• DocumentCode
    3539994
  • Title

    Fuzzy identification of value stream analysis tools in lean manufacturing

  • Author

    Saleh, Chairul ; Astuti, Fatma Hermining ; Purnomo, M. Ridwan Andi ; Deros, Baba Md

  • Author_Institution
    Dept. of Ind. Eng., Univ. Islam Indonesia, Yogyakarta, Indonesia
  • fYear
    2012
  • fDate
    14-15 Aug. 2012
  • Firstpage
    74
  • Lastpage
    77
  • Abstract
    Value stream analysis tools (VALSAT) is one of the technique found in lean manufacturing that provide a mechanism for choosing and utilizing the appropriate tools used in the production process to minimize waste. This preliminary VALSAT model is able to provide a correlation between the tools and waste which could be minimized. The correlation is stated in three different levels, namely: low, medium and high correlation. At present, the value that represents the correlation level is still vague. Therefore this research presents a range of values that can be used to replace the vagueness. The first stage of this research was done by using fuzzy Tsukamoto for developing a new VALSAT model. Then the sensitivity analysis is used toward the model that has been built to find the range value of correlation between tools and waste.
  • Keywords
    fuzzy set theory; lean production; sensitivity analysis; statistical analysis; waste management; VALSAT model; fuzzy identification; high correlation; lean manufacturing; low correlation; medium correlation; production process; sensitivity analysis; value stream analysis tool; waste minimization; Analytical models; Correlation; Indexes; Manufacturing; Pragmatics; Sensitivity analysis; Supply chains; VALSAT; fuzzy Tsukamoto; sensitivity analysis; tools and waste correlation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Uncertainty Reasoning and Knowledge Engineering (URKE), 2012 2nd International Conference on
  • Conference_Location
    Jalarta
  • Print_ISBN
    978-1-4673-1459-6
  • Type

    conf

  • DOI
    10.1109/URKE.2012.6319588
  • Filename
    6319588