A new methodology for predicting quantity of agglomeration between electrodes in PMEDM environment

• Main Authors: Abbas, Mohammed Abdulridha, Lajis, Mohd Amri, Abdul Ridha, Ghassan Shaker
• Format: Article
• Language: English
• Published: IAEME Publication 2019
• Subjects: QD71-142 Analytical chemistry
• Online Access: http://eprints.uthm.edu.my/4449/1/AJ%202019%20%28276%29.pdf; http://eprints.uthm.edu.my/4449/
• Institution: Universiti Tun Hussein Onn Malaysia

The powder mixed-EDM (PMEDM) is a prominent field in precise manufacturing where the material removal operation depends on the electrical erosion mechanism between electrodes in this environment. Prior studies strived to improve the performance of this field, but the obstacles represented by controlling the parameters of this environment created difficulties for the researchers. One of the most important results of this situation is the agglomeration problem between the electrode tool and the workpiece that leads to the collapse of the spark. Thus, the performance of PMEDM environment declines. This study covers the primary reasons for the occurrence of the agglomeration phenomenon in PMEDM. In addition, this study proposes a new methodology to compute the quantity of agglomeration through introducing new hypotheses and procedures. Following from here, the proposed methodology is able to determine the dimensions of the recast layer zone and the density of this zone. Energy Dispersive Spectroscopy (EDS) or Optical Emission Spectrometry (OES) plays an important role in specifying the weight percentage of workpiece elements before and after machining in PMEDM. This study adopted a previous study which observed D2 steel before and after machining in PMEDM by using OES. Furthermore, it applies virtual dimensions of the melting area and the recast layer zone for proving this proposed methodology. Therefore, the total agglomeration for D2 steel is 0.003942529 mg while the active agglomeration of tungsten, carbon, molybdenum, and manganese is 0.001971264 mg. Moreover, the square of the correlation factor (R-sq) and R-sq (adj.) resulting from multiple linear regression analysis for the total agglomeration of D2 steel are 99.36% and 98.97%, respectively. Finally, this methodology presents a new mechanism to specify the performance of PMEDM through adopting the agglomeration ratio as a new criterion. Thus, the agglomeration ratio according to the proposed methodology came up to (50%) which implies that the agglomeration did not exceed the critical stage.