Sustainability assessment associated with surface roughness and power consumption characteristics in nanofluid MQL-assisted turning of AISI 1045 steel

  • Adel Taha Abbas
  • Munish Kumar Gupta
  • Mahmoud S. Soliman
  • Mozammel MiaEmail author
  • Hussein Hegab
  • Monis Luqman
  • Danil Yurievich Pimenov


The constant pressure on the manufacturers to innovate and implement sustainable processes has triggered researching on machining with low carbon footprint, minimum energy consumption by machine tools, and improved products at the lowest cost—this is exactly done in this paper. Herein, the advanced cooling lubrication, i.e., nanofluid assistance, besides dry and flood cooling, during machining has been experimented, and used as the basis for sustainability assessment. This assessment is carried out in respect of surface quality and power consumption as well as the impact on environment, cost of machining, management of waste, and finally the safety and health issues of operators. For a better sustainability, a systematic optimization has been performed. In addition, the solution for an improved machinability has been proposed along with the statistically verified mathematical models of machining responses. Results showed that the nanofluid minimum quantity lubrication showed the most sustainable performance with a total weighted sustainability index 0.7, and it caused the minimum surface roughness and power consumption. The highest desirable (desirability = 0.9050) optimum results are the cutting speed of 116 m/min, depth of cut 0.25 mm, and feed rate of 0.06 mm/rev. Furthermore, a lower feed rate is suggested for better surface quality while for reduced power consumption the lower control factors are better.


Steel AISI 1045 Sustainability assessment Optimization Nanofluid Power consumption Surface roughness 



The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group no. (RG-1439-020).


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© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical Engineering, College of EngineeringKing Saud UniversityRiyadhSaudi Arabia
  2. 2.Key Laboratory of High Efficiency and Clean Mechanical Manufacturing, Ministry of Education, School of Mechanical EngineeringShandong UniversityJinanPeople’s Republic of China
  3. 3.University Center for Research & DevelopmentChandigarh UniversityGharuanIndia
  4. 4.Mechanical and Production EngineeringAhsanullah University of Science and TechnologyDhakaBangladesh
  5. 5.Mechanical Design and Production Engineering DepartmentCairo UniversityGizaEgypt
  6. 6.Department of Automated Mechanical EngineeringSouth Ural State UniversityChelyabinskRussia

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