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1 – 10 of over 1000
Article
Publication date: 17 November 2021

Terry Yuan-Fang Chen, Yu-Lung Lo, Ze-Hong Lin and Jui-Yu Lin

The purpose of this study was expected to simultaneously monitor the surface roughness of each solidified layer, the surface roughness of the metal powder, the outline of…

Abstract

Purpose

The purpose of this study was expected to simultaneously monitor the surface roughness of each solidified layer, the surface roughness of the metal powder, the outline of the solidified layer, and the height difference between the solidified layer and the metal powder.

Design/methodology/approach

In the proposed approach, color images with red, green and blue fringes are used to measure the shape of the built object using a three-step phase-shift algorithm and phase-unwrapping method. In addition, the surface roughness is extracted from the speckle information in the captured image using a predetermined autocorrelation function.

Findings

The feasibility and accuracy of the proposed system were validated by comparing it with a commercial system for an identical set of samples fabricated by a selective laser melting process. The maximum and minimum errors between the two systems are approximately 24% and 0.8%, respectively.

Originality/value

In the additive manufacturing field, the authors are the first to use fringe detection technology to simultaneously measure the profile of the printed layer and its surface roughness.

Details

Rapid Prototyping Journal, vol. 28 no. 4
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 22 February 2022

Kura Alemayehu Beyene

Modeling helps to determine how structural parameters of fabric affect the surface of a fabric and also identify the way they influence fabric properties. Moreover, it…

Abstract

Purpose

Modeling helps to determine how structural parameters of fabric affect the surface of a fabric and also identify the way they influence fabric properties. Moreover, it helps to estimate and evaluate without the complexity and time-consuming experimental procedures. The purpose of this study is to develop and select the best regression model equations for the prediction and evaluation of surface roughness of plain-woven fabrics.

Design/methodology/approach

In this study, a linear and quadratic regression model was developed for the prediction and evaluation of surface roughness of plain-woven fabrics, and the capability in accuracy and reliability of the two-model equation was determined by the root mean square error (RMSE). The Design-Expert AE11 software was used for developing the two model equations and analysis of variance “ANOVA.” The count and density were used for developing linear model equation one “SMD1” as well as for quadratic model equation two “SMD2.”

Findings

From results and findings, the effects of count and density and their interactions on the roughness of plain-woven fabric were found statistically significant for both linear and quadratic models at a confidence interval of 95%. The count has a positive correlation with surface roughness, while density has a negative correlation. The correlations revealed that models were strongly correlated at a confidence interval of 95% with adjusted R² of 0.8483 and R² of 0.9079, respectively. The RMSE values of the quadratic model equation and linear model equation were 0.1596 and 0.0747, respectively.

Originality/value

Thus, the quadratic model equation has better capability accuracy and reliability in predictions and evaluations of surface roughness than a linear model. These models can be used to select a suitable fabric for various end applications, and it was also used for tests and predicts surface roughness of plain-woven fabrics. The regression model helps to reduce the gap between the subjective and objective surface roughness measurement methods.

Details

Research Journal of Textile and Apparel, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1560-6074

Keywords

Article
Publication date: 21 June 2011

Babur Ozcelik, Emel Kuram, Erhan Demirbas and Emrah Şik

The purpose of this paper is to investigate the performance of four cutting oils, two different vegetable‐based cutting fluids developed from refined sunflower oil and two…

695

Abstract

Purpose

The purpose of this paper is to investigate the performance of four cutting oils, two different vegetable‐based cutting fluids developed from refined sunflower oil and two commercial types (semi‐synthetic and mineral), for surface roughness during drilling of AISI 304 austenitic stainless steel with HSSE tool.

Design/methodology/approach

L9 (33) orthogonal array was used for the experiment plan. Spindle speed, feed rate and drilling depth were considered as machining parameters.

Findings

Results were evaluated statistically. Mathematical models based on cutting parameters were obtained from regression analyses to predict surface roughness. ANOVA was used to determine the effect of the cutting parameters on the surface roughness. The performance results were found to be better for vegetable‐based cutting oils than that of commercial ones.

Originality/value

The paper reports on the use of refined sunflower oil in drilling stainless steel.

Details

Industrial Lubrication and Tribology, vol. 63 no. 4
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 7 March 2016

M.P. Jenarthanan, A. Ajay Subramanian and R. Jeyapaul

This paper aims to study the comparison between a response surface methodology (RSM) and artificial neural network (ANN) in the modelling and prediction of surface

Abstract

Purpose

This paper aims to study the comparison between a response surface methodology (RSM) and artificial neural network (ANN) in the modelling and prediction of surface roughness during endmilling of glass-fibre-reinforced polymer composites.

Design/methodology/approach

Aiming to achieve this goal, several milling experiments were performed with polycrystalline diamond inserts at different machining parameters, namely, feed rate, cutting speed, depth of cut and fibre orientation angle. Mathematical model is created using central composite face-centred second-order in RSM and the adequacy of the model was verified using analysis of variance. ANN model is created using the back propagation algorithm.

Findings

With regard to the machining test, it was observed that feed rate is the dominant parameter that affects the surface roughness, followed by the fibre orientation. The comparison results show that models provide accurate prediction of surface roughness in which ANN performs better than RSM.

Originality/value

The data predicted from ANN are very nearer to experimental results compared to RSM; therefore, this ANN model can be used to determine the surface roughness for various fibre-reinforced polymer composites and also for various machining parameters.

Details

Pigment & Resin Technology, vol. 45 no. 2
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 14 April 2014

Ismail Durgun and Rukiye Ertan

The mechanical properties and surface finish of functional parts are important consideration in rapid prototyping, and the selection of proper parameters is essential to…

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Abstract

Purpose

The mechanical properties and surface finish of functional parts are important consideration in rapid prototyping, and the selection of proper parameters is essential to improve manufacturing solutions. The purpose of this paper is to describe how parts manufactured by fused deposition modelling (FDM), with different part orientations and raster angles, were examined experimentally and evaluated to achieve the desired properties of the parts while shortening the manufacturing times due to maintenance costs.

Design/methodology/approach

For this purpose, five different raster angles (0°, 30°, 45°, 60° and 90°) for three part orientations (horizontal, vertical and perpendicular) have been manufactured by the FDM method and tested for surface roughness, tensile strength and flexural strength. Also, behaviour of the mechanical properties was clarified with scanning electron microscopy images of fracture surfaces.

Findings

The research results suggest that the orientation has a more significant influence than the raster angle on the surface roughness and mechanical behaviour of the resulting fused deposition part. The results indicate that there is close relationship between the surface roughness and the mechanical properties.

Originality/value

The results of this paper are useful in defining the most appropriate raster angle and part orientation in minimum production cost for FDM components on the basis of their expected in-service loading.

Details

Rapid Prototyping Journal, vol. 20 no. 3
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 19 January 2015

B. M. Kumar and M. M. Ratnam

– This paper aims to propose a non-contact method using machine vision for measuring the surface roughness of a rotating workpiece at speeds of up to 4,000 rpm.

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Abstract

Purpose

This paper aims to propose a non-contact method using machine vision for measuring the surface roughness of a rotating workpiece at speeds of up to 4,000 rpm.

Design/methodology/approach

A commercial digital single-lens-reflex camera with high shutter speed and backlight was used to capture a silhouette of the rotating workpiece profile. The roughness profile was extracted at sub-pixel accuracy from the captured images using the moment invariant method of edge detection. The average (Ra), root-mean square (Rq) and peak-to-valley (Rt) roughness parameters were measured for ten different specimens at spindle speeds of up to 4,000 rpm. The roughness values measured using the proposed machine vision system were verified using the stylus profilometer.

Findings

The roughness values measured using the proposed method show high correlation (up to 0.997 for Ra) with those determined using the profilometer. The mean differences in Ra, Rq and Rt between the two methods were only 4.66, 3.29 and 3.70 per cent, respectively.

Practical implications

The proposed method has significant potential for application in the in-process roughness measurement and tool condition monitoring from workpiece profile signature during turning, thus, obviating the need to stop the machine.

Originality/value

The machine vision method combined with sub-pixel edge detection has not been applied to measure the roughness of a rotating workpiece.

Details

Sensor Review, vol. 35 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 17 May 2022

Wendy Triadji Nugroho, Yu Dong and Alokesh Pramanik

This paper aims to investigate the dimensional accuracy consisting of thickness, grip section width, full length, circularity, cylindricity and surface finish of printed…

Abstract

Purpose

This paper aims to investigate the dimensional accuracy consisting of thickness, grip section width, full length, circularity, cylindricity and surface finish of printed polyurethane dog-bone samples based on American Society for Testing and Materials D638 type V standard, which were optimally printed by fused deposition modelling (FDM).

Design/methodology/approach

The experimental approach focuses on determining main effects of printing parameters, including nozzle temperature, infill percentage, print speed and layer height on dimensional error and surface finish of the printed samples, followed by the confirmation tests to warrant the reproducibility of experimental results.

Findings

This study shows that layer height has the most significant impact on dimensional accuracy and surface finish of printed samples compared to other printing parameters, whereas infill density has no significant effect on all sample dimensions.

Originality/value

This paper presents a comprehensive study relating to various dimensional accuracies in terms of full length, grip section width, thickness, circularity, cylindricity and surface finish of dog-bone samples printed by FDM to improve the printability and processibility via additive manufacturing.

Details

Rapid Prototyping Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2546

Keywords

Open Access
Article
Publication date: 27 June 2019

Younss Ait Mou and Muammer Koc

This paper aims to report on the findings of an investigation to compare three different three-dimensional printing (3DP) or additive manufacturing technologies [i.e…

Abstract

Purpose

This paper aims to report on the findings of an investigation to compare three different three-dimensional printing (3DP) or additive manufacturing technologies [i.e. fused deposition modeling (FDM), stereolithography (SLA) and material jetting (MJ)] and four different equipment (FDM, SLA, MJP 2600 and Object 260) in terms of their dimensional process capability (dimensional accuracy and surface roughness). It provides a comprehensive and comparative understanding about the level of attainable dimensional accuracy, repeatability and surface roughness of commonly used 3DP technologies. It is expected that these findings will help other researchers and industrialists in choosing the right technology and equipment for a given 3DP application.

Design/methodology/approach

A benchmark model of 5 × 5 cm with several common and challenging features, such as around protrusion and hole, flat surface, micro-scale ribs and micro-scale long channels was designed and printed repeatedly using four different equipment of three different 3DP technologies. The dimensional accuracy of the printed models was measured using non-contact digital measurement methods. The surface roughness was evaluated using a digital profilometer. Finally, the surface quality and edge sharpness were evaluated under a reflected light ZEISS microscope with a 50× magnification objective.

Findings

The results show that FDM technology with the used equipment results in a rough surface and loose dimensional accuracy. The SLA printer produced a smoother surface, but resulted in the distortion of thin features (<1 mm). MJ printers, on the other hand, produced comparable surface roughness and dimensional accuracy. However, ProJet MJP 3600 produced sharper edges when compared to the Objet 260 that produced round edges.

Originality/value

This paper, for the first time, provides a comprehensive comparison of three different commonly used 3DP technologies in terms of their dimensional capability and surface roughness without farther post-processing. Thus, it offers a reliable guideline for design consideration and printer selection based on the target application.

Details

Rapid Prototyping Journal, vol. 25 no. 5
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 1 February 2003

Fred F. Farshad and Thomas C. Pesacreta

The objectives of this study were to determine: the type of coating that minimized pipe surface roughness and how the choice of metrological instrument could influence…

1747

Abstract

The objectives of this study were to determine: the type of coating that minimized pipe surface roughness and how the choice of metrological instrument could influence pipe surface roughness data. The internal surface of pipe was coated with either phenolic, modified novalac, epoxy, or nylon material. Roughness of coated pipe was assessed with two linear surface profilers, a Dektak3ST® and a Hommel T1000, and a Dimension 3000® atomic force microscope (AFM). Arithmetic roughness (Ra), root mean square roughness (Rq), and mean peak‐to‐valley height (RZD), were statistically analyzed. The ability of RZD to focus on the extremes of height and depth on the surface made it a significant parameter for detecting features that would affect fluid flow in pipes.

Details

Anti-Corrosion Methods and Materials, vol. 50 no. 1
Type: Research Article
ISSN: 0003-5599

Keywords

Article
Publication date: 18 September 2017

M.P. Jenarthanan, Venkata Sai Sunil Gujjalapudi and Venkatraman V.

The purpose of this paper is to originate a statistical model for delamination factor, surface roughness, machining force and also to determine and compare the effects of…

Abstract

Purpose

The purpose of this paper is to originate a statistical model for delamination factor, surface roughness, machining force and also to determine and compare the effects of machining parameters (spindle speed, fiber orientation angle, helix angle and feed rate) on the output responses during end-milling of glass fiber reinforced polymers (GFRP) by using desirability functional analysis (DFA) and grey relational analysis (GRA).

Design/methodology/approach

Based on Taguchi’s L27 orthogonal array, milling experiments were carried on GFRP composite plates employing solid carbide end mills with different helix angles. The machining parameters were optimized by an approach based on DFA and GRA, which were useful tools for optimizing multi-response considerations, namely, machining force, surface roughness and delamination factor. A composite desirability index was obtained for multi-responses using individual desirability values from DFA. Based on this index and grey relational grade the optimum levels of parameters were identified and significant contribution of parameters was ascertained by analysis of variance.

Findings

Fiber orientation angle (66.75 percent) was the significant parameter preceded by feed rate (15.05 percent), helix angle (7.76 percent) and spindle speed (0.30 percent) for GFRP composite plates.

Originality/value

Multi-objective optimization in end-milling of GFRP composites using DFA and GRA has not been performed yet.

Details

Multidiscipline Modeling in Materials and Structures, vol. 13 no. 3
Type: Research Article
ISSN: 1573-6105

Keywords

1 – 10 of over 1000