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Article
Publication date: 16 November 2012

M.P. Jenarthanan, R. Jeyapaul and N. Naresh

The purpose of this paper is to develop a mathematical model for surface roughness and delamination through response surface methodology (RSM) and analyse the influences…

Abstract

Purpose

The purpose of this paper is to develop a mathematical model for surface roughness and delamination through response surface methodology (RSM) and analyse the influences of the entire individual input machining parameters (cutting speed, fibre orientation angle, depth of cut and feed rate) on the responses in milling of glass fibre reinforced plastics (GFRP) composites with solid carbide end mill cutter coated with PCD.

Design/methodology/approach

Four factors, five level central composites and a rotatable design matrix in response surface methodology were employed to carry out the experimental investigation. “Design Expert 8.0” software was used for regression and graphical analysis of the data were collected. The optimum values of the selected variables were obtained by solving the regression equation and by analyzing the response surface contour plots. Analysis of variance (ANOVA) was applied to check the validity of the model and for finding the significant parameters.

Findings

The developed second order response surface model was used to calculate the surface roughness and delamination of the machined surfaces at different cutting conditions with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.

Originality/value

The effect of fibre orientation during milling of GFRP laminates using RSM has not been previously attempted for analysis.

Details

Multidiscipline Modeling in Materials and Structures, vol. 8 no. 4
Type: Research Article
ISSN: 1573-6105

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Article
Publication date: 4 September 2020

Benjamin Chukudi Oji and Sunday Ayoola Oke

There is growing evidence of a knowledge gap in the association of maintenance with production activities in bottling plants. Indeed, insights into how to jointly optimise…

Abstract

Purpose

There is growing evidence of a knowledge gap in the association of maintenance with production activities in bottling plants. Indeed, insights into how to jointly optimise these activities are not clear. In this paper, two optimisation models, Taguchi schemes and response surface methodology are proposed.

Design/methodology/approach

Borrowing from the “hard” total quality management elements in optimisation and prioritisation literature, two new models were developed based on factor, level and orthogonal array selection, signal-to-noise ratio, analysis of variance and optimal parametric settings as Taguchi–ABC and Taguchi–Pareto. An additional model of response surface methodology was created with analysis on regression, main effects, residual plots and surface plots.

Findings

The Taguchi S/N ratio table ranked planned maintenance as the highest. The Taguchi–Pareto shows the optimal parametric setting as A4B4C1 (28 h of production, 30.56 shifts and 37 h of planned maintenance). Taguchi ABC reveals that the planned maintenance and number of shifts will influence the outcome of production greatly. The surface regression table reveals that the production hours worked decrease at a value of planned maintenance with a decrease in the number of shifts.

Originality/value

This is the first time that joint optimisation for bottling plant will be approached using Taguchi–ABC and Taguchi–Pareto. It is also the first time that response surface will be applied to optimise a unique platform of the bottling process plant.

Details

The TQM Journal, vol. 33 no. 2
Type: Research Article
ISSN: 1754-2731

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Article
Publication date: 18 May 2021

Mohammad Javad Hooshmand, Saeed Mansour and Amin Dehghanian

The advancement of additive manufacturing technologies has resulted in producing parts of high quality and reduced manufacturing time. This paper aims to achieve a…

Abstract

Purpose

The advancement of additive manufacturing technologies has resulted in producing parts of high quality and reduced manufacturing time. This paper aims to achieve a simultaneous optimal solution for build time and surface roughness as the output data and also to find the best values for the input data consisting of build orientation, extrusion width, layer thickness, infill percentage and raster angle.

Design/methodology/approach

For this purpose, the effects of process parameters on the response variables were investigated by the design of experiments approach to develop empirical models using response surface methodology. The experimental parts of this research were conducted using an inexpensive and locally assembled fused filament fabrication (FFF) machine. A total of 50 runs for 4 different geometries, namely, cylinder, prism, 3DBenchy and twist gear vase, were performed using the rotatable central composite design, and each process parameters were investigated in two levels to develop empirical models. Also, a novel optimization method, namely, the posterior-based method, was accomplished to find the best values for the response variables.

Findings

The results demonstrated that not only the build orientation and layer thickness have notable effects on both response variables but also build time is dependent on extrusion width and infill percentage. Low infill percentage and high extrusion width resulted in increasing build time. By reducing layer thickness and infill percentage while increasing extrusion width, parts of high-quality surface finish and reduced built time were produced. Optimum process parameters were found to be of build direction of 0°, extrusion width of 0.61 mm, layer thickness of 0.22 mm, infill percentage of 20% and raster angle of 0°.

Originality/value

Through the developed empirical models and by minimizing build orientation and layer thickness, and also considerations for process parameters, parts of high-quality surface finish and reduced built time could be produced on FFF machines. To compensate for increased build time because of reduction in layer thickness, extrusion width and infill percentage must have their maximum and minimum value, respectively.

Details

Rapid Prototyping Journal, vol. 27 no. 5
Type: Research Article
ISSN: 1355-2546

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Article
Publication date: 7 November 2016

M.P. Jenarthanan, A. Lakshman Prakash and R. Jeyapaul

The paper aims to develop a mathematical model for delamination and surface roughness during end milling by using response surface methodology (RSM) and to determine how…

Abstract

Purpose

The paper aims to develop a mathematical model for delamination and surface roughness during end milling by using response surface methodology (RSM) and to determine how the input parameters (cutting speed, depth of cut, helix angle and feed rate) influence the output response (delamination and surface roughness) in machining of hybrid glass fibre reinforced plastic (GFRP; Abaca and Glass) composite using solid carbide end mill cutter.

Design/methodology/approach

Four-factor, three-level Taguchi orthogonal array design in RSM is used to carry out the experimental investigation. The “Design Expert 8.0” is used to analyse the data collected graphically. Analysis of variance is carried out to validate the model and for determining the most significant parameter.

Findings

The feed rate is the cutting parameter which has greater influence on delamination (88.39 per cent), and cutting speed is the cutting parameter which has greater influence on surface roughness (53.42 per cent) for hybrid GFRP composite materials. Both surface roughness and delamination increase as feed rate increases, which means that the composite damage is larger for higher feed rates.

Originality/value

Effect of milling of hybrid GFRP composite on delamination and surface roughness with various helix angles of solid carbide end mill has not been analysed yet using RSM.

Details

Pigment & Resin Technology, vol. 45 no. 6
Type: Research Article
ISSN: 0369-9420

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Article
Publication date: 6 August 2018

Deepak Kumar Naik and Kalipada Maity

Plasma arc cutting (PAC) is extensively applicable for cutting the materials in faster speed with better accuracy in different manufacturing industries. The cutting of…

Abstract

Purpose

Plasma arc cutting (PAC) is extensively applicable for cutting the materials in faster speed with better accuracy in different manufacturing industries. The cutting of sailhard steel plate plays a great challenge in plasma arc cutting process.

Design/methodology/approach

In this investigation, a special abrasion-resistant steel known as sailhard of 20 mm thickness plate has been cut by PAC machine. Cutting current, stand-off distance, cutting speed and gas pressure were selected as cutting parameters. The corresponding responses focused for this study are material removal rate, kerf and chamfer. L30 orthogonal array based on a central composite design (CCD) of response surface methodology (RSM) was used to design the run of the experiment. For predicting and modeling of optimal cutting conditions, a hybrid approach of desirability function-based response surface methodology (DRSM) was acquainted.

Findings

The result of this study determines that desirability index (DI) was affected significantly with the machining parameter as well as their interaction. A confirmation test was carried out to analyze the degree of effectiveness of DRSM technique.

Originality/value

In PAC, the selection of process parameters and effect of that parameter on the output responses is of greater value because of the selection of best cutting condition.

Details

World Journal of Engineering, vol. 15 no. 4
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 1 March 1998

Joel E. McClurkin and David W. Rosen

When building parts in a stereolithography apparatus (SLA), the user is faced with many decisions regarding how the part will be built. The quality of the build can be…

Abstract

When building parts in a stereolithography apparatus (SLA), the user is faced with many decisions regarding how the part will be built. The quality of the build can be controlled by the user by changing one of several build style variables, including part orientation, cross sectional layer thickness, and laser hatch density. A user will probably have preferences for the part build (i.e. accuracy or speed), but may not understand how to vary the build style variables to produce the desired results. A method based on response surface methodology and multiobjective decision support is described in this paper for relating build goals to the build style variables to provide support for making build style decisions. The method is applied to the build style of a circuit breaker handle. Results indicate the method’s usefulness in supporting build style decisions. Expected behaviors of the goals with respect to the variables were confirmed and quantified. Additionally, response surface methodology was shown to be accurate and effective in modeling the relationships among variables and goals.

Details

Rapid Prototyping Journal, vol. 4 no. 1
Type: Research Article
ISSN: 1355-2546

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Article
Publication date: 3 May 2016

M.P. Jenarthanan, A. Lakshman Prakash and R. Jeyapaul

This paper aims to develop a mathematical model for analysing surface roughness during end milling by using response surface methodology (RSM) and to determine how the…

Abstract

Purpose

This paper aims to develop a mathematical model for analysing surface roughness during end milling by using response surface methodology (RSM) and to determine how the input parameters (cutting speed, depth of cut and feed rate) influence the output parameter (surface roughness) in the machining of hybrid glass fibre reinforced plastic (GFRP; Abaca and Glass) composite by using solid carbide end mill cutter.

Design/methodology/approach

Three factors and a three-level Box–Behnken design in RSM were used to carry out the experimental investigation. Handysurf E-35A was used to measure the surface roughness of the machined hybrid GFRP composites. The “Design Expert 8.0” was used to analyse the data collected graphically. Analysis of variance was carried out to validate the model and determine the most significant parameter.

Findings

The response surface model was used to predict the input factors influencing the surface roughness of the machined surfaces of hybrid GFRP composite at different cutting conditions with a chosen range of 95 per cent confidence intervals. Analysis of the influences of the entire individual input machining parameters on the surface roughness carried out using RSM.

Originality/value

The effect of the milling of hybrid GFRP composite on the surface roughness with solid carbide end mill by using RSM has not been analysed yet.

Details

Pigment & Resin Technology, vol. 45 no. 3
Type: Research Article
ISSN: 0369-9420

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Article
Publication date: 27 July 2012

A. Safdar, H.Z. He, Liu‐Ying Wei, A. Snis and Luis E. Chavez de Paz

Ti‐6Al‐4V is one of the most attractive materials being used in aerospace, automotive and medical implant industries. Electron beam melting (EBM) is one of the direct…

Abstract

Purpose

Ti‐6Al‐4V is one of the most attractive materials being used in aerospace, automotive and medical implant industries. Electron beam melting (EBM) is one of the direct digital manufacturing methods to produce complex geometries of fully dense and near net shape parts. The EBM system provides an opportunity to built metallic objects with different processing parameter settings like beam current, scan speed, probe size on powder, etc. The purpose of this paper is to determine and understand the effect of part's thickness and variation in process parameter settings of the EBM system on surface roughness/topography of EBM fabricated Ti‐6Al‐4V metallic parts.

Design/methodology/approach

A mathematical model based upon response surface methodology (RSM) is developed to study the variation of surface roughness with changing process parameter settings. Surface roughness of the test slabs produced with different parameter settings and thickness has been studied under confocal microscope. Response surface methodology was used to develop a multiple regression model to correlate the effect of variation in EBM process parameters settings and thickness of parts on surface roughness of EBM produced Ti‐6Al‐4V.

Findings

It has been observed that every part produced by EBM system has detectable surface roughness. The surface roughness parameter Ra varies between 1‐20 μm for different samples depending upon the process parameter setting and thickness. The Ra value increases with increasing sample thickness and beam current, and decreases with increase in offset focus and scan speed.

Originality/value

Surface roughness is related to wear and friction property of the material and hence is related to the life time and performance of the part. Surface roughness is an important property of any material to be considered as biomaterial. The surface roughness of the material depends upon the manufacturing method and environment and hence it is controllable either during fabrication or by post processing. From the 1st order regression model developed in this study, it is also evident that sample thickness, scan speed and beam current have relatively more effect on roughness value then the offset focus. With the model obtained equation, a designer can subsequently select the best combination of sample thickness and process parameter values to achieve desired surface roughness.

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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

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Article
Publication date: 26 January 2021

Camila Aparecida Diniz, Yohan Méndez, Fabrício Alves de Almeida, Sebastião Simões da Cunha Jr and G.F. Gomes

Many studies only take into account the ply stacking sequence as the design variable to determine the optimal ply drop-off location; however, it is necessary to optimize…

Abstract

Purpose

Many studies only take into account the ply stacking sequence as the design variable to determine the optimal ply drop-off location; however, it is necessary to optimize other parameters that have a direct influence on the ply drop-off site such as which plies should be dropped and in which longitudinal direction. That way, the purpose of this study is to find the most significant design variables relative to the drop-off location considering the transversal and longitudinal positions, seeking to achieve the optimal combination of ply drop-off locations that provides excellent performance for the laminate plate.

Design/methodology/approach

This study aims to determine the optimal drop-off location in a laminate plate using the finite element method and an approach statistical with design of experiments (DOE).

Findings

The optimization strategy using DOE revealed to be satisfactory for analyzing laminate structures with ply drop-offs, demonstrating that not all design factors influence the response variability. The failure criterion response variable revealed a poor fit, with an adjusted coefficient of determination lower than 60%, thus demonstrating that the response did not vary with the ply drop-off location. Already the strain and natural frequency response variables presented high significance. Finally, the optimization strategy revealed that the optimal drop-off location that minimizes the strain and maximizes the natural frequency is the ply drop-off located of the end plate.

Originality/value

It was also noted that many researchers prefer evolutionary algorithms for optimizing composite structures with ply drop-offs, being scarce to the literature studies involving optimization strategies using response surface methodology. In addition, many studies only take into account the ply stacking sequence as the design variable to determine the optimal ply drop-off location; however, in this study, the authors investigated other important parameters that have direct influence on the ply drop-off site such as which plies should be dropped and in which longitudinal direction.

Details

Engineering Computations, vol. 38 no. 7
Type: Research Article
ISSN: 0264-4401

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