• DocumentCode
    3658297
  • Title

    An intelligent fuzzy-based storage assignment system for packaged food warehousing

  • Author

    Yasmin Y.Y. Hui;K.L. Choy;G.T.S. Ho;Cathy H.Y. Lam;C.K.H. Lee;Stephen W.Y. Cheng

  • Author_Institution
    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong
  • fYear
    2015
  • Firstpage
    1869
  • Lastpage
    1878
  • Abstract
    In the packaged food industry, fast cargo receiving, reliable storage and accurate order picking in warehouses within short period of time are critical for achieving customer satisfaction. Food easily deteriorates when unloaded packaged food is exposed in an open area, waiting for inbound and packing operations, according to customer orders. In addition, the risk of damaging the packaging of food is higher when the food is frequently transported by forklift trucks during order picking. This highlights the need to provide decision support in warehouse zoning and storage assignment for preventing the above risks occurring. This paper proposes a tri-modular intelligent fuzzy-based storage assignment system, integrating fuzzy logic and association rules mining techniques, to reduce the order-picking and cargo exposure time, as well as the transport frequency and distance. The fuzzy zoning module is used to allocate different types of packaged food to various warehouse zones based on their particular characteristics. The location assignment module reveals hidden relationships in the sales of products, in turns suggesting which products should be placed together in the same zone. A case study is carried out to examine the intelligent system.
  • Keywords
    "Fuzzy logic","Artificial intelligence","Companies","Food industry","Data mining","Engines","Warehousing"
  • Publisher
    ieee
  • Conference_Titel
    Management of Engineering and Technology (PICMET), 2015 Portland International Conference on
  • Type

    conf

  • DOI
    10.1109/PICMET.2015.7273209
  • Filename
    7273209