IDEAS home Printed from https://ideas.repec.org/a/avb/jitdet/2020p16-22.html
   My bibliography  Save this article

Implementation of Lean Methodology on the Main Assembly Line of an Automotive Plant to Enhance Productivity

Author

Listed:
  • Amber Iqbal

    (PNEC, National University of Sciences and Technology, Karachi, Pakistan)

  • M. Nasir Bashir

    (PNEC, National University of Sciences and Technology, Karachi, Pakistan)

  • Asna Alam

    (PNEC, National University of Sciences and Technology, Karachi, Pakistan)

  • M. Bilal Asif

    (PNEC, National University of Sciences and Technology, Karachi, Pakistan)

  • Iqra Arshad

    (PNEC, National University of Sciences and Technology, Karachi, Pakistan)

Abstract

Productivity can be enhanced by reducing wastages in a process while maintaining or increasing the amount of output. This is real work carried out in the automotive industry. In our work, we enhanced the productivity of the assembly line in an automotive plant by applying lean methodologies. There is an extensive range of tools available to remove all kinds of wastes, from which we selected the following two tools to remove waste that will enhance productivity, Value Stream Map (VSM) and Overall Equipment Effectiveness (OEE). The purpose of using VSM is that it easily highlights the bottlenecks in any existing process. For VSM we need to conduct a time and motion study to understand the structure of an organization. At the same time, OEE helps us measure the efficiency of our system being utilized. After applying these tools, we easily identified the parts which needed improvement in the process. It has reduced our cycle time of sub-assemblies by 50% and transportation time by 60%. This overall enhanced the productivity of the system by 20%. The index of OEE increased by 2%. Our work has improved the productivity of the assembly line in an automotive plant. In the future this work can be further improved by our successors for better productivity, fulfilling future customer needs.

Suggested Citation

  • Amber Iqbal & M. Nasir Bashir & Asna Alam & M. Bilal Asif & Iqra Arshad, 2020. "Implementation of Lean Methodology on the Main Assembly Line of an Automotive Plant to Enhance Productivity," Journal of ICT, Design, Engineering and Technological Science, Juhriyansyah Dalle, vol. 4(1), pages 16-22.
    • Handle: RePEc:avb:jitdet:2020:p:16-22
    DOI: 10.33150/JITDETS-4.1.4
    as

    Download full text from publisher

    File URL: https://jitdets.com/ojs/index.php/jitdets/article/view/11
    Download Restriction: no
    File URL: https://jitdets.com/ojs/index.php/jitdets/article/view/11/7
    Download Restriction: no
    File URL: https://libkey.io/10.33150/JITDETS-4.1.4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Rodrigo Romero-Silva & Sabry Shaaban, 2019. "Influence of unbalanced operation time means and uneven buffer allocation on unreliable merging assembly line efficiency," International Journal of Production Research, Taylor & Francis Journals, vol. 57(6), pages 1645-1666, March.
    2. Cheng Mei Tung, 2018. "Vertical integration for smart manufacturing-The dynamic capability perspective," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 4(2), pages 70-78.
    3. Chanawee Aueprasert & Wuthichai Wongthatsanekorn, 2016. "Application of lean technique for outpatient service time improvement in public hospital of Thailand," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 2(6), pages 183-188.
    4. Poorya Ghafoorpoor Yazdi & Aydin Azizi & Majid Hashemipour, 2018. "An Empirical Investigation of the Relationship between Overall Equipment Efficiency (OEE) and Manufacturing Sustainability in Industry 4.0 with Time Study Approach," Sustainability, MDPI, vol. 10(9), pages 1-28, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jorge Luis García Alcaraz & Adrián Salvador Morales García & José Roberto Díaz Reza & Julio Blanco Fernández & Emilio Jiménez Macías & Rita Puig i Vidal, 2022. "Machinery Lean Manufacturing Tools for Improved Sustainability: The Mexican Maquiladora Industry Experience," Mathematics, MDPI, vol. 10(9), pages 1-18, April.
    2. Mariusz Niekurzak & Wojciech Lewicki, 2025. "Optimisation of the Production Process of Ironing Refractory Products Using the OEE Indicator as Part of Innovative Solutions for Sustainable Production," Sustainability, MDPI, vol. 17(11), pages 1-27, May.
    3. Poorya Ghafoorpoor Yazdi & Aydin Azizi & Majid Hashemipour, 2019. "A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs," Sustainability, MDPI, vol. 11(5), pages 1-26, March.
    4. Federica Costa & Matthias Thürer & Alberto Portioli-Staudacher, 2023. "Heterogeneous worker multi-functionality and efficiency in dual resource constrained manufacturing lines: an assessment by simulation," Operations Management Research, Springer, vol. 16(3), pages 1476-1489, September.
    5. Giancarlo Nota & Francesco David Nota & Domenico Peluso & Alonso Toro Lazo, 2020. "Energy Efficiency in Industry 4.0: The Case of Batch Production Processes," Sustainability, MDPI, vol. 12(16), pages 1-28, August.
    6. Felix Constantin Adochiei & Radu Ciucu & Ioana Raluca Adochiei & Florin Ciprian Argatu & CiprianMarius Larco & Miron Casian, 2019. "A Data Analysis platform for high altitude bio monitoring using DEVOPS principles and time series machine learning," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 5(1), pages 18-24.
    7. Stefano Blasi & Maryam Bahrami & Elmar Engels & Alexander Gepperth, 2024. "Safe contextual Bayesian optimization integrated in industrial control for self-learning machines," Journal of Intelligent Manufacturing, Springer, vol. 35(2), pages 885-903, February.
    8. José Salvador da Motta Reis & Maximilian Espuny & Thaís Vieira Nunhes & Nilo Antonio de Souza Sampaio & Raine Isaksson & Fernando Celso de Campos & Otávio José de Oliveira, 2021. "Striding towards Sustainability: A Framework to Overcome Challenges and Explore Opportunities through Industry 4.0," Sustainability, MDPI, vol. 13(9), pages 1-28, May.
    9. C. Camilleri & A. Rochman, 2019. "Defect formation in EBM parts built at different orientation," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 5(3), pages 125-134.
    10. Romero-Silva, Rodrigo & Shaaban, Sabry & Marsillac, Erika & Laarraf, Zouhair, 2021. "The impact of unequal processing time variability on reliable and unreliable merging line performance," International Journal of Production Economics, Elsevier, vol. 235(C).
    11. Piccarozzi, Michela & Silvestri, Cecilia & Aquilani, Barbara & Silvestri, Luca, 2022. "Is this a new story of the ‘Two Giants’? A systematic literature review of the relationship between industry 4.0, sustainability and its pillars," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    12. Héctor Cañas & Josefa Mula & Francisco Campuzano-Bolarín, 2020. "A General Outline of a Sustainable Supply Chain 4.0," Sustainability, MDPI, vol. 12(19), pages 1-17, September.
    13. Shouyao Xiong & Yuanyuan Feng & Kai Huang, 2020. "Optimal MTS and MTO Hybrid Production System for a Single Product Under the Cap-And-Trade Environment," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    14. Alberuni Aziz & Subrata Talapatra & H. M. Belal, 2024. "Improving Equipment Effectiveness through Visual Stream Mapping: Some Exploratory Research Findings in the Ready-Made Garment (RMG) Sector," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(2), pages 303-324, June.
    15. Jakob Trauer & Simon Pfingstl & Markus Finsterer & Markus Zimmermann, 2021. "Improving Production Efficiency with a Digital Twin Based on Anomaly Detection," Sustainability, MDPI, vol. 13(18), pages 1-21, September.
    16. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    17. Xiaoxia Chen & Mélanie Despeisse & Björn Johansson, 2020. "Environmental Sustainability of Digitalization in Manufacturing: A Review," Sustainability, MDPI, vol. 12(24), pages 1-31, December.
    18. Orlando Durán & Paulo Andrés Durán, 2019. "Prioritization of Physical Assets for Maintenance and Production Sustainability," Sustainability, MDPI, vol. 11(16), pages 1-17, August.
    19. Jorge Luis García-Alcaraz & José Roberto Díaz Reza & Cuauhtémoc Sánchez Ramírez & Jorge Limón Romero & Emilio Jiménez Macías & Carlos Javierre Lardies & Manuel Arnoldo Rodríguez Medina, 2021. "Lean Manufacturing Tools Applied to Material Flow and Their Impact on Economic Sustainability," Sustainability, MDPI, vol. 13(19), pages 1-18, September.
    20. Oliver Kovacs, 2019. "Big IFs in Productivity-Enhancing Industry 4.0," Social Sciences, MDPI, vol. 8(2), pages 1-17, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:avb:jitdet:2020:p:16-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Juhriyansyah Dalle (email available below). General contact details of provider: https://jitdets.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.