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Article

Alagappan K M, Vijayaraghavan S, Jenarthanan M P and Giridharan R

The purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite…

Abstract

Purpose

The purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using TaguchiGrey Relational Analysis.

Design/methodology/approach

The contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.

Findings

The optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.

Originality/value

Optimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using TaguchiGrey Relational Analysis has not been previously explored.

Details

Multidiscipline Modeling in Materials and Structures, vol. 16 no. 5
Type: Research Article
ISSN: 1573-6105

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Article

Mohd Muqeem, Ahmad Faizan Sherwani, Mukhtar Ahmad and Zahid Akhtar Khan

Diesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this…

Abstract

Purpose

Diesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this paper is to optimize the input parameters of diesel engine which will lead to optimum performance and exhaust emissions.

Design/methodology/approach

To achieve the goal of improving diesel engine performance and exhaust emissions, four input parameters were considered in the study. Five different levels of each input parameter were taken. Four response variables under no load, half load and full load conditions were recorded. Experiments were performed in random manner according to selected Taguchi L25 orthogonal array. The data were analyzed using grey relational analysis coupled with principal component analysis. Analysis of S/N ratio was performed to obtain the optimum combination of input parameters. The grey relational grade at optimum setting of the input parameters was obtained by regression analysis.

Findings

Results of the current research work give the optimum input parameter settings for no load, half load and full load conditions of diesel engine. Engine produces power more efficiently with low exhaust emissions when operated at these optimum settings.

Practical implications

In view of the compliance to the stringent air pollution norms of the nations and fast depleting fossil fuels, it is of the utmost importance to design and operate the engine in the optimum range of its input parameters so that it produces more power with low exhaust emissions. This paper aims at optimizing input parameters of diesel engine to improve performance and exhaust emissions. Results of the study presented in this paper are significantly useful for diesel engine-related researchers and professionals.

Originality/value

From the literature review, it appears that only few researchers have conducted studies pertaining to the optimization of the input parameters of diesel engine to improve performance or exhaust emissions. Although few studies related to the optimization of compression ratio, fuel injection timing, fuel injection pressure and air pressure have been reported, no work related to optimization of temperature and pressure of turbocharged air has been reported. Therefore, the main focus of the current research work is on optimizing the charge air temperature and pressure with respect to performance and exhaust emissions.

Details

Grey Systems: Theory and Application, vol. 7 no. 3
Type: Research Article
ISSN: 2043-9377

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Article

Deepak Tiwari, Ahmad Faizan Sherwani, Mohammad Asjad and Akhilesh Arora

The purpose of this paper is to investigate the effect of four controllable parameters (fuel mixture, evaporation bubble point temperature, expander inlet temperature and…

Abstract

Purpose

The purpose of this paper is to investigate the effect of four controllable parameters (fuel mixture, evaporation bubble point temperature, expander inlet temperature and condensation dew point temperature) of a solar-driven organic Rankine cycle (ORC) on the first-law efficiency, the exergetic efficiency, the exergy destruction and the volume flow ratio (expander outlet/expander inlet).

Design/methodology/approach

Nine experiments as per Taguchi’s standard L9 orthogonal array were performed on the solar-driven ORC. Subsequently, multi-response optimization was performed using grey relational and principal component analyses.

Findings

The results revealed that the grey relational analysis along with the principal component analysis is a simple as well as effective method for solving the multi-response optimization problem and it provides the optimal combination of the solar-driven ORC parameters. Further, the analysis of variance was also employed to identify the most significant parameter based on the percentage of contribution of each cyclic parameter. Confirmation tests were performed to check the validity of the results which revealed good agreement between predicted and experimental values of the response variables at optimum combination of the input parameters. The optimal combination of process parameters is the set with A3 (the best fuel mixture in the context of optimal performance is 0.9 percent butane and 0.1 percent pentane by weight), B2 (evaporation bubble point temperature=358 K), C1 (condensation dew point temperature=300 K) and D3 (expander inlet temperature=370 K).

Research limitations/implications

In this research, the Taguchi-based grey relational analysis coupled with the principal components analysis has been successfully carried out, whereas for any optimized solution, it is required to have a real-time scenario that may be taken into consideration by the application of different soft computing techniques like genetic algorithm, simulated annealing, etc. The results generated are purely based on theoretical modeling, and, for further research, experimental analyses are required to consolidate the generated results.

Originality/value

This piece of research work will be helpful to users of solar energy, academicians, researchers and other concerned persons, in understanding the importance, severity and benefits obtained by the application, implementation and optimization of the cyclic parameters of the solar-driven ORC.

Details

Grey Systems: Theory and Application, vol. 7 no. 2
Type: Research Article
ISSN: 2043-9377

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Article

Vijay Kumar Meena and Nagahanumaiah

The purpose of this paper is to optimise the electro‐discharge machining (EDM) parameters and investigate feasibility of using direct metal laser sintering (DMLS) parts as…

Abstract

Purpose

The purpose of this paper is to optimise the electro‐discharge machining (EDM) parameters and investigate feasibility of using direct metal laser sintering (DMLS) parts as EDM electrodes.

Design/methodology/approach

In this paper the effects of discharge current, pulse‐on‐time, flushing pressure are optimized for minimum tool wear rate (TWR), maximum metal removal rate (MRR) and minimum surface roughness (Ra). Taguchi‐based L9 orthogonal array has been used for performing experiments on EDM machining of EN 24 steel using DMLS electrodes. The grey relational analysis combined with ANOVA techniques have been employed to determine the optimal level as well as their significance.

Findings

Experimental results have shown that the performance characteristics of the EDM process (TWR, MRR and surface roughness) using DMLS electrode can be quantified and controlled effectively by grey relational approach presented in the study. Current is found to be the most affective parameter in EDM machining using DMLS electrode. Excessive DMLS tool (electrode) wear was also reported, which limits the use of DMLS tool for EDM machining and it has been found out that porosity (which was about 20 per cent) was one of the primary cause.

Research limitations/implications

This paper was focused on understanding the effects of important EDM parameters on three performance characteristics (TWR, MRR and surface roughness). While this study identifies that DMLS electrode wear rate is high and porosity could be one of the main cause, presently it does not cover the investigations on reducing the porosity level and its implications.

Practical implications

The DMLS material had shown huge potential to be used as EDM electrode. The current investigation established a structured experimental approach to understand the effects of EDM parameters on multi response characteristics. The results derived from this study helps to focus future research on two aspects including enriching the copper content and reducing the porosity level, thereby the benefits of lead time reduction in EDM electrode making could be realized.

Originality/value

The previous research attempts were not focussed on optimising the EDM machining process using rapid tooling electrodes. With the best of author's knowledge none of the researchers have reported these aspects especially for DMLS electrodes. Application of grey relational analysis for performance evaluation of rapid tooling‐based EDM electrodes (DMLS electrodes) appear to be completely new.

Details

Rapid Prototyping Journal, vol. 12 no. 4
Type: Research Article
ISSN: 1355-2546

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Article

Shunmugesh K. and Panneerselvam Kavan

This paper aims to attempt to use grey relational analysis (GRA) coupled with Taguchi technique for the optimization of machining parameters (cutting speed, feed rate and…

Abstract

Purpose

This paper aims to attempt to use grey relational analysis (GRA) coupled with Taguchi technique for the optimization of machining parameters (cutting speed, feed rate and drill bit type) with multiple performance characteristics of delamination factor, surface roughness and circularity in drilling of carbon fiber-reinforced polymer (CFRP) along the fiber direction.

Design/methodology/approach

Machining trials involved drilling of 6-mm diameter holes on 8-mm-thick CFRP plates was performed according to L27 (313) Taguchi’s orthogonal array technique using the drill material of high speed steel (HSS), Titanium Nitride (TiN) and Titanium Aluminium Nitride (TiAlN). Analysis of variance has been used find the effect, percentage contribution and significance of the process parameters, namely, cutting speed, feed rate and drill bit type.

Findings

The Taguchi technique is combined with the GRA to find the optimum process parameter which minimizes the delamination factor, surface roughness and circularity within the range of parameters investigated. The effective implementation of the hybrid approach helps to produce quality and defect free holes.

Originality/value

Experimental investigation on delamination factor, surface roughness and circularity in drilling of CFRP along the fiber direction using Taguchi-GRA was seldom reported.

Details

Pigment & Resin Technology, vol. 46 no. 1
Type: Research Article
ISSN: 0369-9420

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Article

Senthilnathan T., Sujay Aadithya B. and Balachandar K.

This study aims to predict the mechanical properties such as equivalent tensile strength and micro-hardness of friction-stir-welded dissimilar aluminium alloy plates AA…

Abstract

Purpose

This study aims to predict the mechanical properties such as equivalent tensile strength and micro-hardness of friction-stir-welded dissimilar aluminium alloy plates AA 6063-O and AA 2014-T6, using artificial neural network (ANN).

Design/methodology/approach

The ANN model used for the experiment was developed through back propagation algorithm. The input parameter of the model consisted of tool rotational speed and weld-traverse speed whereas the output of the model consisted of mechanical properties (tensile strength and hardness) of the joint formed by friction-stir welding (FSW) process. The ANN was trained for 60% of the experimental data. In addition, the impact of the process parameters (tool rotational speed and weld-traverse speed) on the mechanical properties of the joint was determined by Taguchi Grey relational analysis.

Findings

Subsequently, testing and validation of the ANN were done using experimental data, which were not used for training the network. From the experiment, it was inferred that the outcomes of the ANN are in good agreement with the experimental data. The result of the analyses showed that the tool rotational speed has more impact than the weld-traverse speed.

Originality/value

The developed neural network can be used to predict the mechanical properties of the weld. Results indicate that the network prediction is similar to the experiment results. Overall regression value computed for training, validation and testing is greater than 0.9900 for both tensile strength and microhardness. In addition, the percentage error between experimental and predicted values was found to be minimal for the mechanical properties of the weldments. Therefore, it can be concluded that ANN is a potential tool for predicting the mechanical properties of the weld formed by FSW process. Similarly, the results of Taguchi Grey relational analysis can be used to optimize the process parameters of the weld process and it can be applied extensively to ascertain the most prominent factor. The results of which indicates that rotational speed of 1,270 rpm and traverse speed of 30 mm/min are to be the optimized process parameters. The result also shows that tool rotational speed has more impact on the mechanical properties of the weld than that of traverse speed.

Details

World Journal of Engineering, vol. 17 no. 4
Type: Research Article
ISSN: 1708-5284

Keywords

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Article

Sahil Sharma, Umesh Kumar Vates and Amit Bansal

In the current exploration, the machinability of three different nickel-based super-alloy materials (Inconel 625, Inconel 718 and Nimonic 90) was experimentally…

Abstract

Purpose

In the current exploration, the machinability of three different nickel-based super-alloy materials (Inconel 625, Inconel 718 and Nimonic 90) was experimentally investigated by using a die-sinking electrical discharge machining (EDM). The effect of changing important input process parameters such as pulse on time (Ton), off time (Toff), peak current (Ip) and tool rotation (TR) was investigated to get optimum machining characteristics such as material removal rate, roughness, electrode wear rate and overcut.

Design/methodology/approach

Experimentation has been performed by using Taguchi L9 orthogonal design. An integrated route of fuzzy and grey relational analysis approach with Taguchi’s philosophy has been intended for the simultaneous optimization of machining output parameters.

Findings

The most approbatory factors for machining setting have been attained as: (Ton = 100 µs, Toff = 25 µs, Ip = 14 A, TR = 725 rpm) for machining of Inconel 625 and Inconel 718; and (Ton = 100 µs, Toff = 75 µs, Ip = 14 A, TR = 925 rpm) for machining of the Nimonic 90 material. Peak current has been observed as an overall influencing factor to achieve better machining process. Microstructural study through SEM has also been carried out to figure out the surface morphology for the EDMed Ni-based super alloys.

Originality/value

The proposed machining variables and methodology has never been presented for Nimonic 90 alloy on die-sinking EDM.

Details

World Journal of Engineering, vol. 18 no. 1
Type: Research Article
ISSN: 1708-5284

Keywords

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Article

Sahil Sharma, Umesh Kumar Vates and Amit Bansal

In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to…

Abstract

Purpose

In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to investigate the impact of three input machining factors – current (I), pulse on time (Ton) and pulse off time (Toff) – on various response characteristics such as material removal rate (MRR), surface roughness (Ra) and electrode wear rate (EWR).

Design/methodology/approach

A Taguchi L9 design and ANOVA were used to assess machine response characteristics. The study also involved a grey relational analysis (GRA) multi-objective technique of optimization.

Findings

For single-objective performance, the most appropriate machining factors for achieving the best performance were attained as: MRR (I = 20 A, Ton = 200 µs and Toff = 45 µs), Ra (I = 14 A, Ton = 100 µs and Toff = 25 µs) and EWR (I = 17 A, Ton = 150 µs and Toff = 45 µs). The proposed grey relational approach provided the optimal settings (i.e. 14 A I, 100 µs Ton and 25 µs Toff) for the variables used to calculate the predicted and experimental results. Also, a confirmation test indicated that the final experimental grey relational grade value was enhanced when the experimentation was performed at optimal setting.

Originality/value

To the best of the authors’ knowledge, the present work is the first to examine the proposed machining variables (i.e. current, pulse on time and pulse off time) in relation to the optimization technique of GRA for a Nimonic 90 alloy using a die-sinking electric discharge machining method.

Details

World Journal of Engineering, vol. 18 no. 1
Type: Research Article
ISSN: 1708-5284

Keywords

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Article

Vinayambika S. Bhat, Shreeranga Bhat and E. V. Gijo

The primary aim of this article is to ascertain the modalities of leveraging Lean Six Sigma (LSS) for Industry 4.0 (I4.0) with special reference to the process industries…

Abstract

Purpose

The primary aim of this article is to ascertain the modalities of leveraging Lean Six Sigma (LSS) for Industry 4.0 (I4.0) with special reference to the process industries. Moreover, it intends to determine the applicability of simulation-based LSS in the automation of the mineral water industry, with special emphasis on the robust design of the control system to improve productivity and performance.

Design/methodology/approach

This study adopts the action research methodology, which is exploratory in nature along with the DMAIC (define-measure-analyze-improve-control) approach to systematically unearth the root causes and to develop robust solutions. The MATLAB simulation software and Minitab statistical software are effectively utilized to draw the inferences.

Findings

The root causes of critical to quality characteristic (CTQ) and variation in purity level of water are addressed through the simulation-based LSS approach. All the process parameters and noise parameters of the reverse osmosis (RO) process are optimized to reduce the errors and to improve the purity of the water. The project shows substantial improvement in the sigma rating from 1.14 to 3.88 due to data-based analysis and actions in the process. Eventually, this assists the management to realize an annual saving of 20% of its production and overhead costs. This study indicates that LSS can be applicable even in the advent of I4.0 by reinforcing the existing approach and embracing data analysis through simulation.

Research limitations/implications

The limitation of this research is that the inference is drawn based on a single case study confined to process industry automation. Having said that, the methodology deployed, scientific information related to optimization, and technical base established can be generalized.

Originality/value

This article is the first of its kind in establishing the integration of simulation, LSS, and I4.0 with special reference to automation in the process industry. It also delineates the case study in a phase-wise manner to explore the applicability and relevance of LSS with I4.0. The study is archetype in enabling LSS to a new era, and can act as a benchmark document for academicians, researchers, and practitioners for further research and development.

Details

International Journal of Quality & Reliability Management, vol. 38 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

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Article

Bobby Oedy Pramoedyo Soepangkat, Rachmadi Norcahyo, Pathya Rupajati, Mohammad Khoirul Effendi and Helena Carolina Kis Agustin

The purpose of this paper is to investigate prediction and optimization of multiple performance characteristics in the wire electrical discharge machining (wire-EDM…

Abstract

Purpose

The purpose of this paper is to investigate prediction and optimization of multiple performance characteristics in the wire electrical discharge machining (wire-EDM) process of SKD 61 (AISI H13) tool steel.

Design/methodology/approach

The experimental studies were conducted under varying wire-EDM process parameters, which were arc on time, on time, open voltage, off time and servo voltage. The optimized responses were recast layer thickness (RLT), surface roughness (SR) and surface crack density (SCD). Arc on time was set at two different levels, whereas the other four parameters were set at three different levels. Based on Taguchi method, an L18 mixed-orthogonal array was selected for the experiments. Further, three methods, namely grey relational analysis (GRA), backpropagation neural network (BPNN) and genetic algorithm (GA), were applied separately. GRA was performed to obtain a rough estimation of optimum drilling parameters. The influences of drilling parameters on multiple performance characteristics were determined by using percentage contributions. BPNN architecture was determined to predict the multiple performance characteristics. GA method was then applied to determine the optimum wire-EDM parameters.

Findings

The minimum RLT, SR and SCD could be obtained by setting arc on time, on time, open voltage, off time and servo voltage at 2 ms, 3 ms, 90 volt, 10 ms and 38 volt, respectively. The experimental confirmation results showed that BPNN-based GA optimization method could accurately predict and significantly improve all of the responses.

Originality/value

There were no publications regarding multi-response optimization using a combination of GRA and BPNN-based GA methods during wire-EDM process available.

Details

Multidiscipline Modeling in Materials and Structures, vol. 15 no. 5
Type: Research Article
ISSN: 1573-6105

Keywords

1 – 10 of 185