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Article
Publication date: 7 August 2019

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) process of…

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

Article
Publication date: 1 December 2004

James Brink, Alex Lee, David Anderson and Karthik Ramani

This paper describes algorithms and software for decomposing CAD models for a new mold manufacturing process called WirePATH™, which uses wire electrical discharge machining (EDM…

Abstract

This paper describes algorithms and software for decomposing CAD models for a new mold manufacturing process called WirePATH™, which uses wire electrical discharge machining (EDM) to reduce mold fabrication time. A decomposition strategy has been developed to account for the limitations of wire EDM. During decomposition, CAD models are separated into manufacturable segments and then layered if they contain curved or relatively flat sloped surfaces because wire EDM is limited to steeply sloped ruled surfaces. A new algorithm for direct adaptive layering of CAD models is developed. The algorithm analyzes surface error by comparing line segments against actual curves from the model surface. Also, the maximum angle needed to produce each layer is checked, and, in some cases, the layers are reconstructed to conform to the maximum angle.

Details

Rapid Prototyping Journal, vol. 10 no. 5
Type: Research Article
ISSN: 1355-2546

Keywords

Content available
Article
Publication date: 1 July 2006

81

Abstract

Details

Aircraft Engineering and Aerospace Technology, vol. 78 no. 4
Type: Research Article
ISSN: 0002-2667

Keywords

Content available
Article
Publication date: 1 April 2003

89

Abstract

Details

Aircraft Engineering and Aerospace Technology, vol. 75 no. 2
Type: Research Article
ISSN: 0002-2667

Keywords

Content available
Article
Publication date: 1 December 2004

196

Abstract

Details

Aircraft Engineering and Aerospace Technology, vol. 76 no. 6
Type: Research Article
ISSN: 0002-2667

Keywords

Article
Publication date: 11 July 2022

Meltem Altin Karataş

Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture)…

185

Abstract

Purpose

Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture), durability, toughness, hardness and dimensional stability, which is difficult to machine with traditional fabrication methods. To overcome these difficulties, wire electrical discharge machining (WEDM), one of the modern manufacturing methods, is used.

Design/methodology/approach

Main performance criteria in WEDM; material removal rate (MRR), cutting speed, surface roughness, cutting width (kerf) and wire wear rate. In this study, the effect of processing parameters on kerf and MRR because of processing IN718 in WEDM was investigated. Machining parameters, voltage, wire feed rate and dielectric fluid pressure were determined. Deionized water was used as a dielectric fluid and 0.3 mm brass wire was used as wire in the experiments. Gray Relational Analysis (GRA), which is one of the multi-criteria decision-making methods, has been applied for the optimization of the machining parameters in the cutting process with the WEDM. Analysis of variance (ANOVA) was used to determine the effect percentages of the cut-off parameters.

Findings

The parameter with the highest effect was determined as tension with a rate of 76.95% for kerf and 91.21% for MRR.

Originality/value

The novel approach uses Taguchi-based GRA optimization as a result of cutting IN718 with WEDM, reducing cost and time consumption.

Details

Multidiscipline Modeling in Materials and Structures, vol. 18 no. 4
Type: Research Article
ISSN: 1573-6105

Keywords

Content available
Article
Publication date: 16 May 2008

105

Abstract

Details

Aircraft Engineering and Aerospace Technology, vol. 80 no. 3
Type: Research Article
ISSN: 0002-2667

Article
Publication date: 26 July 2011

Mohamad Saraee, Seyed Vahid Moosavi and Shabnam Rezapour

This paper aims to present a practical application of Self Organizing Map (SOM) and decision tree algorithms to model a multi‐response machining process and to provide a set of…

Abstract

Purpose

This paper aims to present a practical application of Self Organizing Map (SOM) and decision tree algorithms to model a multi‐response machining process and to provide a set of control rules for this process.

Design/methodology/approach

SOM is a powerful artificial neural network approach used for analyzing and visualizing high‐dimensional data. Wire electrical discharge machining (WEDM) process is a complex and expensive machining process, in which there are a lot of factors having effects on the outputs of the process. In this work, after collecting a dataset based on a series of designed experiments, the paper applied SOM to this dataset in order to analyse the underlying relations between input and output variables as well as interactions between input variables. The results are compared with the results obtained from decision tree algorithm.

Findings

Based on the analysis of the results obtained, the paper extracted interrelationships between variables as well as a set of control rules for prediction of the process outputs. The results of the new experiments based on these rules, clearly demonstrate that the paper's predictions are valid, interesting and useful.

Originality/value

To the best of the authors' knowledge, this is the first time SOM and decision tree has been applied to the WEDM process successfully.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

Article
Publication date: 12 November 2020

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

Article
Publication date: 1 January 1984

Khong Heng Poh

The numerically controlled machine tool has become a very topical subject due to the current emphasis on increasing productivity and upgrading of manufacturing industry. This…

Abstract

The numerically controlled machine tool has become a very topical subject due to the current emphasis on increasing productivity and upgrading of manufacturing industry. This paper reviews the current applications of NC machine tools in Singapore. It also takes a look at the future directions which NC is likely to develop, particularly in the area of computer aided manufacture, and examines the role of the production engineer within this new environment.

Details

International Journal of Operations & Production Management, vol. 4 no. 1
Type: Research Article
ISSN: 0144-3577

Keywords

1 – 10 of 116