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1 – 10 of 116Bobby 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.
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.
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Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture)…
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.
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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.
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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.
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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.