Ishfaq, Kashif; Asad, Muhammad; Ashraf, Waqar Muhammad; Sana, Muhammad; Anwar, Saqib; Zhang, Wei; Dua, Vivek; (2024) Towards artificial intelligence empowered performance enhancement of EDM process using nano-graphene mixed bio-dielectric supporting the carbon neutrality and sustainable development. Journal of Cleaner Production , 457 , Article 142482. 10.1016/j.jclepro.2024.142482. (In press).

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Abstract

The growing population with every passing day sets an alarming situation with respect to the conservation climate protocols. The increasing needs of society also demand a significant enhancement in the manufacturing capacity to augment the situation. However, it’s a stringent requirement of the hour to propose sustainable and clean manufacturing processes to realize the goal of carbon neutrality to support a healthy life on the earth. Specifically, the processes that are energy intensive like electric discharge machining (EDM) are of serious concern regarding sustainability viewpoint. The role of the said process cannot be essentially eliminated as advent of new materials of superior characteristics demand the application of EDM for accurate cutting of intricate profiles. Nevertheless, the commonly used oil-based dielectric (kerosene) in EDM releases aerosol, deposit particles, oxides of carbon (CO2 & CO), thus contributing to the environmental contamination. It is pertinent to mention that industries are compelled to tune their processes to achieve the goals of Net-Zero. Therefore, this study thoroughly investigates the potential of nano-graphene mixed rice bran oil to make the EDM process cleaner and sustainable which has never been investigated so far. Moreover, the process has been successfully modeled using artificial neural network (ANN) and optimized by non-dominated sorting genetic algorithm-II (NSGA-II) which is another novel aspect of this study as it eradicates the need of extensive experimentation. Experimentation has been performed via Taguchi’s experimental strategy followed by a detailed explanation of the findings based on process physics. In comparison to the traditional dielectric an improvement of 98.8% in material removal rate (MRR) and 93.9% reduction in specific energy consumption (SEC) are realized if the said novel combination is applied without compromising the quality. CO2 emissions determined for both rice bran oil and kerosene oil have revealed that rice bran oil provides 99.96% lesser CO2 emission in comparison to its counterpart.

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