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2014 International Conference on Green Materials and Environmental Engineering (GMEE2014)

作者： Bin Yang Post Doctoral Research Center of Jilin University School of Automobile and Transportation Tianjin University of Technology and Education

ISBN: (纸本)9783038353201

process parameters of nanostructured ZrO-7%YO coating during plasma spraying on the properties of the coating was optimized based on simulated annealing algorithm. BP neural network was applied to compute fitness of simulated annealing algorithm. A BP neural network model was built, four process parameters were input, the parameters included spraying distance, spraying electric current, primary gas pressure and secondary gas pressure, bonding strength of coating was output. Network was trained by orthogonal test data. process parameters of coating were optimized by simulated annealing algorithm. The results show that maximal bonding strength of coating is 43.0377 MPa. process parameters for plasma spraying nanostructured ZrO-7%YO coating are spraying distance of 80 mm, spraying electric current of 977.0283 A, primary gas pressure of 0.3046 MPa and secondary gas pressure 0.9886 MPa.

关键词： Plasma spraying Nanostructured coating Neural networks Simulated annealing algorithm process parameters optimization

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optimization of milling holes process parameters for carbon fiber reinforced composites based on cryogenic cooling

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MACHINING SCIENCE AND TECHNOLOGY 2025年第2期29卷 294-315页

作者： Wang, Fengbiao Cao, Lihua Shenyang Ligong Univ Sch Mech Engn Shenyang Peoples R China Shenyang Sport Univ Coll Exercise & Hlth Shenyang 110102 Peoples R China

The cryogenic cooling method of liquid nitrogen (LN2) spray is often adopted to effectively inhibit the delamination defects in the hole-making process of carbon fiber-reinforced composites (CFRP). But optimizing the processing parameters including cooling temperature, radial feed, milling speed, axial feed and nozzle angle is necessary. Therefore, the analysis method of variance was employed. A series of milling hole experiments were carried out at different temperature strategies. The results show that the LN2 cryogenic cooling method can achieve the high-quality and efficient cryogenic cooling milling hole compared with the conventional dry one, and the delamination defect has been greatly improved. Through processing parameter optimization range and significance analysis, the influence order is the cooling temperature, axial feed, nozzle angle, radial feed and milling speed. Meanwhile, the value of each influence factor is the cooling temperature of -170 degrees C, the axial feed of 30 mm/min, the nozzle angle of 36.5 degrees, the radial feed of 100 mm/min and the cutting speed of 250 m/min. And the actual processing result is fd = 1.023. Although it is slightly larger than the predicted value fd = 1.016, near 50% milling efficiency is increased. Furthermore, lowering the cryogenic cooling temperature will affect the binding strength of the fiber and the resin matrix and lead to the delamination of the hole outlet. A suitable LN2 jet angle is a necessary condition for effective cooling temperature. The research results can be used as a reference for obtaining high- quality milling hole technology at cryogenic cooling for fiber-reinforced composites.

关键词： Carbon fibers reinforced composite cryogenic cooling delamination defect orthogonal experiment process parameters optimization

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optimization of process parameters to Minimize Porosity and Splash in Cold Metal Transfer and Pulse Wire Arc Additive Manufacturing of High-Strength Aluminum Alloy

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ADVANCED ENGINEERING MATERIALS 2025年第7期27卷

作者： Zhang, Zhiqiang Zhuo, Shuai Lu, Xuecheng Yan, Junpei Gong, Pan Zhang, Tiangang Wu, Dongquan Liu, Hongli Civil Aviat Univ China Sch Aeronaut Engn Tianjin 300300 Peoples R China Huazhong Univ Sci & Technol Sch Mat Sci & Engn State Key Lab Mat Proc & Die & Mould Technol Wuhan 430074 Peoples R China Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore Civil Aviat Univ China Sino European Inst Aviat Engn Tianjin 300300 Peoples R China

This article examines the application of advanced cold metal transfer plus pulse composite arc technology for the thin-walled additive manufacturing of high-strength aluminum alloy AA2024. Response surface methodology is employed to design experiments and variance analysis is utilized to assess the model's reliability. Results are further optimized and validated using the non-dominated sorting genetic algorithm II. The focus is on optimizing key process parameters-wire feeding speed, interlayer temperature, protective gas flow rate, and welding wire elongation-to minimize porosity and splash. A comprehensive analysis of parameter interactions is conducted using contour maps and response surface plots. The findings indicate that wire elongation most significantly affects porosity, while wire feeding speed has the greatest impact on splash. The optimized parameters effectively reduce grain size under low heat input conditions, decrease hydrogen-induced porosity and solidification defects, achieving a porosity rate of 0.46% and a splash rate of 0.83%.

关键词： cold metal transfer and pulse porosity process parameters optimization splash degree

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Cutting stability and optimization of process parameters for the large-pitch screw high-feed turning

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2019年第19-20期233卷 6851-6865页

作者： Fu, Xiangfu Li, Zhe Zheng, Minli Wang, Xiurui Li, Junwei Harbin Univ Sci & Technol Key Lab Natl & Local United Engn High Efficiency Harbin Heilongjiang Peoples R China Harbin Univ Sci & Technol Engn Training Ctr 52 Xuefu Rd Harbin 150080 Heilongjiang Peoples R China

In this study, the machining characteristics of the large-pitch screw in high-feed turning are initially analyzed, and a dynamic model for the screw subjected to moving forces is proposed to study the chatter, which has been taken into consideration "quasi-regeneration effect" of the machined surface and the actual machining path. Then, a stability model of the lobes between the amount of feed and spindle speed in the turning screw finishing stage is achieved, taking into consideration deformation of the workpiece and the tool, on the basis of the vibration equation of the workpiece and the dynamic equation of the tool, and is experimentally verified as well. The dynamics model, and stability domain provide a basis upon which multiobjective process parameter optimization method including the amount of feed and spindle speed can be put forward during high-feed turning process. Experiments are likewise performed and the results show that no chatter occurs, verifying the optimization of machining process parameters for large-pitch turning. Meanwhile, it should be noted that the surface quality and shape accuracy of the machined surface are equivalent to the high-feed turning process.

关键词： Large-pitch screw dynamic modeling chatter stability process parameters optimization

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optimization of process parameters of SMAW process using NN-FGRA from the sustainability view point

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JOURNAL OF INTELLIGENT MANUFACTURING 2017年第6期28卷 1459-1480页

作者： Vimal, K. E. K. Vinodh, S. Raja, A. Natl Inst Technol Dept Prod Engn Tiruchirappalli 620015 Tamil Nadu India Bharat Heavy Elect Ltd Welding Res Inst Tiruchirappalli Tamil Nadu India

Welding process does not possess a good environmental image due to fumes, noise and other health hazards. But, it has been widely applied and is irreplaceable as far as structural industries are concerned. In welding process, many factors are responsible for environmental burdens, of which this study investigates and optimizes process parameters. Based on the pilot study, operating levels for parameters like current, voltage and welding speed, and various responses were identified. Further, the responses considered in the study include spatter, slag, fume generation rate, particulates and power consumption. A full factorial design of three factors at five levels requires 125 experiments for a complete analysis;however the conduct of a full factorial design experiment is expensive and consumes much time. Hence, orthogonal design was adopted for three inputs and five levels and 27 experiments were conducted. Further, five back propagation neural network model with network structure of 3-12-1 was individually developed to predict responses. values obtained for back propagation neural network model pertaining to slag, spatter, power consumption, fume generation rate and particulate formation are 0.99, 0.99, 0.989, 0.965 and 0.97 respectively. The responses for full factorial interaction were simulated. Fuzzy based grey relational analysis was used to optimize process parameters. Finally, life cycle assessment methodology outlined by ISO 14040 and 14044 was adopted to quantify the improvement in environmental performance due to parameter optimization. Thus, the proposed methodology helps to improve environmental performance of the manufacturing process with the experiments conducted using partial factorial design. Apart from environmental benefits, economic benefits and man hours saving are attained without compromising accuracy.

关键词： Sustainability practices process parameters optimization Neural network Grey fuzzy methods Life cycle assessment

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optimization of process parameters for pulsed laser milling of micro-channels on AISI H13 tool steel

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2013年第1期29卷 209-218页

作者： Teixidor, Daniel Ferrer, Ines Ciurana, Joaquim Oezel, Tugrul Univ Girona Dept Mech Engn & Ind Construct Girona 17071 Spain Rutgers State Univ Dept Ind & Syst Engn Piscataway NJ 08855 USA

This paper focuses on understanding the influence of laser milling process parameters on the final geometrical and surface quality of micro-channel feature fabricated on AISI H13 steel. Optimal selection of process parameters is highly critical for successful material removal and high dimensional and surface quality for micro-sized die/mold applications. A set of designed experiments is carried out in a pulsed Nd:YAG laser milling system using AISI H13 hardened tool steel as work material. Arrays of micro-channels have been fabricated using a range of process parameters such as scanning speed (SS), pulse intensity (PI), and pulse frequency (PF). The relation between process parameters and quality characteristics has been studied with experimental modeling. Multi-criteria decision making for material and process parameter selection for desired surface quality and dimensional accuracy is investigated using an evolutionary computation method based on particle swarm optimization (PSO). (c) 2012 Elsevier Ltd. All rights reserved.

关键词： process parameters optimization process parameters selection Laser milling process

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optimization of process parameters and catalyst compositions in carbon dioxide oxidative coupling of methane over CaO-MnO/CeO₂ catalyst using response surface methodology

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FUEL processING TECHNOLOGY 2006年第5期87卷 449-459页

作者： Istadi Amin, NAS Univ Teknol Malaysia UTM Skudai Fac Chem & Nat Resources Engn CREG Johor Baharu 81310 Malaysia

The optimization of process parameters and catalyst compositions for the CO2 oxidative coupling of methane (CO2-OCM) reaction over CaO-MnO/CeO2 catalyst was developed using Response Surface Methodology (RSM). The relationship between the responses, i.e. CH4 conversion, C hydrocarbons selectivity or yield, with four independent variables, i.e. CO2/CH4 ratio, reactor temperature, wt.% CaO and wt.% MnO in the catalyst, were presented as empirical mathematical models. The maximum C hydrocarbons selectivity and yields of 82.62% and 3.93%, respectively, were achieved by the individual-response optimization at the corresponding optimal process parameters and catalyst compositions. However, the CH4 conversion was a saddle function and did not show a unique optimum as revealed by the canonical analysis. Moreover pertaining to simultaneous multi-responses optimization, the maximum C selectivity and yield of 76.56% and 3.74%, respectively, were obtained at a unique optimal process parameters and catalyst compositions. It may be deduced that both individual- and multi-responses optimizations are useful for the recommendation of optimal process parameters and catalyst compositions for the CO2-OCM process. (c) 2005 Elsevier B.V. All rights reserved.

关键词： CO2-OCM CaO-MnO/CeO2 catalyst catalysts optimization process parameters optimization response surface methodology central composite design

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Simultaneous optimization of topology and process parameters for laser-powder bed fusion additive manufacturing

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STRUCTURAL AND MULTIDISCIPLINARY optimization 2023年第9期66卷 1-20页

作者： Gokdag, Istemihan Acar, Erdem Turkish Aerosp Ind Inc R&D Div Ankara Turkiye TOBB Univ Econ & Technol Dept Mech Engn Ankara Turkiye

Additive manufacturing (AM) technology is used in sectors such as automotive and aerospace, due to its advantages in producing complex and lightweight structures. However, it is necessary to reduce the total manufacturing costs for AM technology to become widespread. The topology optimization (TO) studies in the literature typically optimize only the design without taking into account the manufacturing phase or sequentially optimize the topology first and then the process parameters. On the other hand, simultaneous optimization of topology together with process parameters provides more efficient and less costly solutions. This paper describes a strategy for simultaneous optimization of topology along with process parameters of the laser-powder bed fusion (L-PBF) process. The topology, laser power, scanning speed, energy density, and yield strength are controlled by integrating the overall process-property-structure-performance relationship of the L-PBF process into the optimization. The proposed simultaneous optimization method aims to minimize the total cost function including material, manufacturing, and energy costs. Moreover, the constraint functions of the optimization include the volume fraction, the strength of the structure, and the energy density calculated according to the process parameters. The proposed method is successfully applied to three different design problems as cantilever beam, MBB beam, and L bracket, respectively. The results of different TO methods including conventional TO (compliance minimization), structural TO (similar to stress-constrained TO), and sequential process parameters and topology optimization are compared with the results of the proposed method. It is found that the proposed method provided the minimum cost results, and the obtained designs met the structural requirements.

关键词： Additive manufacturing Simultaneous optimization Topology optimization process parameters optimization Cost minimization Laser-powder bed fusion

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An effective cellular particle swarm optimization for parameters optimization of a multi-pass milling process

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APPLIED SOFT COMPUTING 2012年第11期12卷 3490-3499页

作者： Gao, Liang Huang, Jida Li, Xinyu Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

In the milling process, the selection of machining parameters is very important as these parameters determine the processing time, quality, cost and so on, especially in the high-accuracy machine tools. However, the parameters optimization of a multi-pass milling process is a nonlinear constrained optimization problem which is difficult to be solved by the traditional optimization techniques. Therefore, in order to solve this problem effectively, this paper proposes a novel parameters optimization method based on the cellular particle swarm optimization (CPSO). To address the constraints efficiently, the proposed method combines two constraints handling techniques, including the penalty function method and the constraints handling strategy of PSO. In the proposed CPSO, the smart cell constructs its neighborhood with self-adaptive function and constraints handling techniques, which guide the unfeasible particles to move to the feasible regions and search for better solutions. A case is adopted and solved to illustrate the effectiveness of the proposed CPSO algorithm. The results of the experiment study are analyzed and compared with those of the previous algorithms. The experimental results show that the proposed approach outperforms other algorithms and has achieved significant improvement. (c) 2012 Elsevier B.V. All rights reserved.

关键词： process parameters optimization Multi-pass milling Cellular particle swarm optimization Constraints handling techniques

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optimization of laser welding process parameters of stainless steel 316L using FEM, Kriging and NSGA-II

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ADVANCES IN ENGINEERING SOFTWARE 2016年第0期99卷 147-160页

作者： Jiang, Ping Wang, Chaochao Zhou, Qi Shao, Xinyu Shu, Leshi Li, Xiongbin Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

Laser welding process parameters have significant effects on the welding bead profile and quality of the welding joint. This paper proposes an integration method of process parameters optimization using finite element method (FEM), Kriging metamodels and nondominated sorting genetic algorithm II (NSGA-II) in laser welding for stainless steel 316L. The process parameters in this study are laser power (LP), welding speed (WS) and laser focal position (LF). Firstly, a three-dimensional thermal finite element model is developed to obtain the simulated results of bead width (BW) and depth of penetration (DP). Then, Kriging metamodels are constructed to reflect the relationship between input process parameters and output responses. Finally, NSGA-II is used to search for multi-objective Pareto optimal solutions. In addition, the main effects and contribution rates of multiple process parameters on welding bead profile are analyzed. The results of verification experiments indicate that the optimal process parameters are effective and reliable for producing expected welding bead profile. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Laser welding process parameters optimization Finite element method Kriging NSGA-II

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