Research on machining error transmission mechanism and compensation method for near-net-shaped jet engine blades CNC machining process

Wu, Dongbo; Wang, Hui; Yu, Jiguo

doi:10.1007/s00170-021-07818-5

Cited by 14 publications

(5 citation statements)

References 21 publications

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“…The machining trajectory error is the shortest distance from the current actual position of the tool to its desired trajectory and is mainly due to the inconsistency between the actual movement value of the tool relative to the workpiece and the command value; it can directly reflect the accuracy of CNC machining [5,6]. In the process of CNC machining, the influence of various factors, such as the accuracy of the machine tool itself [7], the following error generated by the servo system [8], the wear of the cutting tool [9], the deformation of the material [10], and so on, can lead to the generation of machining trajectory errors.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

He,

Zhang,

et al. 2024

Electronics

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Intelligent manufacturing is the main direction of Industry 4.0, pointing towards the future development of manufacturing. The core component of intelligent manufacturing is the computer numerical control (CNC) system. Predicting and compensating for machining trajectory errors by controlling the CNC system’s accuracy is of great significance in enhancing the efficiency, quality, and flexibility of intelligent manufacturing. Traditional machining trajectory error prediction and compensation methods make it challenging to consider the uncertainties that occur during the machining process, and they cannot meet the requirements of intelligent manufacturing with respect to the complexity and accuracy of process parameter optimization. In this paper, we propose a hybrid-model-based machining trajectory error prediction and compensation method to address these issues. Firstly, a digital twin framework for the CNC system, based on a hybrid model, was constructed. The machining trajectory error prediction and compensation mechanisms were then analyzed, and an artificial intelligence (AI) algorithm was used to predict the machining trajectory error. This error was then compensated for via the adaptive compensation method. Finally, the feasibility and effectiveness of the method were verified through specific experiments, and a realization case for this digital-twin-driven machining trajectory error prediction and compensation method was provided.

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Section: Introductionmentioning

confidence: 99%

A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

He,

Zhang,

et al. 2024

Electronics

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“…Therefore, welded parts with low defect rates as well as low distortion can be obtained easily. The material used and manufacturing costs are reduced greatly compared with subtractive techniques, such as machining from buck materials [10,11].…”

Section: Introductionmentioning

confidence: 99%

Experimentation and Numerical Modeling of Peak Temperature in the Weld Joint during Rotary Friction Welding of Dissimilar Plastic Rods

et al. 2023

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Rotary friction welding (RFW) could result in lower welding temperature, energy consumption, or environmental effects as compared with fusion welding processes. RFW is a green manufacturing technology with little environmental pollution in the field of joining methods. Thus, RFW is widely employed to manufacture green products. In general, the welding quality of welded parts, such as tensile strength, bending strength, and surface hardness is affected by the peak temperature in the weld joint during the RFW of dissimilar plastic rods. However, hitherto little is known about the domain knowledge of RFW of acrylonitrile butadiene styrene (ABS) and polycarbonate (PC) polymer rods. To prevent random efforts and energy consumption, a green method to predict the peak temperature in the weld joint of dissimilar RFW of ABS and PC rods was proposed. The main objective of this work is to investigate the peak temperature in the weld joint during the RFW using COMSOL multiphysics software for establishing an empirical technical database of RFW of dissimilar polymer rods under different rotational speeds. The main findings include that the peak temperature affecting the mechanical properties of RFW of PC and ABS can be determined by the simulation model proposed in this work. The average error of predicting the peak temperature using COMSOL software for five different rotational speeds is about 15 °C. The mesh element count of 875,688 is the optimal number of meshes for predicting peak temperature in the weld joint. The bending strength of the welded part (y) using peak welding temperature (x) can be predicted by the equation of y = −0.019 x2 + 5.081x − 200.75 with a correlation coefficient of 0.8857. The average shore A surface hardness, impact energy, and bending strength of the welded parts were found to be increased with increasing the rotational speed of RFW.

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“…Sun et al [21] created the machining error transfer network for the diesel engine body, and improved the prediction accuracy of the body processing quality. Wu et al [22] established the multisource and multiprocess machining error transmission model of a near-net-shaped blade, and qualitatively analyzed the reduction efect of the machining error transmission chain by the adaptive CNC machining process based on the machining error transmission fow model. Most of these methods are based on theoretical research and experimental verifcation, which provides a good foundation for us to revise and condense the research ideas.…”

Section: Introductionmentioning

confidence: 99%

An Analytical Framework for Error Propagation Effects in Multiprocess Manufacturing

2023

Mathematical Problems in Engineering

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Analysis of multisource errors accompanying process execution and study of the propagation effects of the corresponding multiprocess manufacturing process are the basic prerequisites for optimizing the generation process and improving the quality of the product. This paper proposes an analytical framework for error propagation effects in multiprocess manufacturing, which completely covers error source analysis, mathematical calculation of error propagation accumulation, and description of error propagation effects, which can provide better support for error traceability, error propagation monitoring, and error dissipation in manufacturing production. First of all, establish the process state model into the features of the manufacturing level, analyze the type of multisource error, and its mode of action when executing the process operation; second, establish the mathematical calculation model of error propagation accumulation based on state space equation is established, so as to realize calculation and analysis of error propagation; and finally, establish the link graph and link matrix of error propagation influence in multiprocess manufacturing process are established to further reveal the scope and path of error propagation influence. In this section of the case study, a plate cover part had been taken as an example, the multisource error in its manufacturing was analyzed, and the propagation and accumulation of these error values are obtained by state space and state transition theory. On this basis, the link graph and its corresponding link matrix were used to explicitly describe the error propagation effects during the multiprocess manufacturing of the example part. The example analysis illustrated the proposed error analysis framework could analyze and calculate the multisource error of multiprocess manufacturing and visually describe the error propagation effects, which showed the effectiveness and feasibility of the proposed method framework.

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Research on machining error transmission mechanism and compensation method for near-net-shaped jet engine blades CNC machining process

Cited by 14 publications

References 21 publications

A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

Experimentation and Numerical Modeling of Peak Temperature in the Weld Joint during Rotary Friction Welding of Dissimilar Plastic Rods

An Analytical Framework for Error Propagation Effects in Multiprocess Manufacturing

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