Simulation and Evaluation of Different Process Strategies in a 5-axis Re-contouring Process

Denkena, Berend; Böß, Volker; Nespor, D.; Rust, Felix

doi:10.1016/j.procir.2015.08.059

Cited by 10 publications

(1 citation statement)

References 25 publications

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“…Tunç et al (2015) proposed a simulation-based machining strategy development and parameter selection approach based on dynamic programming, and verified the simulation results through the experimental cases including 5-axis milling of an integrally bladed rotor. Denkenaa et al (2015) showed how workpiece quality of re-contouring blades evolves through different 5-axis process strategies, including the ball end milling of the weld in one step, follow the contour of the weld by using sequential cuts, roughing with end mill and finishing with ball end milling. Chen et al (2017) introduced the online cutting process monitoring and optimization in jet engine Ni-based superalloy impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring as examples of intelligent machining.…”

Section: Introductionmentioning

confidence: 99%

Influence of milling toolpaths in machining of the turbine blade

Jarolmasjed

Davoodi

Alamdari

2019

AEAT

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Purpose The purpose of this paper is to machine the pressure surface of the turbine blade made of A286 iron-based superalloy by using four directions of raster strategy, including horizontal upward, horizontal downward, vertical upward and vertical downward, to achieve appropriate surface roughness and to investigate the tool wear in each strategy. Design/methodology/approach In this study, all cutting tests were performed by DAHLIH-MCV 1020 BA vertical 3-axis machining center with ball nose end mill. After milling by each strategy, according to the surface slope, the surface was divided into 27 meshes, and roughness of surface was studied and compared. Roughness measuring after machining was implemented by using portable Mahr ps1 roughness tester, and surface texture was photographed by CCD 100× optical zoom camera. Also, to measure tool flank wear in each strategy as an indication of tool life, the surface of workpiece was divided into four equal areas. The wear of the inserts was measured by ARCS vertical non-contact measuring system at the end of each area. Findings The results indicate that cutting directions and toolpath strategies have significant influence on tool wear and surface roughness in machining processes and that they can be taken into consideration individually as determinative parameters. In this case, the most uniform surface texture and the lowest surface roughness are obtained by using horizontal downward direction; in addition, abrasion is a dominant tool wear mechanism in all experiments, and tool wear in the horizontal downward is lower than other strategies. Practical implications Machining of turbine blades or other airfoil-shaped workpieces is quite common in manufacturing aerospace and aircraft products. The results of this research contribute to increasing quality of machined surface and tool life in machining of turbine blade. Originality/value This work proves the significance of milling strategies in machining of the turbine blade made of A286 superalloy and, consequently, exhibits the proper strategy in terms of surface roughness and tool life. Also, this work explains and elaborates the behavior of A286 superalloy in machining processes, which has not been studied much in recent research works.

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Section: Introductionmentioning

confidence: 99%

Influence of milling toolpaths in machining of the turbine blade

Jarolmasjed

Davoodi

Alamdari

2019

AEAT

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GPU accelerated voxel-based machining simulation

Schnös

Hartmann

Obst

et al. 2021

Int J Adv Manuf Technol

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The simulation of subtractive manufacturing processes has a long history in engineering. Corresponding predictions are utilized for planning, validation and optimization, e.g., of CNC-machining processes. With the up-rise of flexible robotic machining and the advancements of computational and algorithmic capability, the simulation of the coupled machine-process behaviour for complex machining processes and large workpieces is within reach. These simulations require fast material removal predictions and analysis with high spatial resolution for multi-axis operations. Within this contribution, we propose to leverage voxel-based concepts introduced in the computer graphics industry to accelerate material removal simulations. Corresponding schemes are well suited for massive parallelization. By leveraging the computational power offered by modern graphics hardware, the computational performance of high spatial accuracy volumetric voxel-based algorithms is further improved. They now allow for very fast and accurate volume removal simulation and analysis of machining processes. Within this paper, a detailed description of the data structures and algorithms is provided along a detailed benchmark for common machining operations.

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