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Energy-Based Novel Quantifiable Sustainability Value Assessment Method for Machining Processes

Author

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  • Aqib Mashood Khan

    (Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Shandong 250061, China
    College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Saqib Anwar

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Munish Kumar Gupta

    (Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Shandong 250061, China
    Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, 454080 Chelyabinsk, Russia)

  • Abdullah Alfaify

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Saqib Hasnain

    (Depertment of Mechatronics Engineering, University of Engineering and Technology Taxila, Taxila 47050, Pakistan)

  • Muhammad Jamil

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Mozammel Mia

    (Department of Mechanical Engineering, Imperial College London, London SW7 2AZ, UK)

  • Danil Yurievich Pimenov

    (Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, 454080 Chelyabinsk, Russia)

Abstract

Sustainability assessments of cooling/lubrication-assisted advanced machining processes has been demanded by environment control agencies because it is an effective management tool for improving process sustainability. To achieve an effective and efficient sustainability evolution of machining processes, there is a need to develop a new method that can incorporate qualitative indicators to create a quantifiable value. In the present research work, a novel quantifiable sustainability value assessment method was proposed to provide performance quantification of the existing sustainability assessment methods. The proposed method consists of three steps: establishing sustainable guidelines and identifying new indicators, data acquisition, and developing an algorithm, which creates the Overall Performance Assessment Indicator (OPAI) from the sustainability assessment method. In the proposed algorithm, initially, both quantitative and qualitative sustainability indicators are normalized. After weight assignment and aggregation, the OPAI is obtained. The developed algorithm was validated from three literature case studies, and optimal cutting parameters were obtained. The present methodology provides effective guidelines for a machinist to enhance process performance and achieve process optimization. The study also offers a relationship between sustainable and machining metrics for the support of industrial sustainability.

Suggested Citation

  • Aqib Mashood Khan & Saqib Anwar & Munish Kumar Gupta & Abdullah Alfaify & Saqib Hasnain & Muhammad Jamil & Mozammel Mia & Danil Yurievich Pimenov, 2020. "Energy-Based Novel Quantifiable Sustainability Value Assessment Method for Machining Processes," Energies, MDPI, vol. 13(22), pages 1-24, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:6144-:d:449681
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    References listed on IDEAS

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    1. Aqib Mashood Khan & Muhammad Jamil & Konstantinos Salonitis & Shoaib Sarfraz & Wei Zhao & Ning He & Mozammel Mia & GuoLong Zhao, 2019. "Multi-Objective Optimization of Energy Consumption and Surface Quality in Nanofluid SQCL Assisted Face Milling," Energies, MDPI, vol. 12(4), pages 1-22, February.
    2. Alberto Simboli & Andrea Raggi & Pietro Rosica, 2015. "Life Cycle Assessment of Process Eco-Innovations in an SME Automotive Supply Network," Sustainability, MDPI, vol. 7(10), pages 1-16, October.
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    Cited by:

    1. Ardamanbir Singh Sidhu & Sehijpal Singh & Raman Kumar & Danil Yurievich Pimenov & Khaled Giasin, 2021. "Prioritizing Energy-Intensive Machining Operations and Gauging the Influence of Electric Parameters: An Industrial Case Study," Energies, MDPI, vol. 14(16), pages 1-39, August.
    2. Luka Celent & Marko Mladineo & Nikola Gjeldum & Marina Crnjac Zizic, 2022. "Multi-Criteria Decision Support System for Smart and Sustainable Machining Process," Energies, MDPI, vol. 15(3), pages 1-22, January.
    3. Nikolaos E. Karkalos & Panagiotis Karmiris-Obratański & Rafał Kudelski & Angelos P. Markopoulos, 2021. "Experimental Study on the Sustainability Assessment of AWJ Machining of Ti-6Al-4V Using Glass Beads Abrasive Particles," Sustainability, MDPI, vol. 13(16), pages 1-18, August.

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