Modeling and Optimization of Power Consumption for Economic Analysis, Energy-Saving Carbon Footprint Analysis, and Susta
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ORIGINAL RESEARCH PAPER
Modeling and Optimization of Power Consumption for Economic Analysis, Energy-Saving Carbon Footprint Analysis, and Sustainability Assessment in Finish Hard Turning Under Graphene Nanoparticle–Assisted Minimum Quantity Lubrication Smita Padhan 1 & Lalatendu Dash 1 & Santosh Kumar Behera 1 & Sudhansu Ranjan Das 1 Received: 8 May 2020 / Revised: 19 July 2020 / Accepted: 18 August 2020 # Springer Nature Singapore Pte Ltd. 2020
Abstract The present work addresses the issue on power consumption in finish hard turning of die steel under nanofluid-assisted minimum quantity lubrication condition. This study also aims to assess the propitious role of minimum quantity lubrication using graphene nanoparticle-enriched radiator green coolant-based nano-cutting fluid for machinability improvement of hardened steel. The hard turning trials are performed based on design of experiments by considering the geometrical parameters (insert’s nose radius) and machining parameters (cutting speed, axial feed, depth of cut). Combined approach of central composite design—analysis of variance, desirability function analysis, and response surface methodology—have been subsequently employed for analysis, predictive modeling, and optimization of machining power consumption. With a motivational philosophy of “Go Green-Think Green-Act Green”, the work also deals with energy-saving carbon footprint analysis, economic analysis, and sustainability assessment under environmental-friendly nanofluid-assisted minimum quantity lubrication condition. Results showed that machining with nanofluid-minimum quantity lubrication provided an effective cooling-lubrication strategy, safer and cleaner production, environmental friendliness, and assisted to improve sustainability. Keywords Power consumption . Hard turning . AISI D3 steel . Coated tool . NFMQL . Carbon footprint analysis . Economic analysis . Sustainability assessment
Introduction With today’s technologies, one of the important challenges for manufacturing industry is to provide workpieces with specified quality characteristics in the required quantity and in the fastest and most cost-effective way possible. Nowadays, hardened steel materials ranging from 42 to 68 HRC have great demand for manufacturing of precision components to attain high mechanical performance in different engineering applications. Moreover, these materials are extensively used for manufacturing of automotive parts, bearings, dies and molds, and machine tool components requiring specific characteristics (excellent indentation resistance, relatively low ductility, * Sudhansu Ranjan Das [email protected] 1
Department of Production Engineering, Veer Surendra Sai University of Technology, Burla, Odisha 768018, India
high value of hardness-to-elastic modulus ratio, and superior abrasiveness), which makes hard to machine (Suresh et al. 2013). Traditionally, the most common method for machining the hardened steels associated with a long technological chain of time-consuming and expensive operations, as
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