Implementation of lean techniques for sustainable workflow process in Indian motor manufacturing unit

  • Mayur Mahajan
  • , Kezia Bindu Chistopher
  • , Harshan
  • , H. C. Shiva Prasad*
  • *Corresponding author for this work

    Research output: Contribution to journalConference articlepeer-review

    15 Citations (Scopus)

    Abstract

    The process of material movement in the motor factory while transference of raw material from the supplier to stock unergonomically designed while loading and unloading using a heavy corrugated box. There is a need for improving the process for a sustainable materials movement and minimizing the material handling wastage. This research study uses a lean principle of manufacturing that is well accepted such as chalk circle exercise (seven mudas of lean principles), by analyzing the spaghetti diagram that minimizes wastes process. To minimize the usage of the corrugated box and deforestation sustainable metallic returnable pallets is ergonomically designed for the material handling. The findings from this research, a reduction of material handling time from 67 hours to 30.1hours per annum was achieved, with physical movement from 152 kms to 117 kms per annum and solid waste from 464 kg to zero. As this research is action research with the corrective action plan and by developing a sustainable returnable packaging that reduced the lean waste in the handling of raw materials at motor manufacturing. The implication of this study is reducing the corrugated packaging material from getting wasted every time by enhancing the material handling productivity and movement of material efficiently with an eco-environmentally friendly product.

    Original languageEnglish
    Pages (from-to)1196-1204
    Number of pages9
    JournalProcedia Manufacturing
    Volume35
    DOIs
    Publication statusPublished - 01-01-2019
    Event2nd International Conference on Sustainable Materials Processing and Manufacturing, SMPM 2019 - Sun City, South Africa
    Duration: 08-03-201910-03-2019

    All Science Journal Classification (ASJC) codes

    • Industrial and Manufacturing Engineering
    • Artificial Intelligence

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