Application of new robust design by means of probability-based multi-objective optimization to machining process parameters
Introduction/purpose: New robust design by means of probability-based multi-objective optimization takes the arithmetic mean value of the performance indicator and its deviation as twin independent responses of the performance indicator. The aim of this article is to check the applicability of n...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Defence in Belgrade
2023-01-01
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| Series: | Vojnotehnički Glasnik |
| Subjects: | |
| Online Access: | https://scindeks.ceon.rs/article.aspx?artid=0042-84692301084Z |
| _version_ | 1811171883664539648 |
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| author | Maosheng Zheng Haipeng Teng Yi Wang |
| author_facet | Maosheng Zheng Haipeng Teng Yi Wang |
| author_sort | Maosheng Zheng |
| collection | DOAJ |
| description | Introduction/purpose: New robust design by means of probability-based
multi-objective optimization takes the arithmetic mean value of the
performance indicator and its deviation as twin independent responses of
the performance indicator. The aim of this article is to check the
applicability of new robust design in optimizing machining process
parameters. To conduct the examination in detail, the robust design for
optimal cutting parameters to minimize energy consumption during the
turning of AISI 1018 steel at a constant material removal rate is applied as
well as the concurrent optimization of the machining process parameters
and the tolerance allocation of a spheroidal graphite cast iron piston.
Methods: In the spirit of the probability-based method for multi-objective
optimization, the arithmetic mean value of the performance indicator and
its deviation are taken as two independent responses of the performance
indicator to implement robust design. Each of the above twin responses
contributes one part of the partial preferable probabilities to the
performance indicator of the alternatives in the treatment. The arithmetic
mean value of the performance indicator should be assessed as a
representative of the performance indicator according to the function or
the preference of the performance indicator, and the deviation is the other index of the performance indicator, which has the characteristic of the
99
smaller-the-better in general. Furthermore, the square root of the product
of the above two parts of the partial preferable probability forms the actual
preferable probability of the performance indicator. Moreover, the product
of partial preferable probabilities gives the total preferable probability of
each alternative, which is the overall and unique index of each alternative
in the robust optimum.
Results: The paper gives the rational optimum cutting parameters for
minimizing energy consumption during the turning of AISI 1018 steel at a
constant material removal rate and the concurrent optimization of the
machining process parameters and the tolerance allocation of a
spheroidal graphite cast iron piston.
Conclusion: The application study indicates its rationality and convenience
of new robust optimization in the optimization of machining process
parameters. |
| first_indexed | 2024-04-10T17:21:36Z |
| format | Article |
| id | doaj.art-65ee59e84ed146209e13fcb426274436 |
| institution | Directory Open Access Journal |
| issn | 0042-8469 2217-4753 |
| language | English |
| last_indexed | 2024-04-10T17:21:36Z |
| publishDate | 2023-01-01 |
| publisher | University of Defence in Belgrade |
| record_format | Article |
| series | Vojnotehnički Glasnik |
| spelling | doaj.art-65ee59e84ed146209e13fcb4262744362023-02-05T11:23:53ZengUniversity of Defence in BelgradeVojnotehnički Glasnik0042-84692217-47532023-01-01711849910.5937/vojtehg71-39747Application of new robust design by means of probability-based multi-objective optimization to machining process parametersMaosheng Zheng0https://orcid.org/0000-0003-3361-4060Haipeng Teng1https://orcid.org/0000-0003-2987-7415Yi Wang2https://orcid.org/0000-0001-6711-0026Northwest University, School of Chemical Engineering, Xi’an, People's Republic of ChinaNorthwest University, School of Chemical Engineering, Xi’an, People's Republic of ChinaNorthwest University, School of Chemical Engineering, Xi’an, People's Republic of ChinaIntroduction/purpose: New robust design by means of probability-based multi-objective optimization takes the arithmetic mean value of the performance indicator and its deviation as twin independent responses of the performance indicator. The aim of this article is to check the applicability of new robust design in optimizing machining process parameters. To conduct the examination in detail, the robust design for optimal cutting parameters to minimize energy consumption during the turning of AISI 1018 steel at a constant material removal rate is applied as well as the concurrent optimization of the machining process parameters and the tolerance allocation of a spheroidal graphite cast iron piston. Methods: In the spirit of the probability-based method for multi-objective optimization, the arithmetic mean value of the performance indicator and its deviation are taken as two independent responses of the performance indicator to implement robust design. Each of the above twin responses contributes one part of the partial preferable probabilities to the performance indicator of the alternatives in the treatment. The arithmetic mean value of the performance indicator should be assessed as a representative of the performance indicator according to the function or the preference of the performance indicator, and the deviation is the other index of the performance indicator, which has the characteristic of the 99 smaller-the-better in general. Furthermore, the square root of the product of the above two parts of the partial preferable probability forms the actual preferable probability of the performance indicator. Moreover, the product of partial preferable probabilities gives the total preferable probability of each alternative, which is the overall and unique index of each alternative in the robust optimum. Results: The paper gives the rational optimum cutting parameters for minimizing energy consumption during the turning of AISI 1018 steel at a constant material removal rate and the concurrent optimization of the machining process parameters and the tolerance allocation of a spheroidal graphite cast iron piston. Conclusion: The application study indicates its rationality and convenience of new robust optimization in the optimization of machining process parameters.https://scindeks.ceon.rs/article.aspx?artid=0042-84692301084Zpreferable probabilityprobability-based methodmultiobjective optimizationrobust designsimultaneous optimization |
| spellingShingle | Maosheng Zheng Haipeng Teng Yi Wang Application of new robust design by means of probability-based multi-objective optimization to machining process parameters Vojnotehnički Glasnik preferable probability probability-based method multiobjective optimization robust design simultaneous optimization |
| title | Application of new robust design by means of probability-based multi-objective optimization to machining process parameters |
| title_full | Application of new robust design by means of probability-based multi-objective optimization to machining process parameters |
| title_fullStr | Application of new robust design by means of probability-based multi-objective optimization to machining process parameters |
| title_full_unstemmed | Application of new robust design by means of probability-based multi-objective optimization to machining process parameters |
| title_short | Application of new robust design by means of probability-based multi-objective optimization to machining process parameters |
| title_sort | application of new robust design by means of probability based multi objective optimization to machining process parameters |
| topic | preferable probability probability-based method multiobjective optimization robust design simultaneous optimization |
| url | https://scindeks.ceon.rs/article.aspx?artid=0042-84692301084Z |
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