铝合金LF21微铣削顶端毛刺尺寸预测与工艺优化

doi:10.13229/j.cnki.jdxbgxb.20230228

Abstract

Abstract:

Aluminum alloy LF21 has low yield strength and is prone to plastic deformation， and is easy to produce burrs in micro-milling process. The size of the top burr is the largest， which has a great impact on the quality of the parts， and even causes the parts to be scrapped in severe cases. At present， the research on LF21 micro-milling burr has just started. Burr size is difficult to predict accurately， and the influence of processing parameters on burr size is still unknown. A prediction model of top burr size based on response surface method is established， and experiments are conducted to verify the validity of the prediction model. Based on response surface method， the interaction effect of cutting process parameters on top burr size is investigated. Finally， the optimization of process parameters is realized with the aim of minimizing the top burr size of micro-milling aluminum alloy LF21.

Key words: micro-milling, aluminum alloy LF21, top burr, prediction mode, parameters optimization

CLC Number:

TH161.5

Xiao-hong LU,Jia-qing LUO,Chen CONG,Kai XU. Prediction of top burr size and optimization of process parameters in micro-milling aluminum alloy LF21[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(1): 125-131.

Figures/Tables 11

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References 10

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序号	n /（r·min^-1）	a_p /μm	a_e /μm	f_z /（μm·z^-1）	l/μm
1	60 000	80	50	0.9	45.58
2	60 000	80	50	0.9	32.32
3	80 000	80	50	0.9	32.82
4	70 000	50	40	1.05	35.89
5	70 000	110	40	1.05	30.72
6	50 000	110	60	1.05	34.78
7	50 000	50	60	0.75	34.69
8	60 000	80	30	0.9	39.57
9	50 000	50	40	1.05	38.16
10	60 000	80	50	0.9	38.74
11	70 000	110	60	1.05	38.20
12	60 000	80	70	0.9	35.53
13	60 000	20	50	0.9	33.71
14	70 000	50	60	0.75	35.40
15	50 000	50	60	1.05	45.81
16	60 000	80	50	1.2	53.64
17	50 000	50	40	0.75	36.97
18	50 000	110	40	0.75	47.22
19	40 000	80	50	0.9	45.05
20	60 000	140	50	0.9	24.18
21	50 000	110	60	0.75	30.02
22	60 000	80	50	0.6	33.72
23	70 000	50	40	0.75	38.49
24	60 000	80	50	0.9	32.55
25	70 000	110	60	0.75	37.09
26	50 000	110	40	1.05	44.14
27	70 000	110	40	0.75	49.62
28	60 000	80	50	0.9	35.43
29	60 000	80	50	0.9	30.95
30	70 000	50	60	1.05	56.04

方差来源	平方和	自由度	均方	F值	P值	显著性
模型	1 169.86	19	61.57	14.35	< 0.000 1	***
A-n	36.04	1	36.04	8.40	0.015 9	**
B-a_p	17.02	1	17.02	3.97	0.074 4	*
C-a_e	32.62	1	32.62	7.60	0.020 2	**
D-f_z	69.87	1	69.87	16.28	0.002 4	***
AB	4.55	1	4.55	1.06	0.327 2	*
AC	30.64	1	30.64	7.14	0.023 4	**
AD	7.29	1	7.29	1.70	0.221 5	*
BC	28.24	1	28.24	6.58	0.028 1	**
BD	19.14	1	19.14	4.46	0.060 8	*
CD	30.36	1	30.36	7.07	0.023 9	**
A2	51.85	1	51.85	12.08	0.006 0	***
B2	667.54	1	667.54	155.58	< 0.000 1	***
C2	58.15	1	58.15	13.55	0.004 2	***
D2	127.00	1	127.00	29.60	0.000 3	***
ACD	25.89	1	25.89	6.03	0.033 9	**
A2B	70.31	1	70.31	16.39	0.002 3	***
A2C	56.75	1	56.75	13.23	0.004 6	***
A2D	22.80	1	22.80	5.31	0.043 9	**
AB2	50.66	1	50.66	11.81	0.006 4	***
失拟度	27.029	5	5.41	1.70	0.286 7	*
纯误差	15.88	5	3.18

序号	n/（r·min^-1）	a_p/μm	a_e/μm	f_z /（μm·z^-1）	试验测量/μm	预测结果/μm	相对误差/%
1	50 000	50	70	1.0	35.6	33.48	5.9%
2	60 000	80	50	1.2	42.89	44.64	4.0%
3	70 000	110	30	0.8	35.92	33.43	6.9%

Prediction of top burr size and optimization of process parameters in micro-milling aluminum alloy LF21

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