Abstract
Agile manufacturing capabilities require fast responses in workshops to cope with different demands in product geometrical features and qualities in fabricating moulds. Therefore, direct machining of complex mould features using simple shape machined electrodes with the electro-discharge machining (EDM) process, empowers the flexibility and the capacity of the enterprises and dramatically reduces lead times resulting in much more efficient production processes. In the case of machining geometrical features with characteristic dimensions in the order of few millimeters, the EDM process requires further understanding. This article focuses on investigating the influence of EDM parameters and electrode geometry on feature micro-accuracy in tool steel for mould fabrication purposes. A set of designed experiments with varying EDM process parameters such as pulsed current, open voltage, pulse time, and pulse pause time is carried out in H13 steel using differently shaped copper electrodes. Microdimensional and geometrical accuracies are the measures of response. Artificial neural network and regression models have been constructed to capture the influence of the process parameters on the geometrical feature quality such as flatness, depth, slope, width, and dimension variation between the entrance and the exit (DVEE).
Original language | English (US) |
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Pages (from-to) | 1282-1289 |
Number of pages | 8 |
Journal | Materials and Manufacturing Processes |
Volume | 24 |
Issue number | 12 |
DOIs | |
State | Published - Dec 2009 |
All Science Journal Classification (ASJC) codes
- General Materials Science
- Mechanics of Materials
- Mechanical Engineering
- Industrial and Manufacturing Engineering
Keywords
- Artificial neural network modeling
- EDM technology
- Mould making
- Process parameters