• Title of article

    Waste identification in a pipe manufacturing industry through lean concept– A case study

  • Author/Authors

    Rahman ، Md. Suman - Jessore University of Science and Technology , Tahiduzzaman ، Md. - Jessore University of Science and Technology , Kundu ، Rupom - Jessore University of Science and Technology , Juwel ، S. M. Nuruzzaman - Jessore University of Science and Technology , Karim ، Md. Rubayet - Jessore University of Science and Technology

  • Pages
    18
  • From page
    306
  • To page
    323
  • Abstract
    This study addresses the application of the lean manufacturing philosophy to the mass production sector with a focus on the plastic piping section of a selected plastic pipe manufacturing industry. In this study, the different weakness and waste of the piping section are measured by using the specific lean tools, such as Cause– Effect diagram, Pareto analysis, Time Base Mapping, and 5S. The Cause-Effect analysis shows the various root causes of the waste time and rejection of the pipes. The Time Base Mapping measures the required time needed from the raw material to finish the product dispatch. The time has reduced approximately 17 hours by eliminating or reducing the non-value added work activities. The 5S analysis is done to focus on the effective workplace organization and standard work procedure. It also simplifies the work environment, reduces all possible waste and non-value added activity while improving quality, efficiency, and safety. In this study, we have found out the various types of waste (value-added activities and non-value added activities) exist in the piping section and the possible causes behind these activities that also have proposed some recommendation for the studied process industry in order to improve the performance of the piping section.
  • Keywords
    Waste , Lean Concept , Pipe Industry , case study
  • Journal title
    Journal of Applied Research on Industrial Engineering
  • Serial Year
    2018
  • Journal title
    Journal of Applied Research on Industrial Engineering
  • Record number

    2478517