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An Empirical Study of the Implementation of an Integrated Ergo-Green-Lean Framework: A Case Study

Author

Listed:
  • Mohammad Kanan

    (Industrial Engineering Department, Jeddah College of Engineering, University of Business and Technology, Jeddah 21448, Saudi Arabia)

  • Ansa Rida Dilshad

    (Department of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore 54000, Pakistan)

  • Sadaf Zahoor

    (Department of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore 54000, Pakistan)

  • Amjad Hussain

    (Department of Mechanical Engineering, University of Engineering and Technology, Lahore 54890, Pakistan)

  • Muhammad Salman Habib

    (Department of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore 54000, Pakistan)

  • Amjad Mehmood

    (Department of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore 54000, Pakistan)

  • Zaher Abusaq

    (Industrial Engineering Department, Jeddah College of Engineering, University of Business and Technology, Jeddah 21448, Saudi Arabia)

  • Allam Hamdan

    (Department of Accounting and Economics, College of Business and Finance, Ahlia University, Manama P.O. Box 10878, Bahrain)

  • Jihad Asad

    (Department of Physics, Faculty of Applied Sciences, Palestine Technical University-Kadoorie, Tulkarm P305, Palestine)

Abstract

The implementation of lean manufacturing to increase productivity often neglects the impact on the environment and the well-being of employees. This can result in negative consequences such as environmental harm and poor employee satisfaction. To address this issue, an integrated ergo-green-lean conceptual model was developed in the literature. However, no case study has been conducted to support this model. Therefore, this research aims to investigate the practical outcomes of implementing the integrated framework in an automobile parts industry. Key performance indicators (KPIs) were identified, including ergonomic risk score, job satisfaction, carbon footprint emission both from direct energy consumption and material wastage, cycle time, lead time, die setup time, and rejection rate. Various assessment techniques were employed, such as the rapid entire body assessment (REBA) with the Standard Nordic Questionnaire (SNQ), job stress survey, carbon footprint analysis (CFA), and value stream mapping (VSM) to evaluate the KPIs at the pre- and post-intervention phases. The results demonstrate significant improvements in job satisfaction (49%), improved REBA score of 10 postures with very high risk numbers by 100%, a 30.3% and 19.2% decrease in carbon emissions from energy consumption and material wastage, respectively, a 45% decrease in rejection rate at the customer end, a 32.5% decrease in in-house rejection rate, a 15.5% decrease in cycle time, a 34.9% decrease in lead time, and a 21% decrease in die setup time. A Python regression model utilizing sklearn, pandas, and numpy was created to assess the relationship between process improvement and the chosen KPIs.

Suggested Citation

  • Mohammad Kanan & Ansa Rida Dilshad & Sadaf Zahoor & Amjad Hussain & Muhammad Salman Habib & Amjad Mehmood & Zaher Abusaq & Allam Hamdan & Jihad Asad, 2023. "An Empirical Study of the Implementation of an Integrated Ergo-Green-Lean Framework: A Case Study," Sustainability, MDPI, vol. 15(13), pages 1-24, June.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10138-:d:1179818
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    References listed on IDEAS

    as
    1. Muhammad Wasim Jan Khan & Muhammad Khalique, 2014. "An Overview of Small and Medium Enterprises in Malaysia and Pakistan: Past, Present and Future Scenario," Business and Management Horizons, Macrothink Institute, vol. 2(2), pages 38-49, December.
    2. Zaher Abusaq & Sadaf Zahoor & Muhammad Salman Habib & Mudassar Rehman & Jawad Mahmood & Mohammad Kanan & Ray Tahir Mushtaq, 2023. "Improving Energy Performance in Flexographic Printing Process through Lean and AI Techniques: A Case Study," Energies, MDPI, vol. 16(4), pages 1-15, February.
    3. Vargas, Luis G., 1990. "An overview of the analytic hierarchy process and its applications," European Journal of Operational Research, Elsevier, vol. 48(1), pages 2-8, September.
    4. Mohammad Kanan & Muhammad Salman Habib & Tufail Habib & Sadaf Zahoor & Anas Gulzar & Hamid Raza & Zaher Abusaq, 2022. "A Flexible Robust Possibilistic Programming Approach for Sustainable Second-Generation Biogas Supply Chain Design under Multiple Uncertainties," Sustainability, MDPI, vol. 14(18), pages 1-32, September.
    5. Zaher Abusaq & Muhammad Salman Habib & Adeel Shehzad & Mohammad Kanan & Ramiz Assaf, 2022. "A Flexible Robust Possibilistic Programming Approach toward Wood Pellets Supply Chain Network Design," Mathematics, MDPI, vol. 10(19), pages 1-27, October.
    6. R. Anthony Inman & Kenneth W. Green, 2018. "Lean and green combine to impact environmental and operational performance," International Journal of Production Research, Taylor & Francis Journals, vol. 56(14), pages 4802-4818, July.
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