Optimization of pre-polishing parameters on a 5-axis milling machine

Moumen, Mourad; Chaves‐Jacob, Julien; Bouaziz, Mohamed; Linares, Jean‐Marc

doi:10.1007/s00170-015-7944-y

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…For example, Matellan et al use acetone vapor treatment to smooth the PMMA surface as a cost-effective rapid prototyping method [35] to generate the microfluidic device; or they use cryogenic cooling to polish the acrylic-based polymer for optical lens application [36]. In addition to these approaches, abrasive polishing tools are commonly used to polish plastic parts in large scale [37,38]. This method can also be applied in microfluidics application, e.g., Szymborski et al use polishing paste and felt to polish the Teflon bioreactor [39].…”

Section: Introductionmentioning

confidence: 99%

Polymer Microchannel and Micromold Surface Polishing for Rapid, Low-Quantity Polydimethylsiloxane and Thermoplastic Microfluidic Device Fabrication

Tsao

2020

Polymers

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Polymer-based micromolding has been proposed as an alternative to SU-8 micromolding for microfluidic chip fabrication. However, surface defects such as milling marks may result in rough microchannels and micromolds, limiting microfluidic device performance. Therefore, we use chemical and mechanical methods for polishing polymer microchannels and micromolds. In addition, we evaluated their performance in terms of removing the machining (milling) marks on polymer microchannel and micromold surfaces. For chemical polishing, we use solvent evaporation to polish the sample surfaces. For mechanical polishing, wool felt polishing bits with an abrasive agent were employed to polish the sample surfaces. Chemical polishing reduced surface roughness from 0.38 μm (0 min, after milling) to 0.13 μm after 6 min of evaporation time. Mechanical polishing reduced surface roughness from 0.38 to 0.165 μm (optimal pressing length: 0.3 mm). As polishing causes abrasion, we evaluated sample geometry loss after polishing. Mechanically and chemically polished micromolds had optimal micromold distortion percentages of 1.01% ± 0.76% and 1.10% ± 0.80%, respectively. Compared to chemical polishing, mechanical polishing could better maintain the geometric integrity since it is locally polished by computer numerical control (CNC) miller. Using these surface polishing methods with optimized parameters, polymer micromolds and microchannels can be rapidly produced for polydimethylsiloxane (PDMS) casting and thermoplastic hot embossing. In addition, low-quantity (15 times) polymer microchannel replication is demonstrated in this paper.

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Section: Introductionmentioning

confidence: 99%

Polymer Microchannel and Micromold Surface Polishing for Rapid, Low-Quantity Polydimethylsiloxane and Thermoplastic Microfluidic Device Fabrication

Tsao

2020

Polymers

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“…With the continuous development of advanced optical technology, the development direction of optical components is ultra-precision, large-diameter and complex surfaces [1]. Traditional hand polishing technology is expensive, time consuming and difficult to guarantee the polishing quality [2], which has been difficult to meet the manufacturing needs of optical components. Therefore, it is necessary to design and develop efficient, stable and low-cost polishing technology.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of Removal Function for Dual-axis Wheel Polishing

Chen

Peng²,

Lai³

et al. 2023

J. Phys.: Conf. Ser.

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Modern optical manufacturing techniques, such as stress disc polishing, bonnet polishing, magnetorheological finishing, and ion beam finishing, suffer from edge effects or low removal efficiency. To solve the above problems, this paper mainly studies dual-axis wheel polishing technology. According to the Preston equation combined with Hertz contact theory and kinematics, a theoretical removal function model of dual-axis wheel polishing is established. Then, the removal function shape and removal efficiency under different revolution-to-rotation speed ratios are simulated. From the simulation results, it can be concluded that the removal function of the dual-axis wheel polishing technology in this paper is Gauss type when the revolution-to-rotation speed ratio is 10:1 or less. With the increase of rotation ratio, the efficiency of the removal function is higher. This paper establishes a theoretical foundation for the design of the dual-axis wheel polishing device.

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“…This method has low processing efficiency and high processing cost. The contact pressure between the polishing tool and the contact surface needs to be measured using a pressure sensor, since the conventional polishing tool is inelastic [6,7]. Compared with the free abrasive particle polishing process, the fixed abrasive polishing process has a large number of abrasive grains [8].…”

Section: Introductionmentioning

confidence: 99%

Mechanism and Parameter Optimization in Grinding and Polishing of M300 Steel by an Elastic Abrasive

Tong

Zhang

et al. 2019

Materials

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In order to achieve high quality polishing of a M300 mold steel curved surface, an elastic abrasive is introduced in this paper and its polishing parameters are optimized so that the mirror roughness can be achieved. Based on the Preston equation and Hertz Contact Theory, the theoretical material removal rate (MRR) equation for surface polishing of elastic abrasives is obtained. The effects of process parameters on MRR are analyzed and the polishing parameters to be optimized are as follows: particle size (S), rotational speed (Wt), cutting depth (Ap) and feed speed (Vf). The Taguchi method is applied to design the orthogonal experiment with four factors and three levels. The influence degree of various factors on the roughness of the polished surface and the combination of parameters to be optimized were obtained by the signal-to-noise ratio method. The particle swarm optimization algorithm optimized with the back propagation (BP) neural network algorithm (PSO-BP) is used to optimize the polishing parameters. The results show that the rotational speed has the greatest influence on the roughness, the influence degree of abrasive particle size is greater than that of feed speed, and cutting depth has the least influence. The optimum parameters are as follows: particle size (S) = #1200, rotational speed (Wt) = 4500 rpm, cutting depth (Ap) = 0.25 mm and feed speed (Vf) = 0.8 mm/min. The roughness of the surface polishing with optimum parameters is reduced to 0.021 μm.

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Optimization of pre-polishing parameters on a 5-axis milling machine

Cited by 8 publications

References 19 publications

Polymer Microchannel and Micromold Surface Polishing for Rapid, Low-Quantity Polydimethylsiloxane and Thermoplastic Microfluidic Device Fabrication

Polymer Microchannel and Micromold Surface Polishing for Rapid, Low-Quantity Polydimethylsiloxane and Thermoplastic Microfluidic Device Fabrication

Modeling and Simulation of Removal Function for Dual-axis Wheel Polishing

Mechanism and Parameter Optimization in Grinding and Polishing of M300 Steel by an Elastic Abrasive

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