Accuracy analysis of tool deflection error modelling in prediction of milled surfaces by a virtual machining system

Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

doi:10.1504/ijcat.2017.10006843

Cited by 4 publications

(1 citation statement)

References 31 publications

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“…The blisk vibration in aircraft engine using similitude models is analysed by Luo et al [19] to predict and decrease the vibration of the engine systems in the virtual environments. To analyse and modify the machining operations in virtual environments, virtual machining systems and applications are presented by Soori et al [20] to [24]. To analyse and develop the process of part manufacturing using welding operations, a review in recent development of friction stir welding process is presented by Soori et al [25].…”

Section: Introductionmentioning

confidence: 99%

Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades

Soori

Asmael

2021

SV-JME

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To simulate and analyse the real machined parts in virtual environments, virtual machining systems are applied to the production processes. Due to friction, chip forming, and the heat produced in the cutting zone, parts produced using machining operation have residual stress effects. The machining force and machining temperature can cause the deflection error in the machined turbine blades, which should be minimized to increase the accuracy of machined blades. To minimize the residual stress and deflection error of machined parts, optimized machining parameters can be obtained. In the present research work, the application of a virtual machining system is presented to predict and minimize the residual stress and deflection error in a five-axis milling operations of turbine blades. In order to predict the residual stress and deflection error in machined turbine blades, finite element analysis is implemented. Moreover, to minimize the residual stress and deflection error in machined turbine blades, optimized parameters of machining operations are obtained by using a genetic algorithm. To validate the research work, experimentally determining residual stress by using a X-ray diffraction method from the machined turbine blades is compared with the finite element results obtained from the virtual machining system. Also, in order to obtain the deflection error, the machined blades are measured by using the CMM machines. Thus, the accuracy and reliability of machined turbine blades can be increased by analysing and minimizing the residual stress and deflection error in virtual environments.

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Section: Introductionmentioning

confidence: 99%

Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades

Soori

Asmael

2021

SV-JME

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A Voxel-Based End Milling Simulation Method to Analyze the Elastic Deformation of a Workpiece

Kaneko

Shimizu

Shirase

2022

Journal of Manufacturing Science and Engineering

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A new method to analyze the elastic deformation of a workpiece during end milling is proposed. With this method, the workpiece is discretely represented by voxels connected to their neighboring voxels with beam elements. The stiffness matrix for the workpiece is calculated based on the element stiffness matrix for the beam elements and voxel connectivity. Although the finite element method (FEM) is generally used for deformation analysis, it requires substantial time to analyze the workpiece deformation that occurs in the end milling process since it is necessary to re-mesh the workpiece model and update the stiffness matrix due to frequent changes in the workpiece shape. In contrast, the proposed method does not require remeshing, as the workpiece shape change is represented by removing voxels, and the stiffness matrix can be easily updated from the stiffness matrix obtained before the shape change. The proposed method was integrated into a cutting force simulator in order to analyze the workpiece deformation caused by end milling. The results of a verification experiment showed that the analyzed workpiece deformation was in rough agreement with the measured deformation.

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Classification of research and applications of the computer aided process planning in manufacturing systems

Soori

Asmael

2021

Ind. Jour. Manag. & Prod.

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The Computer Aided Process Planning (CAPP) systems are recently developed in manufacturing engineering to provide links between Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) systems. The CAPP systems are developed by considering the different issues of computer applications in production engineering. Optimization techniques can be applied to the CAPP to increase efficiency in part production processes. The energy consumption of part production process can be analyzed and optimized using the CAPP systems in order to increase added value in the part manufacturing process. Also, artificial neural networks as well as cloud manufacturing systems can be applied to the CAPP systems to share advantages of the different CAPP systems in different industry applications. Flexible process planning systems are developed using dynamic CAPP in order to cope with product varieties in process of part production. To develop potential energy saving strategies during product design and process planning stages, the advanced CAPP systems can be used. In this paper, a review of Computer Process Planning systems (CAPP) is presented and future research works are also suggested. It has been observed that the research filed can be moved forward by reviewing and analyzing recent achievements in the published papers.

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Accuracy analysis of tool deflection error modelling in prediction of milled surfaces by a virtual machining system

Cited by 4 publications

References 31 publications

Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades

Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades

A Voxel-Based End Milling Simulation Method to Analyze the Elastic Deformation of a Workpiece

Classification of research and applications of the computer aided process planning in manufacturing systems

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