Multi-Objective Optimization of Manufacturing Process Using Artificial Neural Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F24%3A43926323" target="_blank" >RIV/62156489:43410/24:43926323 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.3390/systems12120569" target="_blank" >https://doi.org/10.3390/systems12120569</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/systems12120569" target="_blank" >10.3390/systems12120569</a>

Result language

angličtina

Original language name

Multi-Objective Optimization of Manufacturing Process Using Artificial Neural Networks

Original language description

This paper focuses on the optimization of a critical operation in the furniture manufacturing process, identifying it as a key priority for improvement by applying Systems Theory. The primary objective of this study is to develop a mathematical model for optimizing the detected key process by employing artificial neural networks (ANNs) which mirror adaptive management principles. Three input and three output parameters significantly impacting the effectiveness of this key process have been systematically identified and experimentally measured. It was necessary to perform multi-objective optimization (MOO), which consisted in achieving the minimum values of cost and process time and the maximum value of the quality index through the optimal setting of the input parameters (cutting speed, feed rate, and volume of removed material). The application of ANNs in MOO in this research study is a novelty in this field. The results obtained through application of the ANN method reveal the optimal values of the examined parameters, which represent the best combination of input technical variables leading to the best results in output economic parameters. This multi-objective optimizing solution facilitates enhanced process efficiency. By integrating Systems Theory, Complexity Theory, and adaptive management, this research advances sustainable process improvements by minimizing resource use, reducing waste, and enhancing overall system efficiency.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

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

Name of the periodical

Systems

ISSN

2079-8954

e-ISSN

2079-8954

Volume of the periodical

12

Issue of the periodical within the volume

12

Country of publishing house

CH - SWITZERLAND

Number of pages

25

Pages from-to

569

UT code for WoS article

001386939100001

EID of the result in the Scopus database

2-s2.0-85213472237