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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2017, Vol. 38 ›› Issue (2): 320258-320272.doi: 10.7527/S1000-6893.2016.0266

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Method of fuzzy earned value management for weapon equipment development project

WU Shihui1, XIE Jiang1, LIU Xiaodong1, HE Bo1, YAN Baohui2, GUO Yakun3   

  1. 1. Equipment Management and Safety Engineering College, Air Force Engineering University, Xi'an 710051, China;
    2. Repair Factory, No. 93705 Unit of PLA, Zunhua 064200, China;
    3. No. 95876 Unit of PLA, Shandan 734100, China
  • Received:2016-03-24 Revised:2016-10-08 Online:2017-02-15 Published:2016-10-14
  • Supported by:

    National Natural Science Foundation of China (61601501); Natural Science Foundation of Shaanxi Province (2014JM2-6095)

Abstract:

Since technology risk exists widely in the weapon equipment development project, it is better to describe the budget as fuzzy number. However, technology risk is neglected in the current earned value management (EVM), which often builds the baseline of the budget with crisp numbers. Therefore, we introduce technology risk to EVM, and propose an improved method of fuzzy earned value management (FEVM) for the weapon development project. The proposed FEVM fully considers technology risk during the project development, and applies the technology readiness level (TRL) concept to estimate the budgeted cost. By utilizing fuzzy theory, the fuzzy assessment standard based on degree of possibility for the cost and schedule of high risk project is given, as well as fuzzy prediction of the estimate completion cost (ECC) and estimate completion time (ECT). The proposed method is illustrated through an example. The proposed method extends the applicability of the EV techniques for the weapon equipment development project with technology risks, and can better help decision-makers to control risks and bring cost and schedule back to the baseline.

Key words: fuzzy earned value management, technology readiness level, fuzzy number, possibility degree, cost correction factors

CLC Number: