• DocumentCode
    3515381
  • Title

    R&D costing analysis and prediction modeling of armored vehicles

  • Author

    Li, Xiangrong ; Xu, Zongchang ; Meng, Xianghui

  • Author_Institution
    Arms Eng. Dept., Armored Force Eng. Coll., Beijing, China
  • fYear
    2009
  • fDate
    20-24 July 2009
  • Firstpage
    9
  • Lastpage
    11
  • Abstract
    Aiming to some problems of armored vehicles research and development, such as few new types, few costing data and long research and development(R&D) cycle, it discussed some key techniques about R&D costing analysis of the armored vehicles, including identifying conversion coefficients about time worth, calculating dynamic and static expense and yearly expense distribution. Then, using parameters modeling method based on non-linear multi-regression technology, it built a prediction model between R&D costing and performance parameters of the armored vehicles. The model can be used to predict R&D costing of one new vehicle whose performance parameters are confirmed. The research results are significant to armored equipments life cycle costing (LCC) analysis that is comparatively weak currently in China.
  • Keywords
    armour; life cycle costing; military vehicles; regression analysis; remaining life assessment; research and development; R&D costing analysis; armored vehicles; life cycle costing; nonlinear multiregression technology; parameter modeling method; research and development; yearly expense distribution; Automotive engineering; Costing; Data engineering; Educational institutions; Inorganic materials; Metals industry; Predictive models; Research and development; Statistics; Vehicle dynamics; life cycle costing analysis; non-linear multi-regression technology; research and development costing prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability, Maintainability and Safety, 2009. ICRMS 2009. 8th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-4903-3
  • Electronic_ISBN
    978-1-4244-4905-7
  • Type

    conf

  • DOI
    10.1109/ICRMS.2009.5270250
  • Filename
    5270250