Surface roughness reduction and diffraction efficiency optimisation for e-beam written phase masks

We report the control of surface relief grating parameters and roughness for phase masks produced using e-beam lithography (EBL) and reactive ion etching (RIE). The relationships between processing conditions, grating parameters, surface roughness and the diffraction efficiency of the zeroth and the two first order transmitted beams are discussed.

Surface roughness reduction and diffraction efficiency optimisation for e-beam written phase masks

We report the control of surface relief grating parameters and roughness for phase masks produced using e-beam lithography (EBL) and reactive ion etching (RIE). The relationships between processing conditions, grating parameters, surface roughness and the diffraction efficiency of the zeroth and the two first order transmitted beams are discussed.

Surface roughness after excimer laser ablation using a PMMA model:profilometry and effects on vision

PURPOSE: To show that the limited quality of surfaces produced by one model of excimer laser systems can degrade visual performance with a polymethylmethacrylate (PMMA) model. METHODS: A range of lenses of different powers was ablated in PMMA sheets using five DOS-based Nidek EC-5000 laser systems (Nidek Technologies, Gamagori, Japan) from different clinics. Surface quality was objectively assessed using profilometry. Contrast sensitivity and visual acuity were measured through the lenses when their powers were neutralized with suitable spectacle trial lenses. RESULTS: Average surface roughness was found to increase with lens power, roughness values being higher for negative lenses than for positive lenses. Losses in visual contrast sensitivity and acuity measured in two subjects were found to follow a similar pattern. Findings are similar to those previously published with other excimer laser systems. CONCLUSIONS: Levels of surface roughness produced by some laser systems may be sufficient to degrade visual performance under some circumstances.

Novel spatial scanning technique for surface roughness measurement

We present the first spatial scanning system using wavelength-spatial transformation of chromatic dispersion device. Optical probe used in fiber optic interferometer for surface measurement is demonstrated by using diffraction grating and wavelength scanning technique.

A geometrical model for surface roughness prediction when face milling Al 7075-T7351 with square insert tools

Surface quality is important in engineering and a vital aspect of it is surface roughness, since it plays an important role in wear resistance, ductility, tensile, and fatigue strength for machined parts. This paper reports on a research study on the development of a geometrical model for surface roughness prediction when face milling with square inserts. The model is based on a geometrical analysis of the recreation of the tool trail left on the machined surface. The model has been validated with experimental data obtained for high speed milling of aluminum alloy (Al 7075-T7351) when using a wide range of cutting speed, feed per tooth, axial depth of cut and different values of tool nose radius (0.8. mm and 2.5. mm), using the Taguchi method as the design of experiments. The experimental roughness was obtained by measuring the surface roughness of the milled surfaces with a non-contact profilometer. The developed model can be used for any combination of material workpiece and tool, when tool flank wear is not considered and is suitable for using any tool diameter with any number of teeth and tool nose radius. The results show that the developed model achieved an excellent performance with almost 98% accuracy in terms of predicting the surface roughness when compared to the experimental data. © 2014 The Society of Manufacturing Engineers.

Integrated optimisation of surface roughness and tool performance when face milling 416 SS

Tool life is an important factor to be considered during the optimisation of a machining process since cutting parameters can be adjusted to optimise tool changing, reducing cost and time of production. Also the performance of a tool is directly linked to the generated surface roughness and this is important in cases where there are strict surface quality requirements. The prediction of tool life and the resulting surface roughness in milling operations has attracted considerable research efforts. The research reported herein is focused on defining the influence of milling cutting parameters such as cutting speed, feed rate and axial depth of cut, on three major tool performance parameters namely, tool life, material removal and surface roughness. The research is seeking to define methods that will allow the selection of optimal parameters for best tool performance when face milling 416 stainless steel bars. For this study the Taguchi method was applied in a special design of an orthogonal array that allows studying the entire parameter space with only a number of experiments representing savings in cost and time of experiments. The findings were that the cutting speed has the most influence on tool life and surface roughness and very limited influence on material removal. By last tool life can be judged either from tool life or volume of material removal.

Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351

In this work, different artificial neural networks (ANN) are developed for the prediction of surface roughness (R a) values in Al alloy 7075-T7351 after face milling machining process. The radial base (RBNN), feed forward (FFNN), and generalized regression (GRNN) networks were selected, and the data used for training these networks were derived from experiments conducted using a high-speed milling machine. The Taguchi design of experiment was applied to reduce the time and cost of the experiments. From this study, the performance of each ANN used in this research was measured with the mean square error percentage and it was observed that FFNN achieved the best results. Also the Pearson correlation coefficient was calculated to analyze the correlation between the five inputs (cutting speed, feed per tooth, axial depth of cut, chip°s width, and chip°s thickness) selected for the network with the selected output (surface roughness). Results showed a strong correlation between the chip thickness and the surface roughness followed by the cutting speed. © ASM International.

On the role of surface roughness in the aerodynamic performance and energy conversion of horizontal wind turbine blades:a review

Summary: Renewable energy is one of the main pillars of sustainable development, especially in developing economies. Increasing energy demand and the limitation of fossil fuel reserves make the use of renewable energy essential for sustainable development. Wind energy is considered to be one of the most important resources of renewable energy. In North African countries, such as Egypt, wind energy has an enormous potential; however, it faces quite a number of technical challenges related to the performance of wind turbines in the Saharan environment. Seasonal sand storms affect the performance of wind turbines in many ways, one of which is increasing the wind turbine aerodynamic resistance through the increase of blade surface roughness. The power loss because of blade surface deterioration is significant in wind turbines. The surface roughness of wind turbine blades deteriorates because of several environmental conditions such as ice or sand. This paper is the first review on the topic of surface roughness effects on the performance of horizontal-axis wind turbines. The review covers the numerical simulation and experimental studies as well as discussing the present research trends to develop a roadmap for better understanding and improvement of wind turbine performance in deleterious environments.

Super-hydrophobic surface of bulk carbon nanotubes compacted by spark plasma sintering followed by modification with polytetrofluorethylene

The surfaces of bulk carbon nanotubes compacted by plasma spark sintering have been modified with polytetrofluorethylene, thereby producing a super-hydrophobic surface with a contact angle above 160°. The surface roughness and air trapped in pores and between the polytetrofluorethylene particles are responsible for the super-hydrophobility. The material can be machined into desired shapes with fine and complex channels, allowing internal surfaces to also be super-hydrophobic.

Influence of cutting parameters and tool wear on martensitic stainless steel surface integrity after a face milling process

Surface finish is one of the most relevant aspects of machining operations, since it is one of the principle methods to assess quality. Also, surface finish influences mechanical properties such as fatigue behavior, wear, corrosion, etc. The feed, the cutting speed, the cutting tool material, the workpiece material and the cutting tool wear are some of the most important factors that affects the surface roughness of the machined surface. Due to the importance of the martensitic 416 stainless steel in the petroleum industry, especially in valve parts and pump shafts, this material was selected to study the influence of the feed per tooth and cutting speed on tool wear and surface integrity. Also the influence of tool wear on surface roughness is analyzed. Results showed that high values of roughness are obtained when using low cutting speed and feed per tooth and by using these conditions tool wear decreases prolonging tool life. Copyright © 2009 by ASME.