Surface Roughness of 17-4PH Products by Metal Fused Filament Fabrication

doi:10.12068/j.issn.1005-3026.2025.20240042

Abstract

Abstract:

Due to the layer-by-layer accumulation and the influence of the debinding/sintering process， the surface of products by metal fused filament fabrication（MFFF）has obvious defects. Optimization of processing parameters is one of the effective methods to improve the surface quality. Firstly， MFFF green/sintered samples were prepared based on the Box-Behnken design principle， and the surface roughness of different parts was experimentally determined. The individual and interaction effects of the processing parameters were then analyzed according to the response surface method， and a variance analysis was conducted on the experimental results to determine the significant factors. Finally， the statistical model and optimized combination of processing parameters were obtained by regression analysis and experimentally verified. The results show that the optimization of processing parameters can effectively improve the surface quality of MFFF products. Extrusion multiplier has the greatest effect on the surface roughness of the sample， and the printing speed has the least effect. Appropriately increasing the extrusion multiplier is helpful to improve the surface quality of green parts.

Key words: metal fused filament fabrication, processing parameter optimization, surface roughness, experimental validation

CLC Number:

TH 164

Shi-jie JIANG, Fei WANG, Shu-guang LI, Zi-zhao XU. Surface Roughness of 17-4PH Products by Metal Fused Filament Fabrication[J]. Journal of Northeastern University(Natural Science), 2025, 46(11): 82-89.

Figures/Tables 15

References 15

[1]	Léonard F， Tammas-Williams S. Metal FFF sintering shrinkage rate measurements by X-ray computed tomography［J］. Nondestructive Testing and Evaluation， 2022， 37（5）： 631-644.
[2]	Caminero M Á， Romero Gutiérrez A， Chacón J M， et al. Effects of fused filament fabrication parameters on the manufacturing of 316L stainless-steel components： geometric and mechanical properties［J］. Rapid Prototyping Journal， 2022， 28（10）： 2004-2026.
[3]	Galantucci L M， Pellegrini A， Guerra M G， et al. 3D printing of parts using metal extrusion： an overview of shaping debinding and sintering technology［J］. Advanced Technologies and Materials， 2022， 47（1）： 25-32.
[4]	Thompson Y， Gonzalez-Gutierrez J， Kukla C， et al. Fused filament fabrication， debinding and sintering as a low cost additive manufacturing method of 316L stainless steel［J］. Additive Manufacturing， 2019， 30： 100861.
[5]	Boschetto A， Bottini L， Miani F， et al. Roughness investigation of steel 316L parts fabricated by metal fused filament fabrication［J］. Journal of Manufacturing Processes， 2022， 81： 261-280.
[6]	Galati M， Minetola P. Analysis of density， roughness， and accuracy of the atomic diffusion additive manufacturing （ADAM） process for metal parts［J］. Materials， 2019， 12（24）： 4122.
[7]	Singh G， Missiaen J M， Bouvard D， et al. Additive manufacturing of 17-4 PH steel using metal injection molding feedstock： analysis of 3D extrusion printing， debinding and sintering［J］. Additive Manufacturing， 2021， 47： 102287.
[8]	Singh G， Missiaen J M， Bouvard D， et al. Copper extrusion 3D printing using metal injection moulding feedstock： analysis of process parameters for green density and surface roughness optimization［J］. Additive Manufacturing， 2021， 38： 101778.
[9]	Lavecchia F， Pellegrini A， Galantucci L M. Comparative study on the properties of 17-4 PH stainless steel parts made by metal fused filament fabrication process and atomic diffusion additive manufacturing［J］. Rapid Prototyping Journal， 2023， 29（2）： 393-407.
[10]	Singh P， Balla V K， Atre S V， et al. Factors affecting properties of Ti-6Al-4V alloy additive manufactured by metal fused filament fabrication［J］. Powder Technology， 2021， 386： 9-19.
[11]	Ferreira S L C， Bruns R E， Ferreira H S， et al. Box-Behnken design： an alternative for the optimization of analytical methods［J］. Analytica Chimica Acta， 2007， 597（2）： 179-186.
[12]	吴昂，吴莹，李国俊，等.基于响应曲面法的大型锥形件缩口成形工艺设计及多几何参数优化［J］.机械工程学报， 2019， 55（24）： 83-92.
	Wu Ang， Wu Ying， Li Guo-jun， et al. Process design and multi-geometric parameter optimization of large cones based on response surface methodology［J］. Journal of Mechanical Engineeringm， 2019， 55（24）： 83-92.
[13]	Supriadi S， Suharno B， Hidayatullah R， et al. Thermal debinding process of SS 17-4 PH in metal injection molding process with variation of heating rates， temperatures， and holding times［J］. Solid State Phenomena， 2017， 266： 238-244.
[14]	张烘州，明伟伟，安庆龙，等.响应曲面法在表面粗糙度预测模型及参数优化中的应用［J］.上海交通大学学报， 2010， 44（4）： 447-451.
	Zhang Hong-zhou， Ming Wei-wei， An Qing-long， et al. Application of response surface methodology in surface roughness prediction model and parameter optimization［J］. Journal of Shanghai Jiaotong University， 2010， 44（4）： 447-451.
[15]	胡雅琴.响应曲面二阶设计方法比较研究［D］.天津：天津大学， 2005.
	Hu Ya-qin. A comparative study on the second-order designs in response surface methodolody［D］. Tianjin： Tianjin University， 2005.

编码	因素
编码	熔融温度A/℃	成型速度B/(mm·s^-1)	挤出倍率C/%	层高D/mm
-1	230	15	100	0.10
0	240	20	110	0.15
1	250	25	120	0.20

编码	因素
编码	熔融温度A/℃	成型速度B/(mm·s^-1)	挤出倍率C/%	层高D/mm
-1	230	15	100	0.10
0	240	20	110	0.15
1	250	25	120	0.20

组别	因素				垂直纤维长度方向表面粗糙度 R_a1V/µm	平行纤维长度方向表面粗糙度 R_a1P/µm
组别	熔融温度A/℃	成型速度B/(mm·s^-1)	挤出倍率C/%	层高D/mm	垂直纤维长度方向表面粗糙度 R_a1V/µm	平行纤维长度方向表面粗糙度 R_a1P/µm
1	0	0	0	0	3.71	2.43
2	0	1	-1	0	12.42	6.34
3	0	1	0	-1	5.91	4.95
4	0	0	0	0	5.29	2.49
5	0	0	1	-1	2.09	1.54
6	0	1	1	0	1.71	1.32
7	1	1	0	0	3.92	1.75
8	-1	0	-1	0	10.07	3.84
9	-1	0	0	1	6.01	2.17
10	0	-1	0	1	8.57	1.56
11	-1	0	1	0	2.46	1.42
12	1	0	0	1	6.64	3.25
13	0	-1	-1	0	9.65	6.34
14	-1	0	0	-1	5.71	4.18
15	0	0	1	1	3.44	1.34
16	0	1	0	1	8.52	3.55
17	-1	1	0	0	4.56	2.69
18	-1	-1	0	0	5.88	3.70
19	0	-1	1	0	6.27	1.45
20	0	0	0	0	6.78	2.24
21	0	0	0	0	6.09	2.22
22	1	-1	0	0	7.95	1.48
23	0	0	-1	1	12.06	6.45
24	0	-1	0	-1	5.94	1.50
25	0	0	-1	-1	9.36	5.06
26	1	0	1	0	5.57	2.45
27	0	0	0	0	6.20	1.23
28	1	0	0	-1	6.05	1.53
29	1	0	-1	0	10.22	2.53

组别	因素				垂直纤维长度方向表面粗糙度 R_a1V/µm	平行纤维长度方向表面粗糙度 R_a1P/µm
组别	熔融温度A/℃	成型速度B/(mm·s^-1)	挤出倍率C/%	层高D/mm	垂直纤维长度方向表面粗糙度 R_a1V/µm	平行纤维长度方向表面粗糙度 R_a1P/µm
1	0	0	0	0	3.71	2.43
2	0	1	-1	0	12.42	6.34
3	0	1	0	-1	5.91	4.95
4	0	0	0	0	5.29	2.49
5	0	0	1	-1	2.09	1.54
6	0	1	1	0	1.71	1.32
7	1	1	0	0	3.92	1.75
8	-1	0	-1	0	10.07	3.84
9	-1	0	0	1	6.01	2.17
10	0	-1	0	1	8.57	1.56
11	-1	0	1	0	2.46	1.42
12	1	0	0	1	6.64	3.25
13	0	-1	-1	0	9.65	6.34
14	-1	0	0	-1	5.71	4.18
15	0	0	1	1	3.44	1.34
16	0	1	0	1	8.52	3.55
17	-1	1	0	0	4.56	2.69
18	-1	-1	0	0	5.88	3.70
19	0	-1	1	0	6.27	1.45
20	0	0	0	0	6.78	2.24
21	0	0	0	0	6.09	2.22
22	1	-1	0	0	7.95	1.48
23	0	0	-1	1	12.06	6.45
24	0	-1	0	-1	5.94	1.50
25	0	0	-1	-1	9.36	5.06
26	1	0	1	0	5.57	2.45
27	0	0	0	0	6.20	1.23
28	1	0	0	-1	6.05	1.53
29	1	0	-1	0	10.22	2.53

数据来源	平方和	自由度	均方	F值	p值
R²=0.91
模型R_a1V	193.93	14	13.85	10.61	<0.000 1
A-熔融温度	2.68	1	2.68	2.05	0.173 7
B-成型速度	4.34	1	4.34	3.32	0.089 8
C-挤出倍率	148.72	1	148.72	113.86	<0.000 1
D-层高	8.59	1	8.59	6.58	0.022 5
AB	1.83	1	1.83	1.40	0.256 3
AC	2.19	1	2.19	1.68	0.215 8
AD	0.02	1	0.02	0.02	0.902 5
BC	13.42	1	13.42	10.28	0.006 4
BD	0.000 1	1	0.000 1	0.000 1	0.993 5
CD	0.45	1	0.45	0.35	0.565 6
A²	0.12	1	0.12	0.09	0.767 4
B²	2.73	1	2.73	2.09	0.170 5
C²	8.59	1	8.59	6.58	0.022 5
D²	1.77	1	1.77	1.36	0.263 6
残差	18.29	14	1.31
失拟项	12.63	10	1.26	0.89	0.599 7
纯误差	5.66	4	1.41