The purpose of this paper is to investigate prediction and optimization of multiple performance characteristics in the wire electrical discharge machining (wire-EDM…
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.
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.
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.
There were no publications regarding multi-response optimization using a combination of GRA and BPNN-based GA methods during wire-EDM process available.
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.
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…
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.
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.
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.
To the best of the authors' knowledge, this is the first time SOM and decision tree has been applied to the WEDM process successfully.
The numerically controlled machine tool has become a very topical subject due to the current emphasis on increasing productivity and upgrading of manufacturing industry…
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.
“Productivity Partnerships”, a regulars series of demonstrations held at The 600 Centre in Shepshed, saw the UK launch of a new machine loading robot system by Fanuc Robotics. A description is given of the rail‐mounted 6‐axis robot together with some of the claimed benefits. It is a system that has been well received in the USA and two brief examples of installations from that side of the Atlantic are given.