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Article
Publication date: 1 March 2008

Yusuf Sahin and A. Riza Motorcu

This paper presents a study of the development of surface roughness model when turning the mild steel hardened up to 484 HV with mixed alumina ceramic (KY1615) and coated…

Abstract

This paper presents a study of the development of surface roughness model when turning the mild steel hardened up to 484 HV with mixed alumina ceramic (KY1615) and coated alumina ceramic cutting tools (KY4400). The model was developed in terms of main cutting parameters such as cutting speed, feed rate and depth of cut, using response surface methodology. The established equation indicated that the feed rate affected the surface roughness the most, but other parametres remined stable for arithmetic average height parametre (Ra). However, it decreased with increasing the cutting speed, and with the starting and finishing point of cut for ten point height parametre (Rz). The cutting speed and the depth of cut had a slight effect on surface roughness values of Ra, Rz when using KY4400 cutting tools. Furthermore, the average surface roughness value of Ra was about 0.926 um, 1.089 um for KY1615, KY4400 cutting tools, respectively. The predicted surface roughness was found to be very close to experimentally observed ones at 95% confidence level. Moreover, analysis of variance indicated that squares terms were significant but interaction terms were insignificant for both cutting tools.

Details

Multidiscipline Modeling in Materials and Structures, vol. 4 no. 3
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 4 October 2011

Nikhil Padhye and Kalyanmoy Deb

The goal of this study is to carry out multi‐objective optimization by considering minimization of surface roughness (Ra) and build time (T) in selective laser sintering…

1353

Abstract

Purpose

The goal of this study is to carry out multi‐objective optimization by considering minimization of surface roughness (Ra) and build time (T) in selective laser sintering (SLS) process, which are functions of “build orientation”. Evolutionary algorithms are applied for this purpose. The performance comparison of the optimizers is done based on statistical measures. In order to find truly optimal solutions, local search is proposed. An important task of decision making, i.e. the selection of one solution in the presence of multiple trade‐off solutions, is also addressed. Analysis of optimal solutions is done to gain insight into the problem behavior.

Design/methodology/approach

The minimization of Ra and T is done using two popular optimizers – multi‐objective genetic algorithm (non‐dominated sorting genetic algorithm (NSGA‐II)) and multi‐objective particle swarm optimizers (MOPSO). Standard measures from evolutionary computation – “hypervolume measure” and “attainment surface approximator” have been borrowed to compare the optimizers. Decision‐making schemes are proposed in this paper based on decision theory.

Findings

The objects are categorized into groups, which bear similarity in optimal solutions. NSGA‐II outperforms MOPSO. The similarity of spread and convergence patterns of NSGA‐II and MOPSO ensures that obtained solutions are (or are close to) Pareto‐optimal set. This is validated by local search. Based on the analysis of obtained solutions, general trends for optimal orientations (depending on the geometrical features) are found.

Research limitations/implications

A novel and systematic way to address multi‐objective optimization decision‐making post‐optimal analysis is shown. Simulations utilize experimentally derived models for roughness and build time. A further step could be the experimental verification of findings provided in this study.

Practical implications

This study provides a thorough methodology to find optimal build orientations in SLS process. A route to decipher valuable problem information through post‐optimal analysis is shown. The principles adopted in this study are general and can be extended to other rapid prototyping (RP) processes and expected to find wide applicability.

Originality/value

This paper is a distinct departure from past studies in RP and demonstrates the concepts of multi‐objective optimization, decision‐making and related issues.

Details

Rapid Prototyping Journal, vol. 17 no. 6
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 14 March 2018

Fuat Kara and Burak Öztürk

This paper aims to examine the performance of the machining parameters used in the hard-turning process of DIN 1.2738 mold steel and identify the optimum machining conditions.

Abstract

Purpose

This paper aims to examine the performance of the machining parameters used in the hard-turning process of DIN 1.2738 mold steel and identify the optimum machining conditions.

Design/methodology/approach

Experiments were carried out via the Taguchi L18 orthogonal array. The evaluation of the experimental results was based on the signal/noise ratio. The effect levels of the control factors on the surface roughness and flank wear were specified with analysis of variance performed. Two different multiple regression analyses (linear and quadratic) were conducted for the experimental results. A higher correlation coefficient (R2) was obtained with the quadratic regression model, which showed values of 0.97 and 0.95 for Ra and Vb, respectively.

Findings

The experimental results indicated that generally better results were obtained with the TiAlN-coated tools, in respect to both surface roughness and flank wear. The Taguchi analysis found the optimum results for surface roughness to be with the cutting tools of coated carbide using physical vapor deposition (PVD), a cutting speed of 160 m/min and a feed rate of 0.1 mm/rev, and for flank wear, with cutting tools of coated carbide using PVD, a cutting speed of 80 m/min and a feed rate of 0.1 mm/rev. The results of calculations and confirmation tests for Ra were 0.595 and 0.570 µm, respectively, and for the Vb, 0.0244 and 0.0256 mm, respectively. Developed quadratic regression models demonstrated a very good relationship.

Originality/value

Optimal parameters for both Ra and Vb were obtained with the TiAlN-coated tool using PVD. Finally, confirmation tests were performed and showed that the optimization had been successfully implemented.

Details

Sensor Review, vol. 39 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 14 September 2015

Marek Burdek

This paper aims to analyze changes in the surface topography of the work rolls during skin passing. Cold rolled steel sheets are additionally subject to skin pass rolling…

Abstract

Purpose

This paper aims to analyze changes in the surface topography of the work rolls during skin passing. Cold rolled steel sheets are additionally subject to skin pass rolling to form an appropriate surface topography. This operation should facilitate the process of further metal forming of steel sheets, such as deep drawing, painting, etc. The surface topography of steel sheets is determined by the surface topography of the work rolls as well as the skin pass rolling parameters (rolling speed, elongation, roll force, etc.). Suitable preparation and selection of roll surface topography influences the degree of rolls wear and the surface topography of steel sheets as well.

Design/methodology/approach

Two-dimensional (2D) and three-dimensional (3D) roughness measurements of work roll surface before, during and after finishing of skin pass rolling of steel sheets are presented in the paper. The measurements were performed on four sets of work rolls with different surface topography.

Findings

The appearance of the surface of rolls obtained from the analysis of 3D roughness, the values of selected parameters of the 3D roughness and relative changes of the roughness parameter Ra/Sa depending on the length of the skin passed steel sheets are presented.

Practical implications

The wear of rolls is different depending on work surface topography.

Originality/value

The aim of this paper is to analyze changes in the surface topography of the work rolls during skin passing. It was expected that the surface of work rolls with more summits at similar average roughness Ra will change much faster than the surface with fewer summits. For this purpose, preliminary tests were performed in an industrial environment on four pairs of work rolls, including two pairs of rolls that were hard chromium-plated.

Details

Industrial Lubrication and Tribology, vol. 67 no. 6
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 20 June 2016

Di Wang, Yang Liu, Yongqiang Yang and Dongming Xiao

The purpose of this paper is to provide a theoretical foundation for improving the selective laser melting (SLM) surface roughness. To improve the part’s surface quality…

2972

Abstract

Purpose

The purpose of this paper is to provide a theoretical foundation for improving the selective laser melting (SLM) surface roughness. To improve the part’s surface quality during SLM process, the upper surface roughness of SLM parts was theoretically studied and the influencing factors were analyzed through experiments.

Design/methodology/approach

The characteristics of single track were first investigated, and based on the analysis of single track, theoretical value of the upper surface roughness would be calculated. Two groups of cubic sample were fabricated to validate SLM parts’ surface roughness, the Ra and relative density of all the cubic parts was measured, and the difference between theoretical calculation and experiment results was studied. Then, the effect of laser energy density on surface roughness was studied. At last, the SLM part’s surface was improved by laser re-melting method. At the end of this paper, the curved surface roughness was discussed briefly.

Findings

The SLM upper surface roughness is affected by the width of track, scan space and the thickness of powder layer. Measured surface roughness Ra value was about 50 per cent greater than the theoretical value. The laser energy density has a great influence on the SLM fabrication quality. Different laser energy density corresponds to different fabricating characteristics. This study divided the SLM fabrication into not completely melting zone, balling zone in low energy density, successfully fabricating zone and excessive melting zone. The laser surface re-melting (LSR) process can improve the surface roughness of SLM parts greatly without considering the fabricating time and stress accumulation.

Originality/value

The upper surface roughness of SLM parts was theoretically studied, and the influencing factors were analyzed together; also, the LSR process was proven to be effective to improve the surface quality. This study provides a theoretical foundation to improve the surface quality of SLM parts to promote the popularization and application of metal additive manufacturing technology.

Details

Rapid Prototyping Journal, vol. 22 no. 4
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 22 July 2019

Yang Tian, Dacian Tomus, Aijun Huang and Xinhua Wu

Selective laser melting (SLM) process is an additive manufacturing method that uses computer-aided design to fabricate complex components layer-by-layer. Surface roughness

Abstract

Purpose

Selective laser melting (SLM) process is an additive manufacturing method that uses computer-aided design to fabricate complex components layer-by-layer. Surface roughness is one of the primary drawbacks of SLM process; hence, the purpose of this paper is to present a parametric study and optimisation of fundamental parameters, including scan power, speed, inclined angle and layer thickness on surface roughness during selective laser melting of Hastelloy X.

Design/methodology/approach

Parametric significance on surface finish was analysed using analysis of variance and response surface methodology. General agreement between predicted and measured values was achieved. Surface characteristics of both up-skin and down-skin with various angles were covered within the investigated range.

Findings

Both experimental and statistical analysis showed that surface roughness of up-skin was primarily influenced by scan power, inclined angle and layer thickness while down-skin was more affected by the former two factors. Melt pool shape and staircase size were found to determine the up-skin surface, whereas attached particles were responsible for down-skin surface roughness.

Originality/value

As per our understanding, this manuscript provides valuable insight into the surface quality problem of SLM, which is a very critical issue for up-grading the process for manufacturing real components. This manuscript helps promote improved knowledge and understanding of the attributes and capabilities of this rapidly evolving 3D printing technology. Moreover, it establishes usable processing window and helps obtain optimal conditions, thus offering useful information to professionals working in this field. By combining experiments with statistical analysis, both practice and theory relevant to SLM process are further developed.

Details

Rapid Prototyping Journal, vol. 25 no. 7
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 8 July 2020

M. Kaladhar

The present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for…

Abstract

Purpose

The present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface roughness (Ra) and cutting tool flank wear (VB) while hard turning of AISI 4340 steel (35 HRC) under dry environment.

Design/methodology/approach

In this study, Taguchi L16 design of experiments methodology was chosen. The experiments were performed under dry machining conditions using TiSiN-TiAlN nanolaminate PVD-coated cutting tool on which Taguchi and responses surface methodology (RSM) for single objective optimization and MCDM methods like the multi-objective optimization by ratio analysis (MOORA) were applied to attain optimal set of machining parameters. The predictive models for each response and multiresponse were developed using RSM-based regression analysis. S/N ratios, analysis of variance (ANOVA), Pareto diagram, Tukey's HSD test were carried out on experimental data for profound analysis.

Findings

Optimal set of machining parameters were obtained as cutting speed: at 180 m/min., feed rate: 0.05 mm/rev., and depth of cut: 0.15 mm; cutting speed: 145 m/min., feed rate: 0.20 mm/rev. and depth of cut: 0.1 mm for Ra and VB, respectively. ANOVA showed feed rate (96.97%) and cutting speed (58.9%) are dominant factors for Ra and VB, respectively. A remarkable improvement observed in Ra (64.05%) and VB (69.94%) after conducting confirmation tests. The results obtained through the MOORA method showed the optimal set of machining parameters (cutting speed = 180 m/min, feed rate = 0.15 mm/rev and depth of cut = 0.25 mm) for minimizing the Ra and VB.

Originality/value

This work contributes to realistic application for manufacturing industries those dealing with AISI 4340 steel of 35 HRC. The research contribution of present work including the predictive models will provide some useful guidelines in the field of manufacturing, in particular, manufacturing of gear shafts for power transmission, turbine shafts, fasteners, etc.

Details

Multidiscipline Modeling in Materials and Structures, vol. 17 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 2 November 2020

Alasdair Soja, Jun Li, Seamus Tredinnick and Tim Woodfield

Additive manufacturing (AM) has the potential to revolutionise the fabrication of complex surgical instruments. However, AM parts typically have a higher surface roughness

Abstract

Purpose

Additive manufacturing (AM) has the potential to revolutionise the fabrication of complex surgical instruments. However, AM parts typically have a higher surface roughness compared to machined or fine cast parts. High surface roughness has important implications for surgical instruments, particularly in terms of cleanliness and aesthetic considerations. In this study, bulk surface finishing methods are described to produce end-use selective laser melting parts.

Design/methodology/approach

The aim was to achieve a surface finish as close as possible to machined parts (Ra = 0.9 µm, Wa = 0.2 µm, Pv = 7.3 µm). A sample coupon was designed to systematically evaluate different finishing techniques. Processes included bulk finishing, blasting and centrifugal finishing methods on individual parts, as well as heat treatment before and after surface finishing.

Findings

Abrasive blasting or centrifugal finishing alone was not adequate to achieve an end-use surface finish. White oxide vapour blasting at high water pressure was the most effective of the abrasive blasting processes. For centrifugal finishing, a 4 h runtime resulted in an acceptable reduction in surface roughness (Ra = 2.9 µm, Wa = 2.0 µm, Pv = 34.6 µm: inclined surface [30°]) while not significantly increasing part radii. The combination of finishing methods resulting in the smoothest surfaces was white oxide blasting followed by 4 h of centrifugal finishing and a final glass bead blast (Ra = 0.6 µm, Wa = 0.9 µm, Pv = 6.9 µm: inclined surface [30°]). The order of these methods was important because white oxide blasting was significantly less effective when applied after the centrifugal finishing.

Originality/value

Collectively, these results describe the development of a practical bulk finishing method for stainless steel surgical instruments produced by AM.

Details

Rapid Prototyping Journal, vol. 27 no. 1
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 1 November 2021

Shimin Dai, Hailong Liao, Haihong Zhu and Xiaoyan Zeng

For the laser powder bed fusion (L-PBF) technology, the side surface quality is essentially important for industrial applicated parts, such as the inner flow parts…

Abstract

Purpose

For the laser powder bed fusion (L-PBF) technology, the side surface quality is essentially important for industrial applicated parts, such as the inner flow parts. Contour is generally adopted at the parts’ outline to enhance the side surface quality. However, the side surface roughness (Ra) is still larger than 10 microns even with contour in previous studies. The purpose of this paper is to study the influence of contour process parameters, laser power and scanning velocity on the side surface quality of the AlSi10Mg sample.

Design/methodology/approach

Using L-PBF technology to manufacture AlSi10Mg samples under different contour process parameters, use a laser confocal microscope to capture the surface information of the samples, and obtain the surface roughness Ra and the maximum surface height Rz of each sample after analysis and processing.

Findings

The results show that the side surface roughness decreases with the increase of the laser power at the fixed scanning velocity of 1,000 mm/s, the side surface roughness Ra stays within the error range as the contour velocity increases. It is found that the Ra increases with the scanning velocity increasing and the greater the laser power with the greater Ra increases when the laser power of contour process parameters is 300 W, 350 W and 400 W. The Rz maintain growth with the contour scanning velocity increasing at constant laser power. The continuous uniform contour covers the pores in the molten pool of the sample edge and thus increase the density of the sample. Two mechanisms named “Active adhesion” and “Passive adhesion” cause sticky powder.

Originality/value

Formation of a uniform and even contour track is key to obtain the good side surface quality. The side surface quality is determined by the uniformity and stability of the contour track when the layer thickness is fixed. These research results can provide helpful guidance to improve the surface quality of L-PBF manufactured parts.

Details

Rapid Prototyping Journal, vol. 28 no. 3
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 3 October 2019

Dharmendra B.V., Shyam Prasad Kodali and Nageswara Rao Boggarapu

The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve…

Abstract

Purpose

The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve maximum material removal rate (MRR) and minimum surface roughness.

Design/methodology/approach

Data of a few experiments as per the Taguchi’s orthogonal array are considered for achieving maximum MRR and minimum surface roughness (Ra) of the Inconel718. Analysis of variance is performed to understand the statistical significance of AWJM input process parameters.

Findings

Empirical relations are developed for MRR and Ra in terms of the AWJM process parameters and demonstrated their adequacy through comparison of test results.

Research limitations/implications

The signal-to-noise ratio transformation should be applied to take in to account the scatter in the repetition of tests in each test run. But, many researchers have adopted this transformation on a single output response of each test run, which has no added advantage other than additional computational task. This paper explains the impact of insignificant process parameter in selection of optimal process parameters. This paper demands drawbacks and complexity in existing theories prior to use new algorithms.

Practical implications

Taguchi approach is quite simple and easy to handle optimization problems, which has no practical implications (if it handles properly). There is no necessity to hunt for new algorithms for obtaining solution for multi-objective optimization AWJM process.

Originality/value

This paper deals with a case study, which demonstrates the simplicity of the Taguchi approach in solving multi-objective optimization problems with a few number of experiments.

Details

Multidiscipline Modeling in Materials and Structures, vol. 16 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

1 – 10 of 640