The Dynamic Comprehensive Evaluation of the Importance of Cutting Parameters in the Side Milling TC4 Process Using an Integrated End Mill DOI Open Access

Xingfu Zhao,

Yanzhong Wang,

Lin Jin

и другие.

Materials, Год журнала: 2024, Номер 17(11), С. 2744 - 2744

Опубликована: Июнь 4, 2024

In the cutting process, there are many parameters that affect effect, and same parameter has different degrees of influence on performance indicators, which makes it difficult to select key for optimization combination evaluation while considering multiple indicators at time. The process titanium alloy milling with an integrated end mill is studied herein. values tool flank face wear material removal rates obtained experimental analytical methods. Numerical characteristics causes stages also analyzed. dynamic, comprehensive method based double incentives model used evaluate importance in view problem dynamic change process. According result a evaluation, highest selected. Finally, radar map plot parameters. overall each intuitively displayed as well. As research, good application value can quickly best combination; established most speed, width second important. turn, depth lowest.

Язык: Английский

Hybrid quantum particle swarm optimization and variable neighborhood search for flexible job-shop scheduling problem DOI

Yuanxing Xu,

Mengjian Zhang,

Ming Yang

и другие.

Journal of Manufacturing Systems, Год журнала: 2024, Номер 73, С. 334 - 348

Опубликована: Фев. 26, 2024

Язык: Английский

Процитировано

27

Productivity prediction of a spherical distiller using a machine learning model and triangulation topology aggregation optimizer DOI
Mohamed Abd Elaziz, Fadl A. Essa, Hassan A. Khalil

и другие.

Desalination, Год журнала: 2024, Номер 585, С. 117744 - 117744

Опубликована: Май 18, 2024

Язык: Английский

Процитировано

23

Review of Machine Learning applications in Additive Manufacturing DOI Creative Commons

Sirajudeen Inayathullah,

Raviteja Buddala

Results in Engineering, Год журнала: 2024, Номер 25, С. 103676 - 103676

Опубликована: Дек. 8, 2024

Язык: Английский

Процитировано

18

Artificial neural networks based computational and experimental evaluation of thermal and drying performance of partially covered PVT solar dryer DOI
Ankur Gupta, Biplab Das, Erhan Arslan

и другие.

Process Safety and Environmental Protection, Год журнала: 2024, Номер 183, С. 1170 - 1185

Опубликована: Янв. 23, 2024

Язык: Английский

Процитировано

14

Enhancing performance of multi-pressure evaporation organic Rankine Cycle/Supercritical Carbon Dioxide Brayton cycle through genetic algorithm and Machine learning optimization DOI
Huaitao Zhu, Gongnan Xie, Abdallah S. Berrouk

и другие.

Energy Conversion and Management, Год журнала: 2024, Номер 301, С. 118037 - 118037

Опубликована: Янв. 4, 2024

Язык: Английский

Процитировано

12

A review on the grinding of SiC-based ceramic matrix composites reinforced by continuous fibre: Damage mechanisms and evaluations DOI
Qihao Xu, Shenglei Xiao, Yiqi Wang

и другие.

Journal of Manufacturing Processes, Год журнала: 2024, Номер 132, С. 261 - 295

Опубликована: Ноя. 5, 2024

Язык: Английский

Процитировано

11

Experimental investigation and machine learning modeling using LSTM and special relativity search of friction stir processed AA2024/Al2O3 nanocomposites DOI Creative Commons
Fathi Djouider, Mohamed Abd Elaziz, Abdulsalam M. Alhawsawi

и другие.

Journal of Materials Research and Technology, Год журнала: 2023, Номер 27, С. 7442 - 7456

Опубликована: Ноя. 1, 2023

In this study, the friction stir technique is proposed to process aluminum nanocomposites reinforced with alumina nanoparticles. The effects of different processing parameters, including spindle speed (900–1800 rpm), feed (10–20 mm/min), and number passes (1–3) on mechanical dynamic properties processed samples were investigated. investigated ultimate tensile strength, yield natural frequency, damping ratio. An advanced machine learning approach composed a long short-term memory model optimized by special relativity search algorithm was developed predict conditions. adequacy tested compared three other models; predicted in good agreement measured properties. outperformed models found be powerful prediction tool for predicting conditions obtain high-quality nanocomposite samples. succeeded ratio R2 0.912, 0.952, 0.951, 0.987, respectively. obtained results showed that samples' loss factor increase passes, while shear modulus, complex modulus decrease passes. Thus, can used improve materials.

Язык: Английский

Процитировано

18

A gazelle optimization expedition for key term separated fractional nonlinear systems with application to electrically stimulated muscle modeling DOI
Taimoor Ali Khan, Naveed Ishtiaq Chaudhary, Chung-Chian Hsu

и другие.

Chaos Solitons & Fractals, Год журнала: 2024, Номер 185, С. 115111 - 115111

Опубликована: Июнь 15, 2024

Язык: Английский

Процитировано

7

Influence of Fibre Orientation on the Slotting Quality of CFRP Composites Using the Multi-Tooth Mill DOI Open Access
Ying Zhai, Shuwei Lv, Defeng Yan

и другие.

Materials, Год журнала: 2024, Номер 17(10), С. 2441 - 2441

Опубликована: Май 18, 2024

Carbon fibre-reinforced plastic (CFRP) composites, prized for their exceptional properties, often encounter surface quality issues during slotting due to inherent heterogeneity. This paper tackles CFRP challenges by employing multi-tooth mills in experiments with various fibre orientations and tool feed rates. In-plane scratching tests are performed under linearly varying loads; then, conducted at different parameters. The test results indicate that the orientation cutting angles have significant influences on forces fracture process. demonstrate roughness

Язык: Английский

Процитировано

5

Leveraging AI for energy-efficient manufacturing systems: Review and future prospectives DOI Creative Commons
Mohamed Abadi, Chao Liu, Mingyu Zhang

и другие.

Journal of Manufacturing Systems, Год журнала: 2024, Номер 78, С. 153 - 177

Опубликована: Ноя. 29, 2024

Язык: Английский

Процитировано

5