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process parameter optimization for laser directed energy deposition B4C/Al neutron absorbing material via Taguchi method

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OPTICS AND LASER TECHNOLOGY 2025年 184卷

作者： Xiao, Weiwei Liu, Yilong Huang, Jinghao Zou, Shuliang Ren, Zhenghao Liu, Shihong Wang, Yanli Univ South China Hunan Prov Key Lab Emergency Safety Technol & Equi Hengyang 421001 Hunan Peoples R China Univ South China Sch Mech Engn Hengyang 421001 Hunan Peoples R China

In this study, the fabrication process parameters of laser directed energy deposition (LDED) B4C/Al composites that can achieve the maximum relative density were obtained via Taguchi method. The single-track experiments were employed to determine the appropriate range of laser power, scanning speed, powder feeding speed and protective gas flow rate. Based on the values of these process parameters, an L16 orthogonal experiment was designed using the Taguchi method, and the signal-to-noise (S/N) ratio analysis and analysis of variance (ANOVA) were performed to obtain the LDED process parameters that can achieve the B4C/Al composites with maximum relative density. And the regression equation and fabrication of bulk composite were adopted to verify the effectiveness of the optimized process parameters. The optimal combination of process parameters was laser power of 1600 W, scanning speed of 350 mm/min, powder feeding speed of 2.0 r/min, and protective gas flow rate of 8.5 L/min. This study will help to establish an effective process for fabricating B4C/Al composite using LDED.

关键词： B 4 C/Al neutron absorbing material Laser directed energy deposition Taguchi method process parameter optimization

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process parameter optimization for Dimensional Accuracy of Vacuum-Assisted Printed Samples Using Response Surface Methodology

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JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE 2025年 1-11页

作者： Shahrum, Mohd Afiq Rajendran, Thavinnesh Kumar Maidin, Shajahan Ismail, Shafinaz Univ Teknikal Malaysia Melaka Fac Ind & Mfg Technol & Engn Melaka Malaysia

Fused deposition modeling (FDM) is a widely used additive manufacturing technique known for its versatility and cost-effectiveness in producing complex prototypes and parts. However, FDM needs more mechanical properties, surface quality issues, and low-dimensional accuracy. This study aims to enhance the dimensional accuracy of FDM-fabricated thermoplastics, specifically acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA), by optimizing two process parameters: infill density (20%, 55%, and 80%) and printing pressure (101.3 kPa atmospheric pressure and 20 kPa vacuum pressure). The printed samples' dimensions, including hole diameter, corner diameter, thickness, width, length, and perpendicular, were precisely measured using a coordinate measuring machine. The Response Surface Methodology was employed to quantify the relationship between process parameters and dimensional accuracy. The results indicated that vacuum-printed samples demonstrated a 23% improvement in overall dimensional accuracy compared to those printed at atmospheric pressure. For ABS, the optimal process parameters were identified as 55% infill density and 20 kPa vacuum pressure, while for PLA, the best accuracy was achieved at 80% infill density and 20 kPa vacuum pressure. Although the material did not reach 100% of the desired dimensional accuracy, these optimized settings significantly enhanced precision, particularly for applications requiring tight tolerances, such as automotive and aerospace components. The findings of this study provide crucial insights for improving dimensional accuracy in FDM-printed parts, contributing to more reliable and precise additive manufacturing processes.

关键词： acrylonitrile-butadiene-styrene dimensional accuracy fused deposition modeling polylactic acid process parameter optimization response surface methodology vacuum system

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Energy Consumption Modeling and process parameter optimization of Internal Gear Power Honing Under Multi-Axis Coupling

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 14510-14524页

作者： Zhang, You Li, Congbo Tang, Ying Cao, Huajun Tao, Guibao Chongqing Univ State Key Lab Mech Transmiss Adv Equipment Chongqing 400044 Peoples R China Rowan Univ Dept Elect & Comp Engn Glassboro NJ 08028 USA

The internal gear power honing process is widely used in gear machining for electric vehicles because of the advantages of high-precision and high-efficiency machining. The gear honing process involves six axes and high spindle speeds, this process contributes a substantial amount of energy consumption but has less attention on energy saving. To improve the energy efficiency of gear honing process, this paper proposes an energy consumption modeling and process parameter optimization method under multi-axis coupling. The multi-axis coupling motion and energy consumption characteristics of gear honing process are analyzed. The energy consumption model of gear honing process under multi-axis coupling is then established, and the influence law of process parameters on honing energy consumption is investigated. Furthermore, a multi-objective process parameter optimization model for minimizing energy consumption and machining time is constructed. An improved multi-objective atomic orbital search (IMOAOS) algorithm is developed to solve the multi-objective optimization problem. The gear honing experiment results demonstrate that the optimized scheme reduces energy consumption by 39.75% and machining time by 8.48% compared to the empirical scheme. The proposed multi-objective optimization scheme also significantly balances the energy consumption and machining time of gear honing process compared with single-objective optimization.

关键词： Energy consumption Gears optimization Wheels Couplings Milling Machine tools Turning optimization models Feeds Energy consumption modeling process parameter optimization internal gear power honing multi-axis coupling

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process parameter optimization for fused deposition modeling using response surface methodology combined with fuzzy inference system

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第1-4期73卷 87-100页

作者： Peng, Anhua Xiao, Xingming Yue, Rui China Univ Min & Technol Sch Mechatron Engn Xuzhou 221116 Jiangsu Peoples R China Huaihai Inst Technol Engn Training Ctr Lianyungang 222005 Jiangsu Peoples R China Jiangsu Coll Informat Technol Dept Mechatron Engn Wuxi 214153 Jiangsu Peoples R China

Fused deposition modeling (FDM) is gaining distinct advantages because of its ability to fabricate the 3D physical prototypes without the restrictions of geometric complexities, while when it comes to accuracy and efficiency, the advantages of FDM is not distinct, and so how to improve them is worthy of study. Focusing on process parameter optimization, such parameters as line width compensation, extrusion velocity, filling velocity, and layer thickness are selected as control factors, input variables, and dimensional error, warp deformation, and built time are selected as output responses, evaluation indexes. Experiment design is assigned according to uniform experiment design, and then the three output responses are converted with fuzzy inference system to a single comprehensive response. The relation between the comprehensive response and the four input variables is derived with second-order response surface methodology, the correctness of which is further validated with artificial neural network. Fitness function is created using penalty function and is solved with genetic algorithm toolbox in Matlab software. With confirmation test, the results are obtained preferring to the results of the experiment 1 with the best comprehensive response among the 17 experiment runs, which confirms that the proposed approach in this study can effectively improve accuracy and efficiency in the FDM process.

关键词： Fused deposition modeling (FDM) process parameter optimization Response surface methodology (RSM) Fuzzy inference system (FIS) Artificial neural network (ANN) Genetic algorithm (GA)

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process parameter optimization for the Laser Metal Deposition of a Functionally Graded GH4169/K417G Superalloy and the Effects of Preheating and Composition on Cracking Behavior

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JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE 2024年第12期33卷 5776-5792页

作者： Liu, Shuai Liu, Changsheng Yuan, Chao Chinese Acad Sci Inst Met Res Shenyang Natl Lab Mat Sci Shenyang 110016 Peoples R China Northeastern Univ Sch Mat Sci & Engn Key Lab Anisotropy & Texture Mat Minist Educ Shenyang 110819 Peoples R China

This study aims to select a suitable process and composition for the fabrication of a functionally graded GH4169/K417G superalloy by laser metal deposition (LMD). A universal process parameter was optimized through an orthogonal test, and the influence of the preheated substrate temperature on the residual stress was investigated. Finally, the effects of preheating and composition on cracking and methods for controlling cracking were noted. As a result, equations for the relationship between the relative densities of samples prepared by LMD with different graded compositions and energy density coupled to laser parameters were established for the first time. Thus, an equation for the relationship between the appropriate laser power and graded composition was obtained. By preheating the substrate to higher temperatures, the maximum residual stress was gradually reduced from 753 to 362 MPa, and thus, the cracking tendency was suppressed partly. However, the decisive cracking factor was the & gamma;/& gamma;& PRIME;eutectic characteristic during the forming of K417G. When the terminal graded composition was designed to be 10% GH4169, the & gamma;/& gamma;& PRIME;eutectic phase exhibited a smaller size and lower quantity, which prevented cracking. The results of this research will help engineers select the appropriate compositions and processes to prepare dual-superalloy blisks.

关键词： cracking functionally graded material (FGM) laser metal deposition (LMD) process parameter optimization superalloys

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process parameter optimization of K477 and GH4169 for defect control in laser-directed energy deposition using Taguchi design of experiments

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2024年第9-10期131卷 4447-4467页

作者： Li, Yuan Chen, Yun Hou, Liang Ye, Chao Chen, Shuyuan Huang, Xiaomei Zou, Jiahao Xiamen Univ Pen Tung Sah Inst Micronano Sci & Technol Xiamen 361102 Peoples R China Xiamen Univ Discipline Intelligent Instrument & Equipment Xiamen 361102 Peoples R China

Turbine blisk used for aerospace engines withstands harsh working environments and requires multiple materials suited for different function requirements. Laser-directed energy deposition (L-DED) is ideal for manufacturing of multi-material turbine blisk. This study investigates the L-DED manufacturability of two dissimilar nickel-based superalloys K477 and GH4169 used for multi-material turbine blisk. K477 is prone to produce defects such as cracks and pores because of its high Ti and Al compositions, and the bimetallic transition zone of the multi-material turbine blisk is also easy to generate cracks. Therefore, the effects of process parameters (laser power PL, scanning speed v, and powder feed rate mp) on the defects during L-DED of the single materials (i.e., 100% K477 or 100% GH4169) and the transition zone material (50 wt% K477 + 50 wt% GH4169) are assessed. The internal defect optimization of K477 fabricated by L-DED is achieved by using the Taguchi orthogonal experiment design. The optimized results show that unfused defects and cracks of K477 disappear, and a high cross-sectional density up to 99.98% is obtained, which indicates the possibility of controlling internal defect through the proposed process parameter optimization method. This work provides a reasonable parameter optimization method for L-DED process in the engineering applications of multi-material parts.

关键词： Laser-directed energy deposition Nickel-based superalloys Multi-material process parameter optimization Taguchi design

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process parameter optimization for laser directed energy deposition (LDED) of Ti6Al4V using single-track experiments with small laser spot size

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OPTICS AND LASER TECHNOLOGY 2024年 175卷

作者： Gonnabattula, Avinash Thanumoorthy, Raja S. Bontha, Srikanth Balan, A. s s Kumar, V. Anil Kanjarla, Anand K. IIT Madras Dept Met & Mat Engn Chennai India NITK Surathkal Dept Mech Engn Mangaluru India Vikram Sarabhai Space Ctr Mat & Mech Ent Trivandrum India

Single-track experiments are routinely used in the optimization of process parameters in additive manufacturing processes. Most of the process parameter optimization studies use a laser spot size of 1 mm or more. Since laser spot size affects the input energy density and in turn the efficiency of the deposition process, it is important to develop process maps every time a laser of different spot sizes is used. In this work, we determine the process maps for a laser of 0.6 mm spot size. By combining the process maps and the metallographic inspection, we estimate the optimum process parameters (laser power, scan speed, powder feed rate) for building Ti6Al4V components using powder-based laser-directed energy deposition(LDED). Single-tracks corresponding to 64 different parameter combinations are deposited. After eliminating the process parameter combinations resulting in defective tracks, the optimum process parameters of 300 W laser power and 720 mm min-1 -1 scan speed is established by considering the relationship between the process parameters and the geometrical features of the deposit. The experimental results are then used to calibrate the modeling parameters of a three-dimensional finite element model for simulating the deposition process.

关键词： Ti6Al4V Directed energy deposition Single-track depositions process parameter optimization Dilution

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process parameter optimization FOR ADDITIVELY MANUFACTURED STAINLESS STEEL 316L PARTS BY SELECTIVE ELECTRON BEAM MELTING 3

PROCESS PARAMETER OPTIMIZATION FOR ADDITIVELY MANUFACTURED S...

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3rd International Conference on Progress in Additive Manufacturing (Pro-AM)

作者： Wang, Chengcheng Tan, Xipeng Liu, Erjia Tor, Shu Beng Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore Ctr 3D Printing 50 Nanyang Ave Singapore 639798 Singapore

An experimental study of process parameter optimization for stainless steel 316L (SS316L) parts additively manufactured by selective electron beam melting (SEBM) was carried out. The process parameters for different stages, particularly in the in-fill hatch melting stage, were optimized in this study. Near-fully dense (>99%) SS316L parts have been successfully fabricated with well-melted surfaces. Microstructural characterization was performed on the as-SEBM-built SS316L parts with the optimal process parameters. It revealed that near-equiaxed grains were formed, which is distinctive from the counterparts additively manufactured by other SEBM processes. The mechanism for the formation of near-equiaxed grains was discussed in detail. This paper provides an insight into fabricating SS316L parts with high density and desirable microstructure via SEBM process.

关键词： additive manufacturing selective electron beam melting stainless steel 316L process parameter optimization near-equiaxed grain structure

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Laser-directed energy deposition of CuCrZr alloy: from statistical process parameter optimization to microstructural analysis

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2023年第9-10期126卷 4407-4418页

作者： Zardoshtian, Ali Ansari, Mazyar Esmaeilzadeh, Reza Keshavarzkermani, Ali Jahed, Hamid Toyserkani, Ehsan Univ Waterloo Dept Mech & Mechatron Engn Multiscale Addit Mfg Lab Waterloo ON N2L 3G1 Canada Univ Waterloo Dept Mech & Mechatron Engn Fatigue & Stress Anal Lab FATSLab 200 Univ Ave West Waterloo ON N2L 3G1 Canada

Laser-directed energy deposition (LDED) is a suitable manufacturing technology for processing CuCrZr alloy that has recently gained interest to be used in high heat flux applications due to its unique thermal properties. Despite its promising properties, the successful deposition of CuCrZr alloy through LDED processing is impeded by its low laser-material absorptivity and high thermal conductivity. To address this challenge, a systematic investigation was conducted using a 2-kW disk laser with a wavelength of 1064 nm and a coaxial nozzle head, as detailed in this study. In that regard, process parameter optimization is exercised first to achieve proper deposition, then the microstructure, and microhardness of single tracks are investigated. In this study, a two-step statistical optimization approach utilizing response surface methodology (RSM) is employed to optimize the geometrical characteristics of the tracks, while laser power, scanning speed, and powder feed rate are considered input variables. The laser power of 1550 W, scanning speed of 4.5 mm/s, and feed rate of 12 g/min are found as the optimum set of process parameters that yield acceptable single-track geometries with proper bead shape and sufficient amount of dilution as well as the maximum deposition rate. Furthermore, the results from the microstructural characterization by optical microscopy, SEM, and EBSD reveal the correlation between the microstructure and the process parameters. Increasing the laser power (P) from 1250 to 1550 W and decreasing the combined parameter of powder feed rate over scanning speed (F/V) from 0.05 to 0.036 g/mm resulted in a noticeable increase in columnarity of the grain structure from 41 to 51.5%. Finally, the microhardness results revealed a moderate transition of hardness from the top of the bead to the bottom of the melt pool for all samples.

关键词： Additive manufacturing Laser-directed energy deposition CuCrZr alloy process parameter optimization Grain morphology Microhardness

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Multi-stage manufacturing process parameter optimization method based on improved marine predator algorithm

ENGINEERING RESEARCH EXPRESS

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ENGINEERING RESEARCH EXPRESS 2024年第2期6卷

作者： Jiang, Xiaojun Zhan, Hongfei Yu, Junhe Wang, Rui Ningbo Univ Coll Mech Engn & Mech Ningbo Peoples R China

Product quality is a critical factor in manufacturing industry competition, and mechanical processing technology has been widely applied in manufacturing, directly affecting product quality. Therefore, it is very important to find the appropriate optimal parameters to improve the impact of processing on product quality. However, modern production processes are characterized by complex mechanisms and the mutual influence of multiple processes, which poses higher challenges for optimizing processing technology parameters. In this regard, the thesis proposes a method for optimizing process parameters in multi-process manufacturing based on an improved marine predator algorithm, aiming to optimize and improve process parameters in multi-process manufacturing processes. Firstly, a multi-process modeling strategy is adopted to explore the nonlinear relationship between process parameters and quality indicators based on multi-gene genetic planning, establishing a multi-process parameter optimization objective model. This effectively solves the problem of modeling difficulty caused by severe coupling of multiple processes. Then, to improve the efficiency of solving the optimization objective model, an improved marine predator algorithm is proposed, utilizing reverse learning strategies and mixed control parameters to enhance optimization capability, thereby obtaining the global optimal solution. Finally, using production process data from a certain factory as an example, the feasibility of the proposed method is verified, achieving the goal of multi-process process parameter optimization and ensuring the stability of product quality.

关键词： process parameter optimization multistage manufacturing improved marine predator algorithm multigene genetic programming

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