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process parameter analysis of inertia friction welding nickel-based superalloy

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第9-12期71卷 1909-1918页

作者： Wang, F. F. Li, W. Y. Li, J. L. Vairis, A. Northwestern Polytech Univ State Key Lab Solidificat Proc Sch Mat Sci & Engn Xian 710072 Shaanxi Peoples R China TEI Crete Dept Mech Engn Iraklion 71004 Crete Greece

A two-dimensional axisymmetric model for the inertia friction welding (IFW) of a nickel-based superalloy was developed. The influences from the axial pressure, initial rotational speed, and moment of inertia of the flywheel on the interface temperature and axial shortening were systemically examined. The analysis shows that the mechanical energy mainly depends on the initial rotational speed, and a relatively high axial pressure will increase conversion efficiency from mechanical energy to effective welding heat. The axial shortening is found to be approximately proportional to the square of initial rotational speed while logarithmical to the axial pressure. Based on this work, the weldability criteria for IFW nickel-based superalloy was established. Additionally, the approach for welding parameter optimization was performed considering the evolution of temperature profiles from various parameters. The results show that the axial pressure has a more obvious effect on the width of high-temperature zone than the rotational speed during the quick shortening stage.

关键词： Inertia friction welding Nickel-based superalloy Finite element method process parameter optimization

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Modelling and optimization of process parameters of wire electrical discharge machining

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2009年第11期223卷 1431-1440页

作者： Rao, R. V. Pawar, P. J. SV Natl Inst Technol Dept Mech Engn Surat 395007 Gujarat India

The optimum selection of process parameters is essential for advanced machining processes as these processes incur high initial investment, tooling cost, operating cost, and maintenance cost. Wire electrical discharge machining (WEDM) is a widely accepted advanced material removal process used to manufacture components with intricate shapes and profiles. The present work highlights the development of mathematical models using response surface modelling (RSM) for correlating the inter-relationships of various WEDM parameters such as pulse-on time, pulse-off time, peak current, and servo feed setting on the machining speed and surface roughness. A recently developed advanced optimization technique, known as artificial bee colony (ABC), is then applied to find the optimal combination of process parameters with an objective of achieving maximum machining speed for a desired value of surface finish.

关键词： wire electrical discharge machining response surface modelling process parameter optimization artificial bee colony algorithm

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A real-time dressing method for metal lapping pads based on the thermal deformation effect

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2022年第1-2期120卷 945-958页

作者： Zhao, Lingyu Zhao, Huiying Wang, Hairong Xie, Ruiqing Cao, Mingchen Zhang, Mingzhuang Zhao, Shijie Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Shaanxi Peoples R China China Acad Engn Phys Res Ctr Laser Fus Mianyang 621900 Sichuan Peoples R China

Surface shape and accuracy of the metal lapping pad have a significant impact on the performance of the lapping process for flat optical components, which are usually improved by the dressing process. A real-time dressing system for metal lapping pad surface shape (RDLS system) based on the bimetal thermal deformation effect is proposed. Unlike traditional dressing methods (e.g., turning dressing with a diamond tool), the real-time dressing based on the RDLS system is a material-loss-free and in-process dressing method. A full-aperture lapping turntable based on the RDLS system was designed, in which the working heat was analyzed. The displacement models of the lapping pad surface were established by regression analysis. Finally, several experiments were conducted to verify the functionality of the RDLS system. During turning dressing (turntable rotational speed n = 100 rpm), the displacement error was compensated by the RDLS system, which was caused by the working heat of the turntable shaft system. During the lapping processing for optical elements (n <= 20 rpm), the correction displacement was controlled by the RDLS system, which realized the real-time dressing of the lapping pad surface. The process performance of the plane optical component was optimized with the RDLS system (process parameter: the coolant temperature t). The effectiveness and practicality of the RDLS system were demonstrated experimentally.

关键词： Real-time dressing Bimetal thermal deformation effect Thermal deformation error compensation process parameter optimization

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Influence of pulsed current GTAW-WAAM process parameters on the single layer bead geometry and multi bead multi-layer deposition of a nickel-based superalloy

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MATERIALS TODAY COMMUNICATIONS 2024年 39卷

作者： Kumar, M. D. Barath Arivazhagan, N. Tofil, Szymon Andersson, Joel Kozak, Jindrich Manikandan, M. Vellore Inst Technol Sch Mech Engn Vellore 632014 India Kielce Univ Technol Fac Mechatron & Mech Engn Laser Res Ctr Ave Tysiaclecia Panstwa Polskiego 7 PL-25314 Kielce Poland Univ West Dept Engn Sci S-46186 Trollhattan Sweden VSB Tech Univ Ostrava Fac Mech Engn Ostrava Czech Republic

Wire + arc additive manufacturing (WAAM) is a state-of-the-art and highly efficient technique utilized to produce near net-shaped products on a large scale, employing a layer-by-layer approach. This research used pulsed current mode welding for single-layer bead-on-plate experiments to optimise the process parameters for WAAM of Hastelloy C-276. The effect of process parameters including pulsed current, pulsed frequency, and pulse duty cycle was systematically investigated on the weld appearance, depth of penetration, layer width, and layer height. The optimisation of single layer experimental runs was conducted using Box-Behnken designs (BBD) and the response surface method to construct several regression models. An analysis of variance was employed to validate the accuracy of both the measured and generated models. The BBD results indicate that interactions have a more significant impact on the peak current parameter than the resulting impact of pulse duty cycle and frequency. Validation tests were performed on the model with the optimal process variables that were identified, and its mechanical and metallurgical properties were analysed. Macrostructure and microstructural analysis of the single layer showed that the specified process parameters led to acceptable base metal fusion and bead is free from cracking. There was a considerable decrease in elemental segregation while using the pulse mode technique. Finer grain structure and reduced microsegregation enhance the hardness. Further residual stress (RS) at weld bead and base plate was 213 MPa and -240 MPa. Nonhomogeneous heat transfer during welding affects RS compressive and tensile characteristics. WAAM printing quality requires precise control of LH, LW, and DOP. This research aimed to propose suitable parameter values for manufacturing WAAM component for usage in chemical processing, nuclear, marine, and industrial settings by using unique pulsing features.

关键词： Wire + arc additive manufacturing process parameter optimization Layer geometry Nickel based superalloy Microstructure Residual stress

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optimization of heat treatment deformation control process parameters for face-hobbed hypoid gear using FEA-PSO-BP method

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JOURNAL OF MANUFACTURING processES 2024年 117卷 40-58页

作者： Sun, Beier Liu, Huaming Tang, Jinyuan Rong, Shifeng Liu, Yashuai Jiang, Weizhe Cent South Univ State Key Lab Precis Mfg Extreme Serv Performance Changsha 410017 Peoples R China Cent South Univ Coll Mech & Elect Engn Changsha 410017 Peoples R China

The face-hobbed hypoid gears are manufactured from low-carbon alloy steel and possess a complex geometric profile. Typically, carburizing and quenching are employed to enhance the surface hardness of the gear teeth. However, deformation unavoidably occurs during the processes of carburizing, quenching, and tempering. This deformation leads to a reduction in the contact precision of the gear pair and an increase in noise during meshing. To effectively control the thermal deformation of face-hobbed hypoid gear and ensure their accuracy, a computational model for carburizing, quenching, and low-temperature tempering processes of face-hobbed hypoid gear was established using the finite element method (FEM) in this study. The computational model simulated the temperature field, phase field, and stress-strain field during the heat treatment process, and the accuracy of hardness, phase transformation structure, and deformation in the model was confirmed by experimental verification. The investigation, conducted through single-factor experiments, aimed to study the impact of process parameters such as carburizing potential, quenching temperature, oil temperature, and tempering temperature on heat treatment deformation. The study results demonstrated that the quenching temperature has a relatively significant influence on the tooth form error. To control and reduce the thermal deformation error on the tooth surface, a back propagation (BP) neural network was constructed using single factor experiments and orthogonal experiments. The optimal process parameters were obtained through particle swarm optimization (PSO) algorithm. Under the optimal process parameters, the average tooth form error of the working surface was reduced by 2.3 mu m (14 %), and the range was reduced by 6.2 mu m (13 %). The FEA-PSO-BP method for optimizing process parameters to reduce thermal deformation in heat treatment offers a set of parameters that minimize the thermal deformation. This method can be

关键词： Computer simulation Face-hobbed hypoid gear Heat treatment deformation Multi -field coupling Deformation prediction process parameter optimization

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Prediction and optimization method for welding quality of components in ship construction

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SCIENTIFIC REPORTS 2024年第1期14卷 1-18页

作者： Liu, Jinfeng Cheng, Yifa Jing, Xuwen Liu, Xiaojun Chen, Yu Jiangsu Univ Sci & Technol Zhenjiang 212100 Jiangsu Peoples R China Southeast Univ Nanjing 211189 Peoples R China

Welding process, as one of the crucial industrial technologies in ship construction, accounts for approximately 70% of the workload and costs account for approximately 40% of the total cost. The existing welding quality prediction methods have hypothetical premises and subjective factors, which cannot meet the dynamic control requirements of intelligent welding for processing quality. Aiming at the low efficiency of quality prediction problems poor timeliness and unpredictability of quality control in ship assembly-welding process, a data and model driven welding quality prediction method is proposed. Firstly, the influence factors of welding quality are analyzed and the correlation mechanism between process parameters and quality is determined. According to the analysis results, a stable and reliable data collection architecture is established. The elements of welding process monitoring are also determined based on the feature dimensionality reduction method. To improve the accuracy of welding quality prediction, the prediction model is constructed by fusing the adaptive simulated annealing, the particle swarm optimization, and the back propagation neural network algorithms. Finally, the effectiveness of the prediction method is verified through 74 sets of plate welding experiments, the prediction accuracy reaches over 90%.

关键词： Quality prediction Components welding Welding quality process parameter optimization

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Setting the process parameters for the coating process in order to assure tablet appearance based on multivariate analysis of prior data

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INTERNATIONAL JOURNAL OF PHARMACEUTICS 2016年第1期511卷 341-350页

作者： Tanabe, Shuichi Nakagawa, Hiroshi Watanabe, Tomoyuki Minami, Hidemi Kano, Manabu Urbanetz, Nora A. Daiichi Sankyo Co Ltd Formulat Technol Res Labs Hiratsuka Kanagawa 2540014 Japan Dauchi Sankyo Europe GmbH Pharmaceut Dev Luitpoldstr 1 D-85274 Pfaffenhofen Germany Kyoto Univ Dept Syst Sci Kyoto 6068501 Japan

Designing efficient, robust process parameters in drug product manufacturing is important to assure a drug's critical quality attributes. In this research, an efficient, novel procedure for a coating process parameter setting was developed, which establishes a prediction model for setting suitable input process parameters by utilizing prior manufacturing knowledge for partial least squares regression (PLSR). In the proposed procedure, target values or ranges of the output parameters are first determined, including tablet moisture content, spray mist condition, and mechanical stress on tablets. Following the preparation of predictive models relating input process parameters to corresponding output parameters, optimal input process parameters are determined using these models so that the output parameters hold within the target ranges. In predicting the exhaust air temperature output parameter, which reflects the tablets' moisture content, PLSR was employed based on prior measured data (such as batch records of other products rather than design of experiments), leading to minimal new experiments. The PLSR model was revealed to be more accurate at predicting the exhaust air temperature than a conventional semi-empirical thermodynamic model. A commercial scale verification demonstrated that the proposed process parameter setting procedure enabled assurance of the quality of tablet appearance without any trial-and-error experiments. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Tablet film coating process parameter optimization Scale-up Multivariate analysis Partial least squares regression (PLSR)

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Optimizing additive manufacturing parameters for graphene-reinforced PETG impeller production: A fuzzy AHP-TOPSIS approach

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RESULTS IN ENGINEERING 2024年 24卷

作者： Raja, S. Praveenkumar, V Rusho, Maher Ali Yishak, Simon Chennai Inst Technol Ctr sustainable Mat & Surface Metamorphosis Chennai 600069 Tamilnadu India Amrita Vishwa Vidyapeetham Dept Mech Engn Amritapuri 690525 India Univ Colorado Engn Engn Management Lockheed Matin Engn Management Boulder CO 80308 USA Arba Minch Univ Coll Engn & Agroind Technol Sawla Campus Arba Minch 40003 Ethiopia

Additive manufacturing, particularly 3D printing, has transformed production by enabling precise, layer-by-layer construction with minimal material waste. This study aims to optimize the mechanical properties and production efficiency of impellers manufactured using Graphene-Reinforced Polyethylene Terephthalate Glycol (G-PETG) filament. By employing the Fuzzy Analytic Hierarchy process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), we identified optimal 3D printing parameters. The results showed that a 65 % infill density, 0.20 mm layer height, 50 mm/s printing speed, 90 degrees C platform temperature, 240 degrees C extruder temperature, and 90 mm/s traverse speed led to a 15 % improvement in tensile strength and a 12 % reduction in production time compared to baseline settings. Additionally, the impellers produced demonstrated superior surface finish and structural integrity, making them suitable for high-performance applications. These findings underscore the importance of parameter optimization in enhancing the performance of 3D-printed components, particularly for applications requiring high mechanical strength and precision.

关键词： Additive manufacturing process parameter optimization Fuzzy AHP-TOPSIS Composite thermoplastic polymer Sustainable materials Mechanical property Fused deposition modeling Material performance Impeller application

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optimization of density and surface morphology of SS 316L/IN718 functionally graded thin-walled structures using hybrid prediction-multi-objective optimization method

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JOURNAL OF MANUFACTURING processES 2024年 120卷 337-352页

作者： Ma, Zongyu Liu, Weiwei Li, Wanyang Liu, Huanqiang Lv, Zhenxin Song, Jianrong Huang, Yujin Liu, Bingjun Liu, Yanming Zhang, Yingzhong Dalian Univ Technol Sch Mech Engn Dalian 116024 Peoples R China Dalian Univ Technol State Key Lab High Performance Precis Mfg Dalian 116024 Peoples R China Dalian Univ Technol Ningbo Inst Ningbo 315000 Peoples R China

During the process of using directed energy deposition (DED) to prepare functionally graded material (FGM), there is a coupling problem involving multiple materials and parameters. The generation of intermetallic compounds and mismatched thermal property parameters often leads to the occurrence of defects such as pores and cracks at the microscopic level, as well as poor surface quality at the macroscopic level. In response to the issues, a hybrid prediction-multi-objective optimization method is proposed for the process parameter optimization of DED-fabricated thin-walled structures with SS 316 L/IN718 FGM. The aim is to achieve optimal density and surface morphology. The study investigates the influence of process parameters on the density and surface morphology of SS 316 L/IN718 functionally graded thin-walled structures during the preparation process and analyzes the reasons for defect generation and surface morphology changes. Based on the results, it can be inferred that interlayer lifting has the most prominent impact on density. The density first increases and then decreases as interlayer lifting increases. On the other hand, scan speed has a significant effect on surface morphology, with an increase leading to a decrease in surface roughness. The presence of ceramic oxides and intermetallic compounds in gradient materials induces cracking, and the accumulation of Nb- and Mo-rich phases, as well as columnar to equiaxed transition (CET), causes thermal stress and residual stress concentration, leading to the expansion of defects. Hybrid prediction-multi-objective optimization achieved optimal density and surface roughness of 8001 kg/m3 and 180.96 mu m, respectively. The model's reliability was validated experimentally.

关键词： Functionally graded material process parameter optimization Density Surface roughness Predictive model

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optimization of Injection Molding process of Transparent Complex Multi-Cavity Parts Based on Kriging Model and Various optimization Techniques

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2021年第12期46卷 11835-11845页

作者： Li, Sai Fan, Xi Ying Guo, Yong Huan Liu, Xin Huang, Hai Yue Li Cao, Yan Li, Lu Lu Jiangsu Normal Univ Sch Mech & Elect Engn Xuzhou 221116 Jiangsu Peoples R China CNPC Engn Technol R&D Co Ltd Beijing 100000 Peoples R China

The injection molding process of a mold with multiple cavities can reduce the mold space, but the process is complicated and the product is prone to warpage. In order to reduce the transparent parts warpage of such a mold, by optimizing injection molding process parameters, an optimization technique combining orthogonal experiment, Kriging model and an optimization algorithm is proposed. First, the orthogonal experiment is designed, based on Computer Aided Engineering (CAE) simulation results, while the significant factors affecting the warpage are selected. On this basis, the Kriging model is established to map the nonlinear function relationship between the significant factors and the warpage. Specifically in this paper, four types of correlation functions, affecting the model precision accuracy, are used to establish the Kriging model and the high-precision accuracy model is selected. A numerical optimization algorithm, direct search approach and global exploration method are used to optimize the model, so as to obtain the optimal injection molding parameters producing the minimum warpage. Finally, CAE simulation and experimental validation prove the effectiveness and reliability of the proposed optimization method.

关键词： A mold with multiple cavities Warpage process parameter optimization Kriging model optimization techniques

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