Izvorni znanstveni članak

https://doi.org/10.17559/TV-20180715085107

Optimization Parameters of Milling Process of Mould Material for Decreasing Machining Power and Surface Roughness Criteria

Trung-Thanh Nguyen orcid.org/0000-0002-0838-872X ; (1) Institute of Research and Development, Duy Tan University, 03 Quang Trung, Da Nang 550000, Viet Nam / (2) Faculty of Mechanical Engineering, Le Quy Don Technical University, Hanoi 100000, Viet Nam
Quoc-Hoang Pham ; Advanced Technology Center, Le Quy Don Technical University, Hanoi 100000, Viet Nam
Xuan-Phuong Dang ; Faculty of Mechanical Engineering, Nha Trang University, Nguyen Đinh Chieu, Nha Trang 57000, Viet Nam
Tat-Khoa Doan ; Faculty of Mechanical Engineering, Le Quy Don Technical University, Hanoi 100000, Viet Nam
Xuan-Hung Le ; Faculty of Mechanical Engineering, Le Quy Don Technical University, Hanoi 100000, Viet Nam

Sažetak

Improving milling performances is an effective solution to decrease the costs required. This paper addressed a multi-response optimization to simultaneously decrease the machining power consumed Pm, arithmetical roughness Ra, and ten-spot roughness Rz. The Grey-Response Surface Method-Multi Island Genetic Algorithm (GRMA) consisting of grey relational analysis (GRA), response surface method (RSM), and multi-island genetic algorithm (MA) was proposed to predict the optimal parameters and yield optimum milling performances. The experimental trials were conducted with the support of a CNC milling center. The influences of spindle speed (S), depth of cut (ap), feed rate (fz), and tip radius (r) were explored using GRA. The nonlinear relationship between machining parameters and grey grade (GG) model was developed using RSM. Finally, two optimization techniques, including desirability approach (DA) and MA were performed to observe the optimal values. The results indicated that the machining power was greatly affected by processing factors and the radius has a significant impact on the roughness criteria. The measured reductions using optimal parameters of Pm, Ra, and Rz are approximately 77.05%, 50.00%, and 58.02%, respectively, as compared to initial settings. The GRMA can be considered as an effective approach to generate reliable values of processing conditions and technological performances in the milling process.

Ključne riječi

cutting parameters; Grey Relational Analysis (GRA); milling; Multi-Island Genetic Algorithm (MA); optimization; Response Surface Method (RSM)

Hrčak ID:

226012

URI

https://hrcak.srce.hr/226012

Datum izdavanja:

8.10.2019.

Posjeta: 1.349 *