激光定向能量沉积NiCo-FGMs的磨削工艺优化

doi:10.12068/j.issn.1005-3026.2025.20230241

摘要/Abstract

摘要：

为解决激光定向能量沉积（laser-directed energy deposition， L-DED）成型工艺制备的镍钴基功能梯度材料（NiCo-FGMs）磨削后表面质量一致性较差这一问题，基于正交试验分析了磨削工艺参数对NiCo-FGMs的磨削力和表面粗糙度的影响规律，并建立相应的预测模型.针对粗加工与精加工的不同加工目标，利用第二代非支配排序遗传算法（NSGA-Ⅱ）结合熵权法与逼近理想解的排序方法即熵权TOPSIS（technique for order proference by similarity to ideal solution）法进行了多目标磨削工艺参数优化，并进行验证.结果表明：粗加工磨削参数采用a_p = 53.61 μm，v_s = 29.99 m/s，v_w = 311.89 mm/min；精加工磨削参数采用a_p = 14.96 μm，v_s = 29.99 m/s，v_w = 300.92 mm/min.经两道工序加工，表面粗糙度标准差从0.195 μm降至0.101 μm，有效提高NiCo-FGMs的表面粗糙度一致性.

关键词: 镍钴基功能梯度材料（NiCo-FGMs）, 激光定向能量沉积（L-DED）, 磨削力, 表面粗糙度

Abstract:

In order to solve the problem of poor surface quality consistency after the grinding of nickel-cobalt-based functional gradient materials （NiCo-FGMs） prepared by laser-directed energy deposition （L-DED） and forming process， the influence laws of the grinding process parameters on the grinding force and surface roughness of NiCo-FGMs were analyzed based on the orthogonal experiments， and the corresponding prediction model was established. For the different processing objectives of rough machining and finish machining， the multi-objective grinding process parameter optimization was carried out and verified by using the second-generation non-dominated sorting genetic algorithm （NSGA-Ⅱ） and the entropy weight technique for order preference by similarity to ideal solution （TOPSIS） method. The results showed that the rough machining parameters are used a_p = 53.61 μm， v_s = 29.99 m/s， v_w = 311.89 mm/min， and the finish machining parameters are used a_p = 14.96 μm， v_s = 29.99 m/s， v_w = 300.92 mm/min. After the two-stage machining， the standard deviation of surface roughness is reduced from 0.195 μm to 0.101 μm， which effectively improves the surface roughness consistency of NiCo-FGMs.

Key words: nickel-cobalt-based functional gradient materials （NiCo-FGMs）, laser-directed energy deposition （L-DED）, grinding force, surface roughness

中图分类号:

TH 161

辛博, 曹刚, 秦嘉鑫, 赵显力. 激光定向能量沉积NiCo-FGMs的磨削工艺优化[J]. 东北大学学报（自然科学版）, 2025, 46(2): 85-95.

Bo XIN, Gang CAO, Jia-xin QIN, Xian-li ZHAO. Grinding Process Optimization of Laser-Directed Energy Deposited NiCo-FGMs[J]. Journal of Northeastern University(Natural Science), 2025, 46(2): 85-95.

图/表 22

参考文献 8

1	Tyagi S A， Manjaiah M. Laser additive manufacturing of titanium-based functionally graded materials： a review［J］. Journal of Materials Engineering and Performance， 2022， 31（8）： 6131-6148.
2	Zhang R Y， Nagaraja K M， Bian N， et al. Experimental studies on fabricating functionally gradient material of stainless steel 316L-Inconel 718 through hybrid manufacturing： directed energy deposition and machining［J］. The International Journal of Advanced Manufacturing Technology， 2022， 120（11）： 7815-7826.
3	Su Y， Chen B， Tan C W， et al. Influence of composition gradient variation on the microstructure and mechanical properties of 316 L/Inconel 718 functionally graded material fabricated by laser additive manufacturing［J］. Journal of Materials Processing Technology， 2020， 283： 116702.
4	Zhao K， Zhang G H， Ma G Y， et al. Microstructure and mechanical properties of titanium alloy/zirconia functionally graded materials prepared by laser additive manufacturing［J］. Journal of Manufacturing Processes， 2020， 56： 616-622.
5	Sim J， Choi D C， Shin K H， et al. Characterization of microscale drilling process for functionally graded M2-Cu material using design of experiments［J］. Journal of the Korean Society of Manufacturing Technology Engineers， 2015， 24（5）： 502-507.
6	Oyelola O， Crawforth P， M’Saoubi R， et al. Machining of functionally graded Ti₆Al₄V/WC produced by directed energy deposition［J］. Additive Manufacturing， 2018， 24： 20-29.
7	Wang C D， Ge Y， Ma J P， et al. Effects of parameter selection strategy on tool wear when milling 3D-printed functionally graded materials with textured tool under minimum quantity lubrication［J］. The International Journal of Advanced Manufacturing Technology， 2023， 125（3）： 1615-1632.
8	Noh I， Jeon J， Lee S W. A study on metallographic and machining characteristics of functionally graded material produced by directed energy deposition［J］. Crystals， 2023， 13（10）： 1491.

材料	C	Si	Mn	Cr	Mo	Ti	Fe	Al	Co	Ni	W	Ta	Hf
K447A	0.14	0.03	0.01	8.69	0.72	1.16	0.12	5.58	10.33	Bal.	10.31	3.11	1.58
Stellite-6	1.15	1.10	0.50	29.00	1.00	—	3.00	—	Bal.	3.00	4.00	—	—

材料	C	Si	Mn	Cr	Mo	Ti	Fe	Al	Co	Ni	W	Ta	Hf
K447A	0.14	0.03	0.01	8.69	0.72	1.16	0.12	5.58	10.33	Bal.	10.31	3.11	1.58
Stellite-6	1.15	1.10	0.50	29.00	1.00	—	3.00	—	Bal.	3.00	4.00	—	—

变量	数值
激光功率/W	1 600
送粉速率/(g·min^-1)	15
激光扫描速度/(mm·min^-1)	600
搭接率/ %	40
送粉/保护气体	N₂
基板预热温度，时间	300 ℃，10 min

变量	数值
激光功率/W	1 600
送粉速率/(g·min^-1)	15
激光扫描速度/(mm·min^-1)	600
搭接率/ %	40
送粉/保护气体	N₂
基板预热温度，时间	300 ℃，10 min

序号	0% K447A		25% K447A		50% K447A		75% K447A		100% K447A
序号	F_n	F_t	F_n	F_t	F_n	F_t	F_n	F_t	F_n	F_t
1	11.99	4.59	15.05	8.69	10.12	5.75	11.12	5.99	23.37	12.65
2	17.27	6.56	20.27	11.25	11.87	6.29	16.25	9.29	28.78	15.12
3	14.21	6.46	19.30	10.59	14.96	7.82	18.43	9.63	20.34	8.46
4	7.96	4.23	16.63	8.06	13.78	6.78	17.80	8.77	17.16	7.33
5	14.00	5.60	39.51	23.75	23.86	13.53	31.22	16.39	66.46	31.55
6	33.57	12.86	33.41	19.12	19.01	10.37	28.05	15.98	44.33	21.39
7	39.60	16.59	45.32	24.14	31.15	15.70	45.71	23.22	60.79	24.60
8	34.59	11.74	36.18	17.49	30.61	15.40	37.57	18.21	56.95	23.86
9	83.87	36.24	65.22	38.67	39.56	22.35	54.78	29.15	111.60	50.81
10	37.79	14.75	57.70	30.67	40.84	21.29	53.94	25.83	66.84	27.45
11	48.25	20.82	40.30	21.90	28.98	15.22	43.17	23.79	88.03	37.27
12	62.60	23.83	53.58	25.58	41.72	21.28	58.75	27.38	89.41	34.74
13	96.26	41.87	88.00	51.26	67.95	37.15	73.17	39.61	145.20	63.06
14	59.92	24.46	75.86	40.76	57.34	29.60	69.44	35.44	110.56	43.23
15	72.37	30.43	55.15	29.66	39.34	19.79	57.13	30.64	112.42	43.83
16	72.50	28.17	58.48	28.21	44.33	23.28	67.05	31.23	104.82	40.91