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Electric discharge machining (EDM) is a thermal-based machining process where material removal in the form of melting and vaporization occurs due to repeated electrical sparks between electrode and workpiece. EDM process finds wide applications in the manufacturing, automobile, aerospace, and biomedical industries due to its remarkable feature of producing complex geometrical shapes like molds, tools, and dies. Irrespective of materials hardness. In this review, the paper author has given details about a new advancement made in the EDM process, which is low-frequency vibration-assisted Die Sinking EDM. There is also a brief introduction of vibration setups that can be used to generate low-frequency vibration. There is also some discussion about various optimization techniques (e.g., TOPSIS, MOORA, GRA) used to optimize the process parameters that are current, frequency, pulse on time, and pulse off time to get better response parameters ( MRR, TWR, and SR). Besides, there is extensive discussion about the effect of current, pulse on time, pulse off time and frequency on MRR, SR, and TWR. In the end, some discussion on the effect of low-frequency vibration on surface topography is also discussed.

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Funding Liquidity is the key component of loanable funds of the bank. Sufficient liquidity also boosts banks’ ability to pay-off its dues timely but at the same time it has been proven to be a significant determinant of various historical banking sector crises all over the world. However, there exists very weak empirical evidence suggesting a clear relationship between funding liquidity and bank lending growth (BLG). We have attempted to address this gap by empirically testing the impact of bank capital, funding liquidity and their interaction variable on the BLG using a dataset of 59 commercial banks operating in India for the period 2006 to 2018 consisting of 21 public sector banks, 18 private sector banks and 20 foreign banks. An attempt has been made to examine the interactive impact of the bank capital and funding liquidity ratio on BLG rate using system GMM approach. Our model reveals a positive and significant impact of capital funding, indicating induction of capital in bank leads to higher growth in BLG rate. The results also suggest that the interaction impact of funding liquidity and bank capital on the bank lending growth is significantly negative. Further, a higher capital induction neutralises the overall impact of funding liquidity on the bank lending growth. The study provides implications for academicians and policy makers to comprehend the role of funding liquidity.

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