Surface Roughness Evolution Model for Finishing Using an Abrasive Tool on a Robot

Fernández, Jesús J.; Antonio, Dieste Jose; Javierre, Carlos; Santolaria, Jorge

doi:10.5772/61251

Cited by 12 publications

(7 citation statements)

References 28 publications

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“…Pilny and Bissacco [10] presented the development of a monitoring and control strategy for automatic detection of the process end point, as well as machine total surface characterization and local defect identification. Fernandez et al [11] focussed on the feasibility of robotic polishing and the development of an evolutionary model pertaining to surface roughness for an abrasive tool mounted on a spherical robot, and obtained a final roughness with less than 15% deviation.…”

Section: A Robotic Belt Grinding For Aero-engine Bladementioning

confidence: 99%

Two-Level Static Floatation Tool Used in Belt Grinding for Root Fillet of Titanium Alloy Blade

Xiao

Huang

2019

IEEE Access

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The root fillet of key components in aero-engines, such as the blade, blisk, and blade ring, is the most stress-concentrated area during thermodynamic interactions. The root fillet is constructed with a small curvature radius and variable curvature in different sections. Variable curvature is difficult to achieve with the integrated heat in the grinding process, and the surface quality of the root fillet is therefore greatly influenced. A ''horseshoe nest'' may be created in the high-temperature air environment, which would significantly affect the fatigue life of the key components. Therefore, to solve the problem of precision grinding for a variablecurvature root fillet, a two-level static floatation tool is proposed for belt grinding. First, the system design of the two-level static floatation tool is introduced, and the principle of the two-level static air floating is analyzed based on fluid dynamics. Second, the deformation and stress distribution of the two-level static floatation tool is analyzed when combined with the belt grinding process for a variable-curvature root fillet. Finally, an experiment performed on the root fillet of an aero-engine titanium alloy blade is described. The results show that the surface roughness is less than 0.4 µm, the profile precision errors are less than 5%, the transition is smooth between the plane and the fillet (blade surface to root fillet rabbet), and a longitudinal texture on the blade root fillet is formed. INDEX TERMS Belt grinding, tool, blade, root fillet, surface integrity.

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Section: A Robotic Belt Grinding For Aero-engine Bladementioning

confidence: 99%

Two-Level Static Floatation Tool Used in Belt Grinding for Root Fillet of Titanium Alloy Blade

Xiao

Huang

2019

IEEE Access

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“…Then, the emergence of Computer Numerical Control machines opened up the possibility of processing more complex parts, and several solutions were commercialized. However, CNC machines have very expensive and rigid systems, making industrial robotics a key technology for the automation of finishing processes, as robots are the most flexible and reconfigurable manufacturing systems [3].…”

Section: Introductionmentioning

confidence: 99%

Robotic Belt Finishing with Process Control for Accurate Surfaces

Torres

Mata

Iriarte

et al. 2023

JMMP

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The aerospace industry still relies on manual processes for finish applications, which can be a tedious task. In recent years, robotic automation has gained interest due to its flexibility and adaptability to provide solutions to this issue. However, these processes are difficult to automate, as the material removal rate can vary due to changes in the process variables. This work proposes an approach for automatically modeling the material removal process based on experimental data in a robotic belt grinding application. The methodology concerns the measurement of the removed mass of a test part during a finishing process using an automatic precision measurement system. Then, experimental models are used to develop a control algorithm for continuous material removal that maintains a uniform finishing process by regulating the robot’s feed rate. Next, the results for various experimental material removal models under different process conditions are presented, showing the process parameter’s influence on the removal capacity. Finally, the proposed control algorithm is validated, achieving a constant material removal rate.

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“…However, it is necessary to know the whole geometry of the part and to have a computer-aided design and manufacturing software to generate the right trajectory. It is also necessary to use a tool that absorbs vibrations due to the contact force [ 11 ]. Another example can be found in [ 12 ], where researchers develop a specific end effector for grinding applications.…”

Section: Introductionmentioning

confidence: 99%

“…

where

is the contact pressure,

is the feed rate of the tool, and

is the Preston coefficient, which is determined experimentally and depends on the material, abrasive, and lubrication, among other factors [ 20 ]. However, other works provide more complex mathematical models that allow obtaining of the minimum number of passes and the characteristics of the abrasive material that should be used to obtain the desired roughness [ 11 , 21 ]. An experimental investigation was developed in [ 22 ], from which the parameters that affect the surface quality in an industrial robot (no collaborative) polishing could be obtained.…”

Section: Introductionmentioning

confidence: 99%

Behavioural Study of the Force Control Loop Used in a Collaborative Robot for Sanding Materials

et al. 2020

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The rise of collaborative robots urges the consideration of them for different industrial tasks such as sanding. In this context, the purpose of this article is to demonstrate the feasibility of using collaborative robots in processing operations, such as orbital sanding. For the demonstration, the tools and working conditions have been adjusted to the capacity of the robot. Materials with different characteristics have been selected, such as aluminium, steel, brass, wood, and plastic. An inner/outer control loop strategy has been used, complementing the robot’s motion control with an outer force control loop. After carrying out an explanatory design of experiments, it was observed that it is possible to perform the operation in all materials, without destabilising the control, with a mean force error of 0.32%. Compared with industrial robots, collaborative ones can perform the same sanding task with similar results. An important outcome is that unlike what might be thought, an increase in the applied force does not guarantee a better finish. In fact, an increase in the feed rate does not produce significant variation in the finish—less than 0.02 µm; therefore, the process is in a “saturation state” and it is possible to increase the feed rate to increase productivity.

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Surface Roughness Evolution Model for Finishing Using an Abrasive Tool on a Robot

Cited by 12 publications

References 28 publications

Two-Level Static Floatation Tool Used in Belt Grinding for Root Fillet of Titanium Alloy Blade

Two-Level Static Floatation Tool Used in Belt Grinding for Root Fillet of Titanium Alloy Blade

Robotic Belt Finishing with Process Control for Accurate Surfaces

Behavioural Study of the Force Control Loop Used in a Collaborative Robot for Sanding Materials

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