, and cryogenic treatment) with different performance characteristics. Second, to relate the machining process parameters with the performance characteristics (cutting force, cutting temperature, and surface roughness), a mathematical model was developed using response surface analysis. The created mathematical response model was validated using ANOVA. The results showed that in IGD values of GHO, GWO, HSA and ALO module had 2.5765, 2.4706, 2.3647 and 2.5882 respectively, ALO has the best performance indicator. A Friedman's test was also conducted, revealing higher resolution with the ALO method than with the HSA, GWO, and GHO methods. The results of the scanning test show that the ALO approach is workable.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20300 - Mechanical engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Frontiers in Mechanical Engineering - Switzerland
ISSN
2297-3079
e-ISSN
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Volume of the periodical
10
Issue of the periodical within the volume
JAN 25 2024
Country of publishing house
CH - SWITZERLAND
Number of pages
17
Pages from-to
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UT code for WoS article
001157172200001
EID of the result in the Scopus database
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