Dynamic model identification for CNC machine tool feed drives from in-process signals for virtual process planning

Turhan, Mustafa Hakan; Tseng, Ginette Wei Get; Erkorkmaz, Kaan; Fi̇dan, Barış

doi:10.1016/j.mechatronics.2020.102445

Cited by 8 publications

(7 citation statements)

References 48 publications

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“…The variance (R 2 ), adjusted variance (R 2 -adj), and prediction variance (R 2pre) of the proposed fitting model all exceeded 98%, as shown in Table 4, which indicates that the proposed modeling method demonstrates good prediction accuracy. To facilitate the fitting of the relationships between the process parameters and material removal power, Equation ( 14) was further manipulated into Equation (25). A linear regression approach can be employed to obtain the coefficients for each term.…”

Section: Resultsmentioning

confidence: 99%

“…Apart from the motor output power, permanent magnet synchronous motors also have internal energy losses, which can generally be classified into the following categories: copper loss, iron loss, mechanical loss, additional loss, and electromagnetic loss, as shown in Figure 4. Prior research has indicated that the power loss of a motor can be represented as a quadratic function of the motor's rotational speed, as shown in Equation ( 9) [25]. (9) where k and b are coefficients determined by the motor itself, and Pc represents the fixed power loss.…”

Section: Power Consumption Modeling In Feed and Spindle Subsystemsmentioning

confidence: 99%

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Multi-Objective Optimization of Micro-Milling Parameters—The Trade-Offs between Machining Quality, Efficiency, and Sustainability in the Fabrication of Thin-Walled Microstructures

Wang,

Bai,

Cheng

et al. 2023

Applied Sciences

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Micro-milling has found extensive applications in machining components with thin-walled microstructures, such as terahertz slow-wave structures, microfluidic chips, and micro-molds. Due to the influence of size effects, micro-milling exhibits higher specific energy consumption compared with traditional milling, implying that more energy is consumed to remove a unit volume of material, particularly in challenging-to-machine materials like Ti-6Al-4V. Historically, research on parameter optimization for micro-milling has predominantly focused on enhancing machining quality and efficiency, with limited attention given to energy efficiency. However, in the context of the “double carbon” strategy, energy conservation and emissions reduction have garnered significant attention in the manufacturing industry. Therefore, this paper proposes a micro-milling parameter-based power consumption model. Based on this, a specific energy consumption model can be obtained. Moreover, evolutionary algorithms are utilized for the optimization of micro-milling parameters, which aims to achieve comprehensive enhancements in both machinability and sustainability. The optimization objectives encompass improving surface quality, dimensional accuracy, material removal rate, and specific energy consumption during the micro-milling process for thin-walled micro-structures. Among them, NSGA-III achieves the best optimization results. Under conditions in which cutting energy consumption and processing efficiency are very close, the optimization outcomes based on NSGA-III lead to the best machining quality, including the minimum surface roughness and dimensional errors, and the largest surface fractal dimension. The optimal combination of micro-milling parameters is n = 28,800 rpm, fz = 2.6 μm/t, and ap = 62 μm.

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Section: Resultsmentioning

confidence: 99%

Section: Power Consumption Modeling In Feed and Spindle Subsystemsmentioning

confidence: 99%

Multi-Objective Optimization of Micro-Milling Parameters—The Trade-Offs between Machining Quality, Efficiency, and Sustainability in the Fabrication of Thin-Walled Microstructures

Wang,

Bai,

Cheng

et al. 2023

Applied Sciences

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“…Therefore, AC servo system has been more and more widely used. From the relevant statistical data, it is not difficult to find that there are more than 80% AC servo systems used in the industrial field today [25]. At present, the current loop, speed loop and position loop of three closedloop PID control technology are widely used in the servo system of CNC machine tools.…”

Section: Control Parameter Optimization-based Machining Control Technology Of State-of-the Art Computer Numericalmentioning

confidence: 99%

Control Parameter Optimization-Based Machining Control Technology of State-of-the Art Computer Numerical Control Machine Tools

2021

IJOMAM

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In order to improve the accuracy, reliability and efficiency of computer numerical control (CNC) machine tools, first, according to the working principle of servo motor and related physical relations, the mathematical model of servo system is established. Moreover, the mathematical model is used to establish the three-closed loop simulation structure of servo. Then, according to the simulation structure, a parameter optimization algorithm of CNC machine tool servo system based on improved particle swarm optimization (PSO) algorithm is proposed. Compared with the previous PSO algorithm, the PSO algorithm used has two improvements. First, it introduces the nonlinear dynamic inertia weight coefficient, and constructs the functional relationship between accelerated factor and inertia weight. Second, it introduces the extreme perturbation operator to increase the search range of particles. Moreover, the improved PSO algorithm is used to optimize the scale factor parameters in the regulator. The experimental results show that the dynamic performance of CNC machine tool servo system has been improved to a certain extent. Compared with the Proportion Integration Differentiation (PID) parameters without tuning, the overshoot of the system is reduced and the robustness is improved. In addition, the tuning PID parameters are compared with those of crowd search algorithm (SOA), PSO and genetic algorithm (GA). The results show that the adjustment time to the stable error of the CNC machine tool servo system optimized by GA algorithm is longer than other algorithms, and the oscillation of the transition time is severer. The PID parameters of CNC machine tool servo system optimized by improved PSO algorithm are obviously better than those optimized by other algorithms. The system using this parameter has a short adjustment time and an overshoot of 0. Therefore, the performance of the improved PSO algorithm is better than SOA, PSO and GA algorithm. The proposed algorithm provides a new idea for intelligent algorithm to solve the control parameter optimization problem of CNC machine tools.

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“…The use of sophisticated CAM technology in CNC-based collaborative virtual reality as an alternative to traditional methods of optimization is explored in study [16]. A research report claims that the corrective measures taken on CNC parameters throughout the planning process utilizing virtual technology lead to accurate planning machine tools with accurately improved parameter convergence [17]. The deployment of a virtual laboratory-based teaching and learning procedure for learning CNC programming in Indonesia was not discovered through study in the literature [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Utilizing Virtual Laboratory to Improve CNC Distance Learning of Vocational Students at Higher Education

Prasetya,

Syahri,

Fajri

et al. 2023

TEM Journal

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This research develops learning materials for Computer Numerical Control (CNC) programming courses based on virtual reality technology. The impact of the Covid-19 pandemic on social activities, one of which is the educational aspect, has changed the learning pattern to a massive one where the learning process that should be carried out face-to-face, but now must carry out distance learning. Therefore, alternative learning media is needed to support the practicum process from a distance by utilizing virtual reality technology that is simulated using digital devices. The Software engineering models, namely: requirements, design, implementation, verification, and maintenance phases are the five primary stages used in this study, which uses the waterfall development model research method. The feasible of the virtual laboratory obtained the results of material validation, learning media, and small group trials of 12 diploma students of Mechanical Engineering at Universitas Negeri Padang. The findings of the study found that small group trials in CNC virtual laboratory can be successfully utilized in CNC programming courses. This research is expected to have implications for improving learning outcomes in CNC programming courses by using virtual laboratory technology in creating a conducive and quality learning atmosphere, so that the learning material provided can be accepted by students.

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Dynamic model identification for CNC machine tool feed drives from in-process signals for virtual process planning

Cited by 8 publications

References 48 publications

Multi-Objective Optimization of Micro-Milling Parameters—The Trade-Offs between Machining Quality, Efficiency, and Sustainability in the Fabrication of Thin-Walled Microstructures

Multi-Objective Optimization of Micro-Milling Parameters—The Trade-Offs between Machining Quality, Efficiency, and Sustainability in the Fabrication of Thin-Walled Microstructures

Control Parameter Optimization-Based Machining Control Technology of State-of-the Art Computer Numerical Control Machine Tools

Utilizing Virtual Laboratory to Improve CNC Distance Learning of Vocational Students at Higher Education

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