Circular usage of waste cooking oil towards green electrical discharge machining process with lower carbon emissions

Author:

Ishfaq Kashif,Sana MuhammadORCID,Waseem Muhammad Umair,Anwar Saqib,Zia Abdul WasyORCID

Abstract

AbstractA global manufacturing community is dedicatedly striving to implement the concept of NetZero in precision cutting of difficult-to-machine materials, specifically, Inconel 617 (IN617) with due consideration to environmental protocols. The fast strain hardening issue of the said alloy during conventional processing rationalizes the application of electric discharge machining (EDM). However, EDM has been criticized for its high energy consumption and limited cutting efficiency. Moreover, conventional dielectric (kerosene) employed in EDM has drastic environmental and operator health concerns. To address the abovementioned issues, waste cooking oil (WCO) has been employed in this study which enhances the reusability of resources and minimizes the cost of the dielectric. Making the process sustainable is imperative along with continuously escalating scarcity of engineering resources. Therefore, the potential of shallow and deep cryogenically treated electrodes (SCT and DCT) has been comprehensively examined against nanofilled WCO to achieve the aforementioned objective. Three different concentrations of powder (Cp) and surfactant (Cs) to uplift the machining responses are investigated through a detailed parametric experimental design. Core machining factors such as material removal rate (MRR), surface roughness (SR), and specific energy consumption (SEC) are examined through optical and electron microscopy studies and 3D surface profilometry. Hereafter, machining factors are modelled using the artificial neural network (ANN) technique. An exceptional improvement of 80%, 25.3%, and 75.16% has been achieved in MRR, SR, and SEC respectively using nanopowder-mixed WCO against SCT brass compared to the responses’ values obtained against conventionally used kerosene. Furthermore, compared to kerosene, the maximum CO2 reduction of 79.97 ± 11.2% is achieved with WCO.

Funder

King Saud University

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3