Finite Element Analysis of Machining Thin-Wall Parts: Error Prediction and Stability Analysis

Huang, Yu-Jung; Zhang, Xiaoming; Xiong, Yan

doi:10.5772/50374

Cited by 12 publications

(10 citation statements)

References 50 publications

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“…Ivester and Danai [29] have suggested the adaptive control optimization, where the machine settings are adjusted according to the cutting process reaction and in a manner to compensate inaccuracies in the milling of thin walls. Huang et al [30] have used the finite element analysis to predict the error due to the tool deflection and system instability by a thermo-mechanical model, and thanks to min-max method, they have realized a robust optimization of cutting parameters.…”

Section: Previous Work Relating To Robust Optimizationmentioning

confidence: 99%

Efficient genetic algorithm for multi-objective robust optimization of machining parameters with taking into account uncertainties

Sahali

Belaidi²,

Serra³

2014

Int J Adv Manuf Technol

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The respect of the machined piece quality and productivity is closely related to the mastery of uncertain factors. Indeed, the efficient solutions obtained from the machining parameter optimization based on classical methods are assigned of uncertain deviations which affect the cutting process. In the present paper, we propose multi-and monoobjective optimization approach of parameter turning with taking into account both production constraints related to piece quality, to machine power, or to tool life, than uncertainty factors related to the tool wear and to piece geometry defaults. To this end, we developed and implemented an efficient genetic algorithm, based on an evaluation mechanism of "objective" functions, which integrate the Monte Carlo simulations to calculate the robustness of objective function and different constraints. Our approach has been validated by two applications implemented with Matlab™ for the minimization of cost and machining time, which has allowed obtaining simultaneously efficient and robust results and offering the possibility to choose beforehand a compromise between efficiency and robustness of solutions.

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Section: Previous Work Relating To Robust Optimizationmentioning

confidence: 99%

Efficient genetic algorithm for multi-objective robust optimization of machining parameters with taking into account uncertainties

Sahali

Belaidi²,

Serra³

2014

Int J Adv Manuf Technol

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“…The workpiece deflects to a new position due to cutting forces and cutting temperatures which creates dimensional error and inaccuracy in process of machining operations. The surface dimensional error due to the cutting forces and cutting temperature is shown in the figure 5 [26]. Fig.…”

Section: -Deflection Error Analysis Of Thin-wall Workpiece In Machinmentioning

confidence: 99%

Deflection Error Prediction and Minimization in 5-Axis Milling Operations of Thin-Walled Impeller Blades

Soori

Asmael

2020

Preprint

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To enhance accuracy as well as efficiency in process of machining operations, the virtual machining systems are developed. Free from surfaces of sophisticated parts such as turbine blades, airfoils, impellers, and aircraft components are produced by using the 5-axis CNC machine tools which can be analyzed and developed by using virtual machining systems. The machining operations of thin walled structures such as impeller blades are with deflection errors due to cutting forces and cutting temperatures. The flexibility of thin walled impeller blades can cause machining defects such as overcut or undercut. So, the desired accuracy in the machined impeller blades can be achieved by decreasing the deflection error in the machining operations. To minimize the deflection of machined impeller blades, optimized machining parameters can be obtained. An application of virtual machining system in predicting and minimizing the deflection errors of 5-Axis CNC machining operations of impeller blades is presented in the study to increase accuracy and efficiency in process of part production. The finite element analysis is applied to obtain the deflection error in machined impeller blades. In order to minimize the deflection error of impeller blades in the machining operations, the optimization methodology based on the Genetic algorithm is applied. The impeller is machined by using the 5-axis CNC machine tool in order to validate the developed virtual machining system in the study. Then, the machined impeller is measured by using the CMM machines to obtain the deflection error. As a result, the deflection error of in machining operations of impeller by using 5-Axis CNC machine tools can be decreased in order to enhance accuracy and efficiency of part manufacturing.

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“…Dari hasil penelitian yang dilakukan oleh Huang, dkk menunjukkan bahwa proses permesinan pada thin wall biasanya memiliki sifat low rigidity pada saat proses proses permesinan berlangsung dan gaya potong serta suhu pemotongan juga dapat menyebabkan terjadinya defleksi [8,9]. Kondisi ini tentunya sangat merugikan karena dapat mengakibatkan permasalahan pada keakuratan dimensi dan surface integrity pada benda kerja yang dihasilkan.…”

Section: Gambar 2 Benda Kerja Setelah Proses Facingunclassified

Pengaruh Proses Pembubutan Muka (Facing) pada Arah Forward dan Backward Terhadap Besarnya Defleksi yang Terjadi serta Daya Permesinan yang Dibutuhkan

Rusnaldy¹,

Tauviqirrahman²,

Prasetyo³

2018

Rot.

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Makalah ini membahas tentang pengaruh proses facing terhadap besarnya defleksi yang terjadi pada benda kerja terutama pada bagian facenya yang dikurangi ketebalannya dari 5 mm hingga 0,3 mm. Proses facing yang digunakan disamping menggunakan pergerakan pahat pada arah forward juga digunakan pergerakan pahat pada arah backward. Disamping itu besarnya daya permesinan yang digunakan juga diukur untuk melihat tingkat keekonomisan proses facing pada arah forward dan backward. Parameter proses permesinan yang digunakan adalah putaran spindel sebesar 500 rpm, feeding sebesar 0,4 mm/rev, depth of cut sebesar 1 mm dan kondisi permesinan tanpa menggunakan cairan coolant. Dari hasil eksperimen diperoleh bahwa proses facing pada arah forward menghasilkan defleksi yang lebih rendah dibanding proses facing pada arah backward. Semakin tipis bagian face pada benda kerja yang dihasilkan semakin besar defleksi yang terjadi. Namun, facing pada arah forward ternyata membutuhkan daya permesinan yang lebih besar dibanding pada arah backward.

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Finite Element Analysis of Machining Thin-Wall Parts: Error Prediction and Stability Analysis

Cited by 12 publications

References 50 publications

Efficient genetic algorithm for multi-objective robust optimization of machining parameters with taking into account uncertainties

Efficient genetic algorithm for multi-objective robust optimization of machining parameters with taking into account uncertainties

Deflection Error Prediction and Minimization in 5-Axis Milling Operations of Thin-Walled Impeller Blades

Pengaruh Proses Pembubutan Muka (Facing) pada Arah Forward dan Backward Terhadap Besarnya Defleksi yang Terjadi serta Daya Permesinan yang Dibutuhkan

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