Supporting the system architect: Model-assisted communication

被引:0
|
作者
Engebakken E. [1 ]
Muller G. [2 ]
Pennotti M. [3 ]
机构
[1] Buskerud University College, Kongsberg
[2] Stevens Institute of Technology, Hoboken, NJ
来源
Systems Research Forum | 2010年 / 4卷 / 02期
关键词
critical success factors; modeling techniques; system analysis; System modeling;
D O I
10.1142/S1793966610000211
中图分类号
V271.4 [军用飞机(战机)];
学科分类号
摘要
System modeling and analysis is used to validate assumptions, increase understanding, synchronize views, and support decisions. By measuring indirect related quantities and commonalities of different modeling techniques in practice we can get an indication of the value of modeling. In this paper, we discuss how to increase modeling value and provide more effective model-assisted communication by understanding critical success factors of modeling. We analyze models used to support production line design at Volvo Aero Norge AS. Volvo Aero Norge AS manufactures jet engine components for commercial and military engine suppliers. Flight safety is fundamental in the domain which translates to comprehensive component quality and traceability requirements. Long-term engine programs make production line development and process improvements important for staying competitive and maintaining a profitable production that supports the required quality level. System modeling and analysis is applied to communicate insight between stakeholders and visualize different aspects of production lines and processes. In this paper we present impact factors the architect can use to increase a model's ability to assist communication. We argue how balancing and utilizing the right quantity of these factors increase modeling value. © 2010 World Scientific Publishing Company.
引用
收藏
页码:173 / 188
页数:15
相关论文
共 50 条
  • [21] A model-assisted design for partially or completely ordered groups
    Celum, Connor
    Conaway, Mark
    PHARMACEUTICAL STATISTICS, 2024, 23 (06) : 906 - 927
  • [22] Multifidelity model-assisted probability of detection via Cokriging
    Du, Xiaosong
    Leifsson, Leifur
    NDT & E INTERNATIONAL, 2019, 108
  • [23] Investigation of a model-assisted approach to probability of detection evaluation
    Knopp, J. S.
    Aldrin, J. C.
    Lindgren, E.
    Annis, C.
    REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOLS 26A AND 26B, 2007, 894 : 1775 - 1782
  • [24] On the relative efficiency of model-assisted designs: a conditional approach
    Lin, Ruitao
    Yuan, Ying
    JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 2019, 29 (04) : 648 - 662
  • [25] Model-assisted steady-state evolution strategies
    Ulmer, H
    Streichert, F
    Zell, A
    GENETIC AND EVOLUTIONARY COMPUTATION - GECCO 2003, PT I, PROCEEDINGS, 2003, 2723 : 610 - 621
  • [26] EFFICIENCY OF MODEL-ASSISTED REGRESSION ESTIMATORS IN SAMPLE SURVEYS
    Shao, Jun
    Wang, Sheng
    STATISTICA SINICA, 2014, 24 (01) : 395 - 414
  • [27] Nonparametric additive model-assisted estimation for survey data
    Wang, Li
    Wang, Suojin
    JOURNAL OF MULTIVARIATE ANALYSIS, 2011, 102 (07) : 1126 - 1140
  • [28] Semiparametric model-assisted estimation for natural resource surveys
    Breidt, F. Jay
    Opsomer, Jean D.
    Johnson, Alicia A.
    Ranalli, M. Giovanna
    SURVEY METHODOLOGY, 2007, 33 (01) : 35 - 44
  • [29] Model-Assisted Survey Estimation with Modern Prediction Techniques
    Breidt, F. Jay
    Opsomer, Jean D.
    STATISTICAL SCIENCE, 2017, 32 (02) : 190 - 205
  • [30] Model-assisted feedback control for liquid composite molding
    Dunkers, JP
    Flynn, KM
    Parnas, RS
    Sourlas, DD
    COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING, 2002, 33 (06) : 841 - 854