Improvement on the surface roughness of microlens array in the excimer laser machining process

2001 ◽  
Author(s):  
Shuh-Yi Wang ◽  
Chi-Sheng Huang ◽  
Hsau-Yu Chou ◽  
Tone-Yen Lee ◽  
Rang-Seng Chang
Keyword(s):  
Surface Roughness ◽  
Excimer Laser ◽  
Microlens Array ◽  
Machining Process ◽  
Laser Machining

Spherical and Aspheric Microlenses Fabricated by Excimer Laser LIGA-like Process

2006 ◽  
Vol 129 (1) ◽  
pp. 126-134 ◽  
Author(s):  
Yung-Chun Lee ◽  
Chun-Ming Chen ◽  
Chun-Ying Wu
Keyword(s):  
Surface Roughness ◽  
Excimer Laser ◽  
Focal Length ◽  
Surface Profile ◽  
Polymer Materials ◽  
Laser Machining ◽  
Scanning Method ◽  
Average Surface ◽  
Direct Laser ◽  
Profile Accuracy

This paper presents an effective and low-cost method for fabricating spherical and aspheric microlenses based on excimer laser LIGA-like processes. It is based on a newly developed excimer laser micromachining technique that can accurately machine a 3D microstructure with a predetermined continuous surface profile. The method is called the planetary scanning method since it is based on a combination of sample rotation and revolution and a concept of laser machining probability. Spherical and aspheric microlenses with precise and smooth surface profiles are fabricated by direct laser machining on polymer materials. Laser-machined microlenses are replicated by electroforming to obtain inverse metal molds. Finally, plastic microlenses are replicated from these metal molds using hot embossing method. The profile accuracy and surface roughness of the produced microlenses at each stage have been measured and monitored. The average surface profile accuracy is better than 1μm and average surface roughness is less than 10nm. Optical performance of the fabricated microlenses is evaluated by measuring the light intensity distribution at the focal plane and the focal length. Experimental data show that the characteristics of fabricated spherical and aspheric microlenses are well matched to the theoretical predictions, which demonstrates the controllability and accuracy of this micromachining process. Potential applications and further developments will be addressed.

Excimer Laser Machining of Fired LTCC for Selectively Metallized Open Channel Structures

2013 ◽  
Vol 2013 (1) ◽  
pp. 000194-000199
Author(s):  
Dilshani Rathnayake-Arachchige ◽  
David A. Hutt ◽  
Paul P. Conway
Keyword(s):  
Excimer Laser ◽  
Machining Process ◽  
Laser Machining ◽  
Machining Parameters ◽  
Copper Plating ◽  
Active Components ◽  
Electroless Copper Plating ◽  
Machined Surface ◽  
Electroless Copper ◽  
Channel Structures

Low Temperature Co-fired Ceramic (LTCC) is an important technology in high frequency electronics applications and enables the fabrication of several ceramic layers with cavities, channel structures and micro-vias for embedded passive and active components. Typically, laser cutting combined with screen printing technology are used to form metallized cavities and micro-vias on green state LTCC. However, in this study, the excimer laser (248 nm wavelength) machining process combined with electroless copper plating was successfully employed to create selectively metallized channel structures on fired LTCC substrates. Dry film photoresist was used within the process to guide the activation of the laser machined surface with Sn/Pd catalyst prior to electroless copper deposition. The effect of different laser parameters were investigated and machined channels were characterized for their maximum depth and surface roughness. It was found that there was a significant correlation between the laser machining parameters and the channel characteristics which also affected the subsequent electroless copper plating and its electrical resistance.

Studying The Effect of a New Mixed Cutting Fluid on Surface Roughness

2020 ◽  
Vol 38 (11A) ◽  
pp. 1593-1601
Author(s):  
Mohammed H. Shaker ◽  
Salah K. Jawad ◽  
Maan A. Tawfiq
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Cutting Fluids ◽  
Machining Processes ◽  
Dry Cutting ◽  
Cutting Speeds

This research studied the influence of cutting fluids and cutting parameters on the surface roughness for stainless steel worked by turning machine in dry and wet cutting cases. The work was done with different cutting speeds, and feed rates with a fixed depth of cutting. During the machining process, heat was generated and effects of higher surface roughness of work material. In this study, the effects of some cutting fluids, and dry cutting on surface roughness have been examined in turning of AISI316 stainless steel material. Sodium Lauryl Ether Sulfate (SLES) instead of other soluble oils has been used and compared to dry machining processes. Experiments have been performed at four cutting speeds (60, 95, 155, 240) m/min, feed rates (0.065, 0.08, 0.096, 0.114) mm/rev. and constant depth of cut (0.5) mm. The amount of decrease in Ra after the used suggested mixture arrived at (0.21µm), while Ra exceeded (1µm) in case of soluble oils This means the suggested mixture gave the best results of lubricating properties than other cases.

High-Throughput Picosecond Laser Machining of Aerospace Nickel Superalloy

2021 ◽  
pp. 095440542110288
Author(s):  
Sundar Marimuthu ◽  
Bethan Smith
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Thermal Damage ◽  
Removal Rate ◽  
Picosecond Laser ◽  
Nickel Superalloy ◽  
Laser Machining ◽  
Process Conditions ◽  
Machining Performance

This manuscript discusses the experimental results on 300 W picosecond laser machining of aerospace-grade nickel superalloy. The effect of the laser’s energetic and beam scanning parameters on the machining performance has been studied in detail. The machining performance has been investigated in terms of surface roughness, sub-surface thermal damage, and material removal rate. At optimal process conditions, a picosecond laser with an average power output of 300 W can be used to achieve a material removal rate (MRR) of ∼140 mm3/min, with thermal damage less than 20 µm. Shorter laser pulse widths increase the material removal rate and reduce the resultant surface roughness. High scanning speeds improve the picosecond laser machining performance. Edge wall taper of ∼10° was observed over all the picosecond laser machined slots. The investigation demonstrates that high-power picosecond lasers can be used for the macro-machining of industrial components at an acceptable speed and quality.

Surface Roughness and Cutting Force Components Evaluation in Hard Turning by Differently Shaped Cutting Tools

2016 ◽  
Vol 862 ◽  
pp. 26-32 ◽  
Author(s):  
Michaela Samardžiová
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Hard Turning ◽  
Cutting Tool ◽  
Single Point ◽  
Machining Process ◽  
Tool Geometry ◽  
Machined Surface ◽  
Cutting Force Components ◽  
Force Components

There is a difference in machining by the cutting tool with defined geometry and undefined geometry. That is one of the reasons of implementation of hard turning into the machining process. In current manufacturing processes is hard turning many times used as a fine finish operation. It has many advantages – machining by single point cutting tool, high productivity, flexibility, ability to produce parts with complex shapes at one clamping. Very important is to solve machined surface quality. There is a possibility to use wiper geometry in hard turning process to achieve 3 – 4 times lower surface roughness values. Cutting parameters influence cutting process as well as cutting tool geometry. It is necessary to take into consideration cutting force components as well. Issue of the use of wiper geometry has been still insufficiently researched.

Single Input Multi Output Adaptive Network Based Fuzzy Inference System for Machinability Data Selection in Turning Operations

2011 ◽  
Vol 383-390 ◽  
pp. 1062-1070
Author(s):  
Adeel H. Suhail ◽  
N. Ismail ◽  
S.V. Wong ◽  
N.A. Abdul Jalil
Keyword(s):  
Surface Roughness ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Cutting Parameters ◽  
Machining Process ◽  
Data Selection ◽  
Adaptive Network ◽  
Inference System ◽  
Single Input ◽  
Machinability Data

The selection of machining parameters needs to be automated, according to its important role in machining process. This paper proposes a method for cutting parameters selection by fuzzy inference system generated using fuzzy subtractive clustering method (FSCM) and trained using an adaptive network based fuzzy inference system (ANFIS). The desired surface roughness (Ra) was entered into the first step as a reference value for three fuzzy inference system (FIS). Each system determine the corresponding cutting parameters such as (cutting speed, feed rate, and depth of cut). The interaction between these cutting parameters were examined using new sets of FIS models generated and trained for verification purpose. A new surface roughness value was determined using the cutting parameters resulted from the first steps and fed back to the comparison unit and was compared with the desired surface roughness and the optimal cutting parameters ( which give the minimum difference between the actual and predicted surface roughness were find out). In this way, single input multi output ANFIS architecture presented which can identify the cutting parameters accurately once the desired surface roughness is entered to the system. The test results showed that the proposed model can be used successfully for machinability data selection and surface roughness prediction as well.

Sign in / Sign up

Export Citation Format

Share Document