Constant probe orientation for fast contact-based inspection of 3D free-form surfaces using (3+2)-axis inspection machines

Sliusarenko, Oleksii; Escudero, Gaizka Gómez; Gonzalez, Hernán; Calleja, A.; Bartoň, Michael; Ortega, Naiara; Lacalle, Luis Norberto López de

doi:10.1016/j.precisioneng.2023.06.013

Cited by 11 publications

(2 citation statements)

References 18 publications

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“…This method offers a universal tool geometry and the ability to machine various gear types and sizes within one manufacturing system. Studies have shown that free-form milling enhances the quality and performance of gears by providing higher flexibility and precision [14]. Moreover, the emergence of 5-axis double-flank CNC machining for spiral bevel gears presents new opportunities in flank form design and manufacturing, overcoming kinematic restrictions of traditional methods [15].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Tooth Profile Deviation for WEDM Rigid Gears Based on ISSA-LSSVM

Wang,

Wang

et al. 2024

Applied Sciences

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This study aimed to develop and validate an improved sparrow search algorithm (ISSA)-optimized Least Squares Support Vector Machine (LSSVM) model for accurately predicting the tooth profile deviation of rigid gears produced by wire electrical discharge machining (WEDM). The ISSA was obtained by optimizing the sparrow search algorithm (SSA) using Tent chaotic mapping, adaptive adjustment strategy, dynamic inertia weights, and grey wolf hierarchy strategy. The effectiveness of the ISSA was verified using four different classes of benchmark test functions. Four main process parameters (peak current, pulse width, pulse interval, and tracking) were taken as inputs and the tooth profile deviations of rigid gears were considered as outputs to develop an ISSA-LSSVM-based profile deviation prediction model. The prediction performance of the ISSA-LSSVM model was evaluated by comparing it with the LSSVM model optimized by three standard algorithms. The prediction results of the ISSA-LSSVM model were R2 = 0.9828, RMSE = 0.0029, and MAPE = 0.0156. The results showed that the established model exhibits high prediction accuracy and can provide reliable theoretical guidance for predicting the tooth profile deviation of rigid gears.

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Section: Introductionmentioning

confidence: 99%

Prediction of Tooth Profile Deviation for WEDM Rigid Gears Based on ISSA-LSSVM

Wang,

Wang

et al. 2024

Applied Sciences

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“…In addition to that, the authors also measured the superficial roughness and microstructure and found that positive inserts gave the best results. Sliusarenko et al [ 50 ] suggested a new probe optimization method for (2 + 3)-axis inspection machines by moving the stylus at an inclined angle, by moving the stylus in a globally collision-free state, and by setting the stylus at a constant position. This optimized method compared the 3-axis and 5-axis optimization strategies and found that optimization results obtained by setting the stylus at a constant position were accurate compared to the results of the 3-axis and 5-axis approaches.…”

Section: Introductionmentioning

confidence: 99%

Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach

Ishfaq,

Sana,

Waseem

et al. 2023

Micromachines

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The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 μm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC’s nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments.

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Freeform surface profiling by iterative learning-extremum seeking control

Nguyen,

Lee

2024

Int J Adv Manuf Technol

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Constant probe orientation for fast contact-based inspection of 3D free-form surfaces using (3+2)-axis inspection machines

Cited by 11 publications

References 18 publications

Prediction of Tooth Profile Deviation for WEDM Rigid Gears Based on ISSA-LSSVM

Prediction of Tooth Profile Deviation for WEDM Rigid Gears Based on ISSA-LSSVM

Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach

Freeform surface profiling by iterative learning-extremum seeking control

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