وثيقة

Machining of Carbon Steel under Aqueous Environment : Investigations into Some Performance Measures

مؤلف
وكيل مرتبط
Hussain, Ghulam , مؤلف مشارك
Shehbaz, Tauheed, مؤلف مشارك
Muhammad, Riaz, مؤلف مشارك
Aamir, Muhammad, مؤلف مشارك
Giasin, Khaled, مؤلف مشارك
Pimenov, Danil Yurievich, مؤلف مشارك
عنوان الدورية
Coatings
العدد
Volume 12 - Issue 8
دولة النشر
Switzerland
مكان النشر
MDPI, Basel, Switzerland
الناشر
MDPI
تاريخ النشر
2022
اللغة
إنجليزي
الملخص الإنجليزي
Abstract: In this study, a new machining approach (aqueous machining) is applied for mill machining and its performance is compared with traditional wet machining. AISI 1020 steel is employed as the test material and Taguchi statistical methodology is implemented to analyze and compare the performance of the two machining approaches. The cutting speed, feed rate, and depth of cut were the machining parameters used for both types of machining, while the selected response variables were surface roughness and hardness. Temperature variations were also recorded in aqueous machining. Compared with wet machining, aqueous machining resulted in lower surface roughness (up to 13%) for the same operating conditions and about 14% to 16% enhancement in hardness due to the formation of finer pearlite, as revealed by the microstructure analysis. Compared to the parent unmachined surface, the hardness of machined surfaces was 24% to 31% higher in wet machining and 44% to 51% higher in aqueous machining. Another benefit of aqueous machining was the energy gain, which ranged from 718 to 8615.96 J. This amount of heat energy can be used as waste heat for preheating domestic hot water, running the organic Rankine cycle with waste heat and preheating the inlet saline water for desalination, vacuum desalination, etc. If successfully implemented in the future, this idea will provide a step towards achieving sustainable machining by saving lubricants and toxic wastes in addition to saving energy for secondary applications.
المجموعة
المعرف
https://digitalrepository.uob.edu.bh/id/de280c53-f9ac-46c5-8e10-69e11a65eaef