• DocumentCode
    2284676
  • Title

    A order mix decision model for make-to-order enterprise

  • Author

    Wang, Chao

  • Author_Institution
    Sch. of Manage., Wuhan Univ. of Technol., Wuhan, China
  • fYear
    2009
  • fDate
    14-16 Sept. 2009
  • Firstpage
    541
  • Lastpage
    546
  • Abstract
    Make-to-stock and Make-to-order are two generic operation modes commonly used in the manufacturing world. The make-to-order enterprise makes the production systems to produce a product only after it is ordered. The enterprise must decide which orders can be accepted to get the optimal profit and meet the due time. This paper addresses a order mix decision model in a make-to-order operation environment. The mathematical model is proposed to select a set of customer orders to maximize the operational profit such that all the selected orders are fulfilled by their deadline. With a given capacity limit on each resource type and its cost rate, solving this model leads to an optimal production mix for the orders over a given time horizon. The conclusion shows that it is not a optimal choice to accept all customer´s orders although they can be produced before deadline. This paper tells the enterprise how to select the order mix according to the cost and production capacity planning.
  • Keywords
    manufacturing systems; mathematical analysis; order processing; organisational aspects; production planning; make-to-order enterprise; make-to-order operation; make-to-stock; manufacturing world; mathematical model; optimal production mix; order mix decision model; production capacity planning; production systems; Capacity planning; Conference management; Costs; Engineering management; Job shop scheduling; Manufacturing; Meeting planning; Production; Subcontracting; Technology management; decision model; enterprise; make-to-order; order mix;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering, 2009. ICMSE 2009. International Conference on
  • Conference_Location
    Moscow
  • Print_ISBN
    978-1-4244-3970-6
  • Electronic_ISBN
    978-1-4244-3971-3
  • Type

    conf

  • DOI
    10.1109/ICMSE.2009.5317313
  • Filename
    5317313