Abstract

As an established tool-based micro-machining technique, micro electrical discharge machining (μEDM) has received widespread attention from academia and industry for its capability of producing intricate micro-scale structures and features on various difficult-to-cut materials. However, assurance of the as-built surface quality and consistency has been a challenge due to the complex interactions among machining parameters and the unpredictable variability of material properties and the discharge process. In this paper, an efficient closed-loop control methodology based on an innovative application of on-machine metrology (OMM) and in-process roughness prediction (IPRP) is proposed for automatically ensuring the μEDM surface quality. The work takes into consideration process fundamentals related to size and distribution of craters by means of single crater experiments and pulse discrimination studies in order to analyze the influence of actual energy parameter on the evolving surface roughness. The OMM enables accurate in situ surface characterization while the IPRP, which is built on an online Bayesian regression model, allows for the prediction of surface quality according to the monitored process features. This IPRP model presents an increased predictive performance and confidence when more OMM data become available. Depending on the acquired quality outputs, a two-step quality control strategy involving energy adaptation and discharge stability regulation is implemented. This novel control strategy has proven to achieve a consistent areal surface roughness with variations smaller than 0.1 μm for a specific material and dielectric combination in μEDM milling.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call