Optimization of Process Parameters and Performance Analysis of Laser Directed Energy Deposition Considering Specific Energy Consumption， Energy Utilization Rate， and Height-to-width Ratio

doi:10.3969/j.issn.1004-132X.2026.10.009

Abstract

Abstract:

The preparation of TC4 titanium alloy via LDED was investigated. Taking laser power， scanning speed， and powder feed rate as the primary process parameters， an L₁₆（4³） orthogonal experimental design was employed to systematically investigate the influence of these process parameters on energy utilization rate， specific energy consumption， and the height-to-width ratio of the deposited layer. Through range analysis and variance analysis， the significance of the influence of each parameter on the energy efficiency and morphology indicators was clarified， and the optimized combination of process parameters was determined （laser power： 800 W， scanning speed： 600 mm/min， powder feed rate： 6 g/min）. Experimental verification showed that， compared with the average values of the orthogonal test groups， the specific energy consumption and the deviation of the height-to-width ratio were improved by 21.8% and 69.5%， respectively， under the optimized parameters， while the energy utilization rate increased by 22.4%. Microstructural analysis showed that the deposited layer primarily consists of fine acicular α'-Ti martensite， with an average grain size smaller than that of the rolled substrate. Mechanical property tests indicated that the as-deposited TC4 exhibited increases in hardness， yield strength， and tensile strength of 25.63%， 9.94%， and 9.60%， respectively， compared to the rolled substrate， although the elongation slightly decreased. The fracture surface exhibited ductile-brittle mixed fracture characteristics.

Key words: additive manufacturing, laser directed energy deposition（LDED）, specific energy consumption, process optimization, mechanical properties

摘要：

针对激光定向能量沉积制备TC4钛合金，以激光功率、扫描速度和粉末进给速度为主要工艺参数，采用L₁₆（4³）正交试验设计，系统研究了各工艺参数对能量利用率、比能耗及沉积层高宽比的影响规律。通过极差分析与方差分析，明确了各参数对能效与形貌指标的影响显著性，并确定了优化的工艺参数组合（激光功率800 W，扫描速度600 mm/min，粉末进给速度6 g/min）。试验验证表明，相较于正交试验组的平均值，该优化参数下比能耗与高宽比偏差分别改善了21.8%与69.5%，且能量利用率提高了22.4%；微观组织分析显示，沉积层主要由细小的针状α'-Ti马氏体组成，其平均晶粒尺寸小于轧制态基板；力学性能测试表明，沉积态TC4硬度、屈服强度与抗拉强度相较于轧制基板提高25.63%、9.94%和9.60%，但延伸率略有下降，断口呈韧-脆混合断裂特征。

关键词: 增材制造, 激光定向能量沉积, 比能耗, 工艺优化, 力学性能

CLC Number:

TG665

FEI Fan, WU Jianzhao, ZHONG Liuyang, ZHANG Chaoyong, LIU Wenhui, LIU Xiao. Optimization of Process Parameters and Performance Analysis of Laser Directed Energy Deposition Considering Specific Energy Consumption， Energy Utilization Rate， and Height-to-width Ratio[J]. China Mechanical Engineering, 2026, 37(10): 2466-2475.

费凡, 吴剑钊, 仲刘洋, 张超勇, 刘文辉, 刘筱. 考虑比能耗、能量利用率和高宽比的激光定向能量沉积工艺参数优化及性能分析[J]. 中国机械工程, 2026, 37(10): 2466-2475.

Figures/Tables 20

References 23

[1]	SEO G， AHSAN M R， LEE Y， et al. A Functional Modeling Approach for Quality Assurance in Metal Additive Manufacturing［J］. Rapid Prototyping Journal， 2021， 27（2）： 288-303.
[2]	SU Y， WANG C， XU X， et al. Pore Defects and Corrosion Behavior of AISI 316L Stainless Steel Fabricated by Laser Directed Energy Deposition under Closed-loop Control［J］. Surface and Coatings Technology， 2023， 463： 129527.
[3]	SUN J， LU H， LIANG Y， et al. Integrated Manufacturing Method for Compressor Blisks： LDED Ti65 on Sheet Ti-6Al-4V［J］. Materials Science and Engineering： A， 2025， 932： 148266.
[4]	YOON H S， LEE J Y， KIM H S， et al. A Comparison of Energy Consumption in Bulk Forming， Subtractive， and Additive Processes： Review and Case Study［J］. International Journal of Precision Engineering and Manufacturing-Green Technology， 2014， 1（3）： 261-279.
[5]	GEDDA H， POWELL J， WAHLSTRÖM G， et al. Energy Redistribution during CO2 Laser Cladding［J］. Journal of Laser Applications， 2002， 14（2）： 78-82.
[6]	JIANG X， TIAN Z， LIU W， et al. An Energy-efficient Method of Laser Remanufacturing Process［J］. Sustainable Energy Technologies and Assessments， 2022， 52： 102201.
[7]	WU J， LIAN K， DENG Y， et al. Multi-objective Parameter Optimization of Fiber Laser Welding Considering Energy Consumption and Bead Geometry［J］. IEEE Transactions on Automation Science and Engineering， 2022， 19（4）： 3561-3574.
[8]	LI J， HU J， ZHOU Q， et al. Transfer Learning-based Quality Monitoring of Laser Powder Bed Fusion across Materials［J］. Expert Systems with Applications， 2024， 252： 124150.
[9]	GAO B， PENG S， LI T， et al. Integration of Improved Meta-heuristic and Machine Learning for Optimizing Energy Efficiency in Additive Manufacturing Process［J］. Energy， 2024， 306： 132518.
[10]	NIU J， LI Y， QI X， et al. An Image-physics Dual-driven Machine Learning Framework for Cross-sectional Geometry Prediction in Laser Direct Energy Deposition［J］. Optics & Laser Technology， 2025， 192： 114150.
[11]	ZHANG R， WEI C， SHI T， et al. Study on Process Method and Forming Quality of Large-overhang Thin-walled Curved Tubes Fabricated by Annular Laser Metal Deposition［J］. Journal of Materials Processing Technology， 2025， 344： 119011.
[12]	OLIVEIRA J P， SANTOS T G， MIRANDA R M. Revisiting Fundamental Welding Concepts to Improve Additive Manufacturing： From Theory to Practice［J］. Progress in Materials Science， 2020， 107： 100590.
[13]	YUSUF S M， GAO N. Influence of Energy Density on Metallurgy and Properties in Metal Additive Manufacturing［J］. Materials Science and Technology， 2017， 33（11）： 1269-1289.
[14]	ZHU Y， PENG T， JIA G， et al. Electrical Energy Consumption and Mechanical Properties of Selective-laser-melting-produced 316L Stainless Steel Samples Using Various Processing Parameters［J］. Journal of Cleaner Production， 2019， 208： 77-85.
[15]	PENG T， LV J， MAJEED A， et al. An Experimental Investigation on Energy-effective Additive Manufacturing of Aluminum Parts via Process Parameter Selection［J］. Journal of Cleaner Production， 2021， 279： 123609.
[16]	LIU W， WEI H， LIU A， et al. Multi-index Co-evaluation of Metal Laser Direct Deposition： an Investigation of Energy Input Effect on Energy Efficiency and Mechanical Properties of 316l Parts［J］. Journal of Manufacturing Processes， 2022， 76： 277-290.
[17]	LU Q， JIN J， ZHANG P， et al. Performance of Vibration-assisted Laser Welded Joints Based on Orthogonal Experiment Design［J］. Journal of Materials Engineering and Performance， 2022， 31（3）： 2147-2158.
[18]	VINOD A R， SRINIVASA C K， KESHAVAMURTHY R， et al. A Novel Technique for Reducing Lead-time and Energy Consumption in Fabrication of Inconel-625 Parts by Laser-based Metal Deposition Process［J］. Rapid Prototyping Journal， 2016， 22（2）： 269-280.
[19]	SHAO D， BI X， HONG M， et al. Optimization of Process Parameters for Laser-directed Energy Deposition Coatings of FeCoNi + 1%Y₂O₃ High-entropy Alloy Based on Response Surface Methodology［J］. Materials， 2025， 18（4）： 883.
[20]	MENGHINI A， MAFFIA S， DEMIR A G， et al. Performance of Laser Metal Deposition on Hot-rolled Stainless Steel for Hybrid Steel Structures［J］. Construction and Building Materials， 2024， 443： 137744.
[21]	LIU Y， WANG F， XU D， et al. Microstructure and Mechanical Properties of Laser Metal Deposited Ti₆Al₄V Alloy with near Equiaxed β Grain Structure［J］. Journal of Materials Research and Technology， 2023， 22： 1935-1947.
[22]	DE FORMANOIR C， BRULARD A， VIVÈS S， et al. A Strategy to Improve the Work-hardening Behavior of Ti-6Al-4V Parts Produced by Additive Manufacturing［J］. Materials Research Letters， 2017， 5（3）： 201-208.
[23]	EL-HADAD S， NADY M， KHALIFA W， et al. Influence of Heat Treatment Conditions on the Mechanical Properties of Ti-6Al-4V Alloy［J］. Canadian Metallurgical Quarterly， 2018， 57（2）： 186-193.

Ti	Al	V	Fe
余量	5.5~6.75	3.5~4.5	≤0.30
C	N	H	O
≤0.08	≤0.05	≤0.008	≤0.20

Ti	Al	V	Fe
余量	5.5~6.75	3.5~4.5	≤0.30
C	N	H	O
≤0.08	≤0.05	≤0.008	≤0.20

水平	因素A/W	因素B/（mm·min^-1）	因素C/（g·min^-1）
1	650	450	2.4
2	700	500	3.6
3	750	550	4.8
4	800	600	6.0

水平	因素A/W	因素B/（mm·min^-1）	因素C/（g·min^-1）
1	650	450	2.4
2	700	500	3.6
3	750	550	4.8
4	800	600	6.0

序号	因素A	因素B	因素C	序号	因素A	因素B	因素C
1	1	1	1	9	3	1	3
2	1	2	2	10	3	2	4
3	1	3	3	11	3	3	1
4	1	4	4	12	3	4	2
5	2	1	2	13	4	1	4
6	2	2	1	14	4	2	3
7	2	3	4	15	4	3	2
8	2	4	3	16	4	4	1