Temat: multi-objective - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Tuning of a Fuzzy System for Controlling Searching Process In Multi Objective Scheduling Immune Algorithm
Autorzy:: Wosik, I.
Skołud, B.
Powiązania:: https://bibliotekanauki.pl/articles/971215.pdf
Data publikacji:: 2009
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: Immune Algorithm
multi objective optimization
fuzzy system
Opis:: In the paper the Multi Objective Immune Algorithm (MOIA) for an open job shop scheduling problem (OJSP) is proposed. The OJSP belongs to most both time consuming and most complicated problems in scope of searching space. In the paper schedules are evaluated by using three criteria: makespan, flowtime and total tardiness. MOIA proposes a schedule, which is best one, selected from a set of achieved solutions. An affinity threshold is a parameter that controls equilibrium between searching space and solutions diversity in MOIA. The affinity threshold is defined by using fuzzy logic system. In the paper fuzzy system is tuned by selecting shape, size of fuzzy sets, and fuzzy decisions of an affinity threshold. If the fuzzy system is used then neither the knowledge about the affinity threshold nor influence over searching processes is not required from a decision-maker. The application of the fuzzy system makes the process of decision-making user friendly. In the paper efficiency of MOIA before and after the fuzzy system tuning is compared and computational results are presented.
Źródło:: Journal of Machine Engineering; 2009, 9, 1; 130-143
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Design optimization of compliant mechanisms for vibration assisted machining applications using a hybrid Six Sigma, RSM-FEM, and NSGA-II approach
Autorzy:: Pham, Huy-Tuan
Nguyen, Van-Khien
Dang, Quang-Khoa
Duong, Thi Van Anh
Nguyen, Duc-Thong
Phan, Thanh-Vu
Powiązania:: https://bibliotekanauki.pl/articles/24084644.pdf
Data publikacji:: 2023
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: compliant mechanism
multi-objective optimisation
Six Sigma
NSGA-II
Opis:: Vibration-assisted machining, a hybrid processing method, has been gaining considerable interest recently due to its advantages, such as increasing material removal rate, enhancing surface quality, reducing cutting forces and tool wear, improving tool life, or minimizing burr formation. Special equipment must be designed to integrate the additional vibration energy into the traditional system to exploit those spectacular characteristics. This paper proposes the design of a new 2-DOF high-precision compliant positioning mechanism using an optimization process combining the response surface method, finite element method, and Six Sigma analysis into a multi-objective genetic algorithm. The TOPSIS method is also used to select the best solution from the Pareto solution set. The optimum design was fabricated to assess its performance in a vibration-assisted milling experiment concerning surface roughness criteria. The results demonstrate significant enhancement in both the manufacturing criteria of surface quality and the design approach criteria since it eliminates modelling errors associated with analytical approaches during the synthesis and analysis of compliant mechanisms.
Źródło:: Journal of Machine Engineering; 2023, 23, 2; 135--158
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: A hybridization of machine learning and NSGA-II for multi-objective optimization of surface roughness and cutting force in AISI 4340 alloy steel turning
Autorzy:: Nguyen, Anh-Tu
Nguyen, Van-Hai
Le, Tien-Thinh
Nguyen, Nhu-Tung
Powiązania:: https://bibliotekanauki.pl/articles/2200263.pdf
Data publikacji:: 2023
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: multi-objective optimisation
machine learning
AISI 4340
NSGA-II
ANN
Opis:: This work focuses on optimizing process parameters in turning AISI 4340 alloy steel. A hybridization of Machine Learning (ML) algorithms and a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is applied to find the Pareto solution. The objective functions are a simultaneous minimum of average surface roughness (Ra) and cutting force under the cutting parameter constraints of cutting speed, feed rate, depth of cut, and tool nose radius in a range of 50–375 m/min, 0.02–0.25 mm/rev, 0.1–1.5 mm, and 0.4–0.8 mm, respectively. The present study uses five ML models – namely SVR, CAT, RFR, GBR, and ANN – to predict Ra and cutting force. Results indicate that ANN offers the best predictive performance in respect of all accuracy metrics: root-mean-squared-error (RMSE), mean-absolute-error (MAE), and coefficient of determination (R2). In addition, a hybridization of NSGA-II and ANN is implemented to find the optimal solutions for machining parameters, which lie on the Pareto front. The results of this multi-objective optimization indicate that Ra lies in a range between 1.032 and 1.048 μm, and cutting force was found to range between 7.981 and 8.277 kgf for the five selected Pareto solutions. In the set of non-dominated keys, none of the individual solutions is superior to any of the others, so it is the manufacturer's decision which dataset to select. Results summarize the value range in the Pareto solutions generated by NSGA-II: cutting speeds between 72.92 and 75.11 m/min, a feed rate of 0.02 mm/rev, a depth of cut between 0.62 and 0.79 mm, and a tool nose radius of 0.4 mm, are recommended. Following that, experimental validations were finally conducted to verify the optimization procedure.
Źródło:: Journal of Machine Engineering; 2023, 23, 1; 133--153
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Modelling of surface roughness and tool wear when finish milling process of the circular bevel gear
Autorzy:: Pham, Van Dong
Hoang, Xuan Thinh
Powiązania:: https://bibliotekanauki.pl/articles/2200262.pdf
Data publikacji:: 2023
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: circular bevel gear
surface roughness model
tool wear model
multi-objective optimisation
Opis:: An experimental process to build the models of surface roughness and tool wear in the finish milling of the Gleason circular bevel gears was carried out in this study. The experiments were conducted according to a Box-Behnken matrix. Three cutting parameters were adjusted in each experiment including cutting speed, feed rate, and depth of cut. From the experimental results, the influences of cutting parameters on the surface roughness and tool wear were analysed in detail. Two models of surface roughness and tool wear were established with high accuracy. The optimal values of the cutting parameters were also determined to simultaneously ensure the minimum values of two output parameters. The further research directions were also suggested at the end of this study.
Źródło:: Journal of Machine Engineering; 2023, 23, 1; 154--169
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Multi-objective optimization for weld track geometry in wire-arc directed energy deposition of ER308L stainless steel
Autorzy:: Nguyen, Van Canh
Le, Van Thao
Pham, Ngoc-Linh
Nguyen, Anh-Thang
Powiązania:: https://bibliotekanauki.pl/articles/24084674.pdf
Data publikacji:: 2023
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: wire-arc directed energy deposition
weld track
ER308L stainless steel
multi-objective optimisation
Opis:: In this research, the weld track geometry in wire-arc DED (directed energy deposition) of ER308L stainless steel was predicted and optimized. The studied geometrical attributes of weld tracks include weld track width (WTW), weld track height (WTH), and contact angle (α). The experiment was designed based on Taguchi method with three variables (current I, voltage U, and weld velocity v) and four levels for each variable. The ANOVA was adopted to evaluate the accuracy of the models and impact levels of variables on the responses. The TOPSIS method was utilized to predict the optimal variables. The results indicated that the predicted models were built with high accuracy levels (R2 = 98.92%, 98.77%, and 98.91% for WTW, WTH, and α, respectively). Among the studied variables, U features the highest effects on WTW and α with 78.56% and 69.90% of contribution, respectively, while v is the variable that has the most impact on WTH with 39.82% of contribution. The optimal variables predicted by TOPSIS were U = 23 V, I = 140 A, and v = 300 mm/min, which allows building components with stable and regular geometry.
Źródło:: Journal of Machine Engineering; 2023, 23, 2; 123--134
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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