Modeling and Simulation of Material Removal Rates and Profile Accuracy Control in Abrasive Flow Machining of the Integrally Bladed Rotor Blade and Experimental Perspectives

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Kai Cheng ◽  
Yizhi Shao ◽  
Rodrigo Bodenhorst ◽  
Mitul Jadva
Keyword(s):  
Dimensional Accuracy ◽  
Accuracy Control ◽  
Abrasive Flow Machining ◽  
Virtual Machining ◽  
Computational Environment ◽  
Component Form ◽  
Simulation Based ◽  
Machining System ◽  
Bladed Rotor ◽  
Profile Accuracy

Abrasive flow machining (AFM) technology is getting more and more interest by the industry and research community particularly in the context of increasing demands for postprocessing of the additively manufactured and complex components. It is essentially important to develop an industrial feasible approach to controlling and improving the profile accuracy (form and dimensional) of components as well as their surface roughness. In this paper, a multiscale multiphysics simulation-based approach is presented to model and simulate the AFM process against the component form and dimensional accuracy control in particular. The simulation is developed in comsol which is a multiphysics computational environment. Well-designed AFM experiment trials are carried out on a purposely configured blade “coupon” to further evaluate and validate the simulations. The AFM machine and specific machining media for the experiments are provided by the industrial collaboration company, with their further industrial inputs. Both the simulation and experimental trial results illustrate that the approach is applicable to the blade profile prediction and accuracy control, which is used as a foundation for developing the simulation-based AFM virtual machining system.

Tool Deflection Error of Three-Axis Computer Numerical Control Milling Machines, Monitoring and Minimizing by a Virtual Machining System

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Mohsen Soori ◽  
Behrooz Arezoo ◽  
Mohsen Habibi
Keyword(s):  
Manufacturing Systems ◽  
Optimization Technique ◽  
Dimensional Accuracy ◽  
Virtual Manufacturing ◽  
Numerical Control ◽  
Free Form ◽  
Machining Parameters ◽  
Tool Deflection ◽  
Virtual Machining ◽  
Machining System

Virtual manufacturing systems carry out the simulation of manufacturing processes in digital environment in order to increase accuracy as well as productivity in part production. There are different error sources in machine tools, such as tool deflection, geometrical deviations of moving axis, and thermal distortions of machine tool structures. The errors due to tool deflection are caused by cutting forces and have direct effects on dimensional accuracy, surface roughness of the parts, and efficient life of the cutting tool, holder, and spindle. This paper presents an application of virtual machining systems in order to improve the accuracy and productivity of part manufacturing by monitoring and minimizing the tool deflection error. The tool deflection error along machining paths is monitored to present a useful methodology in controlling the produced parts with regard to desired tolerances. Suitable tool and spindle can also be selected due to the ability of error monitoring. In order to minimize the error, optimization technique based on genetic algorithms is used to determine optimized machining parameters. Free-form profile of virtual and real machined parts with tool deflection error is compared in order to validate reliability as well as accuracy of the software.

Study on the Propagation of Dimensional Deviation in the Hull Block Building Process

2020 ◽  
Vol 36 (02) ◽  
pp. 143-151
Author(s):  
Changhui Liu ◽  
Jianfeng Liu ◽  
Yansong Zhang ◽  
Sun Jin ◽  
Can Wang ◽  
...  
Keyword(s):  
Critical Role ◽  
Dimensional Accuracy ◽  
Butt Joint ◽  
Measured Data ◽  
Accuracy Control ◽  
Bottom Block ◽  
Whole Process ◽  
Building Process ◽  
Dimensional Deviation ◽  
Industry Practice

Dimensional accuracy of hull block plays a critical role in guaranteeing the whole ship accuracy and reducing the hull butt-joint cost. The current industry practice of dimensional control in shipbuilding mainly focuses on the prediction of cutting and welding deformation based on engineering experience. Its main limitation is that the propagation and accumulation of deviations in the whole building process are neglected. In this article, cutting errors, assembly deviations, welding shrinkages, turnover distortions, and thermal expansions generated at different stages are analyzed. The propagation and accumulation of deviations and variations in the double-bottom block building process are studied based on the measured data in the whole process. Finally, the correlations of deviations between the adjacent stage are concluded. The conclusions can be used to guide the accuracy control in the hull block building process and reduce dimension trimming.

scholarly journals Virtual machining system simulator: analysis of machine tool accuracy

2018 ◽  
Vol 25 ◽  
pp. 338-343 ◽  
Author(s):  
Nikolas Theissen ◽  
Theodoros Laspas ◽  
Károly Szipka ◽  
Andreas Archenti
Keyword(s):  
Machine Tool ◽  
Virtual Machining ◽  
Machine Tool Accuracy ◽  
Machining System

scholarly journals Development of smart machining system for optimizing feedrates to minimize machining time

2017 ◽  
Vol 5 (3) ◽  
pp. 299-304 ◽  
Author(s):  
Hong-seok Park ◽  
Bowen Qi ◽  
Duck-Viet Dang ◽  
Dae Yu Park
Keyword(s):  
Cutting Force ◽  
Machining Process ◽  
Cnc Machine ◽  
Machining Time ◽  
Virtual Machining ◽  
Milling Operations ◽  
Nc Program ◽  
Machining System ◽  
Optimal Feed ◽  
Smart Machining

Abstract Feedrate optimization is an important aspect of getting shorter machining time and increase the potential of efficient machining. This paper presents an autonomous machining system and optimization strategies to predict and improve the performance of milling operations. The machining process was simulated and analyzed in virtual machining framework to extract cutter-workpiece engagement conditions. Cutting force along the cutting segmentation is evaluated based on the laws of mechanics of milling. In simulation, constraint-based optimization scheme was used to maximize the cutting force by calculating acceptable feedrate levels as the optimizing strategy. The intelligent algorithm was integrated into autonomous machining system to modify NC program to accommodate these new feedrates values. The experiment using optimized NC file which generates by our smart machining system were conducted. The result showed autonomous machining system, was effectively reduced 26%. Highlights The smart machining system was implemented in the CNC machine. Optimal feed rates enhance machine tool efficiency. The smart machining system is reliable to reduce machine time.

VIRTUAL MACHINING SYSTEM ENGINE FOR SIMULATION OF THE PROCESS MACHINE INTERACTION

2012 ◽  
Vol 2012 (01) ◽  
pp. 310-314
Author(s):  
Andreas Archenti ◽  
Mihai Nicolescu ◽  
Thomas Lundholm
Keyword(s):  
Virtual Machining ◽  
Machining System ◽  
Machine Interaction ◽  
Process Machine Interaction

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

2021 ◽  
Vol 67 (5) ◽  
pp. 235-244
Author(s):  
Mohsen Soori ◽  
Mohammed Asmael
Keyword(s):  
Residual Stress ◽  
Finite Element ◽  
Virtual Environments ◽  
Turbine Blades ◽  
Research Work ◽  
Machining Parameters ◽  
Virtual Machining ◽  
Machined Parts ◽  
Machining System ◽  
Five Axis

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.

scholarly journals Surface Roughness Prediction and Minimization in 5-Axis Milling Operations of Gas Turbine Blades

2021 ◽  
Author(s):  
Arameh Eyvazian ◽  
Farayi Musharavati ◽  
Afrasyab Khan ◽  
Mohsen Soori ◽  
Tamer A. Sebaey ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Gas Turbine ◽  
Turbine Blades ◽  
Machining Process ◽  
Machining Parameters ◽  
Gas Turbine Blades ◽  
Virtual Machining ◽  
Machined Parts ◽  
Machining System

Abstract To enhance the quality of machined parts, virtual machining systems are presented in this study. In the turbine blades, the minimization of the surface roughness of the blades can decrease the Reynolds number to decrease the loss of energy in power generation. Due to difficulties of polishing process in minimizing the surface roughness of machined blades, the optimized machining parameters for minimizing the surface roughness is an effective solution for the problem. In this study, a virtual machining system is developed to predict and minimize the surface roughness in 5-Axis machining operations of gas turbine blades. To minimize the surface roughness, the machining parameters were optimized by the Genetic algorithm. To validate the developed system, the turbine blades were machined using a 5-Axis CNC machine tool and the machined blades were measured using the CMM machine to obtain the surface roughness of machined parts. So, a 41.29% reduction in the measured surface roughness and a 42.09% reduction in the predicted surface roughness are obtained using the optimized machining parameters. The developed virtual machining system can be applied in the machining process of turbine blades to enhance the surface quality of machined blades and thus improve the efficiency of gas turbines.

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