IDEAS home Printed from https://ideas.repec.org/a/wly/syseng/v15y2012i1p28-40.html
   My bibliography  Save this article

An advanced cost estimation methodology for engineering systems

Author

Listed:
  • C.G. Hart
  • Z. He
  • R. Sbragio
  • N. Vlahopoulos

Abstract

A mathematically advanced method for improving the fidelity of cost estimation for an engineering system is presented. In this method historical cost records can be expanded either through the use of local metamodels or by using an engineering build‐up model. In either case, the expanded data set is analyzed using principal component analysis (PCA) in order to identify the physical parameters, and the principal components (PCs) which demonstrate the highest correlation to the cost. A set of predictor variables, composed of the physical parameters and of the multipliers of the principal components which demonstrate the highest correlation to the cost, is developed. This new set of predictor variables is regressed, using the Kriging method, thus creating a cost estimation model with a high level of predictive capability and fidelity. The new methodology is used for analyzing a set of cost data available in the literature, and the new cost model is compared to results from a neural network based analysis and to a cost regression model. Further, a case study addressing the fabrication of a submarine pressure hull is developed in order to illustrate the new method. The results from the final regression model are presented and compared to results from other cost regression methods. The technical characteristics of the new novel general method are presented and discussed. © 2011 Wiley Periodicals, Inc. Syst Eng

Suggested Citation

  • C.G. Hart & Z. He & R. Sbragio & N. Vlahopoulos, 2012. "An advanced cost estimation methodology for engineering systems," Systems Engineering, John Wiley & Sons, vol. 15(1), pages 28-40, March.
  • Handle: RePEc:wly:syseng:v:15:y:2012:i:1:p:28-40
    DOI: 10.1002/sys.20192
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/sys.20192
    Download Restriction: no

    File URL: https://libkey.io/10.1002/sys.20192?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    2. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    3. Meisl, Claus J., 1988. "Missile propulsion cost modeling," Engineering Costs and Production Economics, Elsevier, vol. 14(2), pages 117-129, July.
    4. Meisl, Claus J., 1988. "Techniques for cost estimating in early program phases," Engineering Costs and Production Economics, Elsevier, vol. 14(2), pages 95-106, July.
    5. Swee Lean Chan & Moonseo Park, 2005. "Project cost estimation using principal component regression," Construction Management and Economics, Taylor & Francis Journals, vol. 23(3), pages 295-304.
    6. Shtub, Avraham & Versano, Ronen, 1999. "Estimating the cost of steel pipe bending, a comparison between neural networks and regression analysis," International Journal of Production Economics, Elsevier, vol. 62(3), pages 201-207, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wolff, François-Charles, 2014. "Lift ticket prices and quality in French ski resorts: Insights from a non-parametric analysis," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1155-1164.
    2. François-Charles Wolff, 2014. "Lift ticket prices and quality in French ski resorts: Insights from a non-parametric analysis," Working Papers hal-00952999, HAL.
    3. Lei Wang & Yan Yan & Xiaoteng Li & Xiaosong Chen, 2018. "General Component Analysis (GCA): A new approach to identify Chinese corporate bond market structures," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
    4. Shanmugam, Ramalingam & Johnson, Charles, 2007. "At a crossroad of data envelopment and principal component analyses," Omega, Elsevier, vol. 35(4), pages 351-364, August.
    5. Juan Carlos Chávez & Felipe J. Fonseca & Manuel Gómez-Zaldívar, 2017. "Resoluciones de disputas comerciales y desempeño económico regional en México. (Commercial Disputes Resolution and Regional Economic Performance in Mexico)," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 79-93, May.
    6. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    7. Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang K., 2014. "TVICA—Time varying independent component analysis and its application to financial data," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 95-109.
    8. Yan Yu Chen & Chun-Cheih Chao & Fu-Chen Liu & Po-Chen Hsu & Hsueh-Fen Chen & Shih-Chi Peng & Yung-Jen Chuang & Chung-Yu Lan & Wen-Ping Hsieh & David Shan Hill Wong, 2013. "Dynamic Transcript Profiling of Candida albicans Infection in Zebrafish: A Pathogen-Host Interaction Study," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-16, September.
    9. Plat, Richard, 2009. "Stochastic portfolio specific mortality and the quantification of mortality basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 123-132, August.
    10. Kondylis, Athanassios & Whittaker, Joe, 2008. "Spectral preconditioning of Krylov spaces: Combining PLS and PC regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2588-2603, January.
    11. Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Governance, capital flight and industrialisation in Africa," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-22, December.
    12. M. J. Aziakpono & S. Kleimeier & H. Sander, 2012. "Banking market integration in the SADC countries: evidence from interest rate analyses," Applied Economics, Taylor & Francis Journals, vol. 44(29), pages 3857-3876, October.
    13. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    14. Bianca Maria Colosimo & Luca Pagani & Marco Grasso, 2024. "Modeling spatial point processes in video-imaging via Ripley’s K-function: an application to spatter analysis in additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 429-447, January.
    15. Ouyang, Yaofu & Li, Peng, 2018. "On the nexus of financial development, economic growth, and energy consumption in China: New perspective from a GMM panel VAR approach," Energy Economics, Elsevier, vol. 71(C), pages 238-252.
    16. Fan, Cheng & Sun, Yongjun & Zhao, Yang & Song, Mengjie & Wang, Jiayuan, 2019. "Deep learning-based feature engineering methods for improved building energy prediction," Applied Energy, Elsevier, vol. 240(C), pages 35-45.
    17. Ionela Munteanu & Adriana Grigorescu & Elena Condrea & Elena Pelinescu, 2020. "Convergent Insights for Sustainable Development and Ethical Cohesion: An Empirical Study on Corporate Governance in Romanian Public Entities," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    18. Daniel Boss & Annick Hoffmann & Benjamin Rappaz & Christian Depeursinge & Pierre J Magistretti & Dimitri Van de Ville & Pierre Marquet, 2012. "Spatially-Resolved Eigenmode Decomposition of Red Blood Cells Membrane Fluctuations Questions the Role of ATP in Flickering," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-10, August.
    19. L-J Kao & C-C Lu & C-C Chiu, 2011. "The training institution efficiency of the semiconductor institute programme in Taiwan—application of spatiotemporal ICA with DEA approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2162-2172, December.
    20. Doukas, Haris & Papadopoulou, Alexandra & Savvakis, Nikolaos & Tsoutsos, Theocharis & Psarras, John, 2012. "Assessing energy sustainability of rural communities using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 1949-1957.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:syseng:v:15:y:2012:i:1:p:28-40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6858 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.