Multiple Targets Technology Optimization Based Grey Relative Analysis of 18Ni300 Die Steel Formed by Selective Laser Melting

Table 1. Chemical composition of 18Ni300 die steel powder
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Table 1. Chemical composition of 18Ni300 die steel powder
Element C S P Si Mn Al Ti Mo Co Ni Fe
Mass fraction /% 0.03 0.01 0.01 0.1 0.1 0.15 0.8 5.20 9.50 18 Bal.

Table 2. Levels of experiment parameters

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Table 2. Levels of experiment parameters

Parameter	Symbol	Level of parameter
Parameter	Symbol	Level 1	Level 2	Level 3	Level 4	Level 5
Laser power /W	A	150	200	250	300	350
Scanning speed /(mm·s^-1)	B	650	700	750	800	850
Hatching distance /mm	C	0.05	0.08	0.11	0.14	0.17
Powder coating thickness /mm	D	0.02	0.03	0.04	0.05	0.06

Table 3. Data of forming samples

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Table 3. Data of forming samples

No.	Forming parameter				Response value
No.	A /W	B /(mm·s^-1)	C /mm	D /mm	Relativedensity (RD) /%	Hardness(HD) /HRC	Wear resistance(WR) /μm³
1	300	800	0.08	0.03	99.8	27.6	430780
2	350	750	0.11	0.04	99.9	35.5	1226820
3	250	750	0.11	0.04	98.2	39.7	883720
4	300	700	0.14	0.05	97.5	43.4	533680
5	200	700	0.14	0.05	93.8	33.5	450080
6	250	750	0.11	0.04	99.2	39.1	1081940
7	200	700	0.08	0.05	96.6	40.1	513880
8	300	700	0.08	0.05	99.4	42.9	1454260
9	200	800	0.14	0.05	96.0	33.6	1825140
10	150	750	0.11	0.04	93.2	38.3	845880
11	300	800	0.08	0.05	99.6	36.5	648780
12	200	700	0.08	0.03	98.5	40.9	1901920
13	250	750	0.11	0.02	99.9	36.1	915040
14	250	650	0.11	0.04	99.4	36.5	998560
15	250	750	0.05	0.04	98.7	37.3	831540
16	300	700	0.14	0.03	99.6	39.3	156060
17	300	800	0.14	0.05	95.7	39.2	816140
18	200	800	0.08	0.03	99.9	40.9	917560
19	300	700	0.08	0.03	99.7	39.0	860520
20	250	750	0.11	0.06	99.8	40.7	818740
21	300	800	0.14	0.03	96.1	38.1	600280
22	200	800	0.08	0.05	94.0	38.2	621960
23	200	700	0.14	0.03	97.9	39.7	1461940
24	200	800	0.14	0.03	92.2	37.1	1505180
25	250	750	0.11	0.04	95.8	40.6	651760
26	250	750	0.11	0.04	94.9	41.1	604780
27	250	850	0.11	0.04	95.1	40.6	415180
28	250	750	0.11	0.04	98.8	37.3	765940
29	250	750	0.11	0.04	98.8	39.0	724240
30	250	750	0.17	0.04	92.0	40.7	290960

Table 4. Principal component analysis results

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Table 4. Principal component analysis results

Parameter	Principalcomponent 1	Principalcomponent 2	Principalcomponent 3	Eigenvalue	Contribution /%
Relative density	-0.681	0.072	-0.728	1.1910	39.7
Hardness	0.417	0.856	-0.305	0.9758	32.5
Wear resistance	0.601	-0.512	-0.613	0.8332	27.8

Table 5. Result ofexperimental data processing

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Table 5. Result ofexperimental data processing

No.	Normalization			GRC			GRG
No.	RD		HD	WR	RD	HD	WR
1	0.0126582	1	0.1573551	0.9753086	0.3333333	0.7606239	0.7070
2	0	0.5	0.6133138	1	0.5	0.4491097	0.6844
3	0.2151898	0.2341772	0.4167918	0.6991150	0.6810345	0.5453801	0.6505
4	0.3037974	0	0.2162945	0.6220472	1	0.6980369	0.7660
5	0.7721518	0.6265822	0.1684098	0.3930348	0.4438202	0.7480440	0.5082
6	0.0886075	0.2721518	0.5303289	0.8494624	0.6475410	0.4852819	0.6826
7	0.4177215	0.2088607	0.2049534	0.5448276	0.7053571	0.7092667	0.6427
8	0.0632911	0.031645	0.7435877	0.8876405	0.9404762	0.4020625	0.7698
9	0.4936708	0.6202531	0.9560217	0.5031847	0.4463277	0.3434015	0.4403
10	0.8481012	0.3227848	0.3951176	0.3708920	0.6076923	0.5585858	0.5000
11	0.0379746	0.4367088	0.2822219	0.9294118	0.5337838	0.6392048	0.7202
12	0.1772151	0.1582278	1	0.7383178	0.7596154	0.3333333	0.6327
13	0	0.4620253	0.4347313	1	0.5197368	0.5349131	0.7146
14	0.0632911	0.4367089	0.4825702	0.8876404	0.5337838	0.5088695	0.6673
15	0.1518987	0.3860759	0.3869039	0.7669903	0.5642857	0.5637590	0.6446
16	0.0379746	0.2594937	0	0.9294118	0.6583333	1	0.8609
17	0.53164557	0.2658228	0.3780830	0.4846626	0.6528926	0.5694222	0.5629
18	0	0.1582278	0.4361747	1	0.7596154	0.5340883	0.7924
19	0.0253164	0.2784810	0.4035031	0.9518072	0.6422764	0.5534015	0.7405
20	0.0126582	0.1708861	0.3795722	0.9753086	0.7452830	0.5684581	0.7874
21	0.4810126	0.3354430	0.2544419	0.5096774	0.5984848	0.6627415	0.5811
22	0.746835443	0.329113924	0.266859886	0.4010152	0.6030534	0.6520096	0.5365
23	0.253164557	0.234177215	0.747986666	0.6638655	0.6810345	0.4006453	0.5963
24	0.974683544	0.398734177	0.772753829	0.3390558	0.5563380	0.3928489	0.4246
25	0.518987342	0.17721519	0.283928837	0.4906832	0.7383178	0.6378130	0.6121
26	0.632911392	0.14556962	0.257019463	0.4413408	0.7745098	0.660485	0.6105
27	0.607594937	0.17721519	0.14841969	0.4514286	0.7383178	0.7711055	0.6335
28	0.139240506	0.386075949	0.34932927	0.7821782	0.5642857	0.5886998	0.6576
29	0.139240506	0.278481013	0.325444194	0.7821782	0.6422764	0.6057345	0.6877
30	1	0.170886076	0.07726851	0.3333333	0.7452830	0.8661481	0.6153

Table 6. Variance analysis of prediction model
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Table 6. Variance analysis of prediction model
Source Degree of freedom Sum of square Mean square F P
Prediction model 14 0.240364 0.017169 3.91 0.006
Error 15 0.065823 0.004388
Total 29 0.306187
Standard deviation R²=78.50%

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Xiayu Chen, Weidong Huang, Weijie Zhang, Zhangpeng Lai, Guofu Lian. Multiple Targets Technology Optimization Based Grey Relative Analysis of 18Ni300 Die Steel Formed by Selective Laser Melting[J]. Chinese Journal of Lasers, 2020, 47(5): 0502003

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