Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-22T06:52:09.111Z Has data issue: false hasContentIssue false
  • English
  • Français

Aircraft cost modelling using the genetic causal technique within a systems engineering approach

Published online by Cambridge University Press:  03 February 2016

R. Curran ,
S. Castagne ,
J. Early ,
M. Price ,
S. Raghunathan ,
J. Butterfield  and
A. Gibson
R. Curran
Affiliation:
Centre of Excellence for Integrated Aircraft Technologies (CEIAT), School of Mechanical and Aerospace Engineering, Queens University Belfast, Northern Ireland, UK
S. Castagne
Affiliation:
Centre of Excellence for Integrated Aircraft Technologies (CEIAT), School of Mechanical and Aerospace Engineering, Queens University Belfast, Northern Ireland, UK
J. Early
Affiliation:
Centre of Excellence for Integrated Aircraft Technologies (CEIAT), School of Mechanical and Aerospace Engineering, Queens University Belfast, Northern Ireland, UK
M. Price
Affiliation:
Centre of Excellence for Integrated Aircraft Technologies (CEIAT), School of Mechanical and Aerospace Engineering, Queens University Belfast, Northern Ireland, UK
S. Raghunathan
Affiliation:
Centre of Excellence for Integrated Aircraft Technologies (CEIAT), School of Mechanical and Aerospace Engineering, Queens University Belfast, Northern Ireland, UK
J. Butterfield
Affiliation:
Centre of Excellence for Integrated Aircraft Technologies (CEIAT), School of Mechanical and Aerospace Engineering, Queens University Belfast, Northern Ireland, UK
A. Gibson
Affiliation:
Centre of Excellence for Integrated Aircraft Technologies (CEIAT), School of Mechanical and Aerospace Engineering, Queens University Belfast, Northern Ireland, UK Aeronautical Engineering, Massey University, New Zealand
Get access Rights & Permissions [Opens in a new window]

Abstract

The paper is primarily concerned with the modelling of aircraft manufacturing cost. The aim is to establish an integrated life cycle balanced design process through a systems engineering approach to interdisciplinary analysis and control. The cost modelling is achieved using the genetic causal approach that enforces product family categorisation and the subsequent generation of causal relationships between deterministic cost components and their design source. This utilises causal parametric cost drivers and the definition of the physical architecture from the Work Breakdown Structure (WBS) to identify product families. The paper presents applications to the overall aircraft design with a particular focus on the fuselage as a subsystem of the aircraft, including fuselage panels and localised detail, as well as engine nacelles. The higher level application to aircraft requirements and functional analysis is investigated and verified relative to life cycle design issues for the relationship between acquisition cost and Direct Operational Cost (DOC), for a range of both metal and composite subsystems. Maintenance is considered in some detail as an important contributor to DOC and life cycle cost. The lower level application to aircraft physical architecture is investigated and verified for the WBS of an engine nacelle, including a sequential build stage investigation of the materials, fabrication and assembly costs. The studies are then extended by investigating the acquisition cost of aircraft fuselages, including the recurring unit cost and the non-recurring design cost of the airframe sub-system. The systems costing methodology is facilitated by the genetic causal cost modeling technique as the latter is highly generic, interdisciplinary, flexible, multilevel and recursive in nature, and can be applied at the various analysis levels required of systems engineering. Therefore, the main contribution of paper is a methodology for applying systems engineering costing, supported by the genetic causal cost modeling approach, whether at a requirements, functional or physical level.

Type
Research Article
Information
The Aeronautical Journal , Volume 111 , Issue 1121 , July 2007 , pp. 409 - 420
Copyright
Copyright © Royal Aeronautical Society 2007 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. EIA Standard S-632, Systems Engineering, December 1994.Google Scholar
2. Department of Defense, Systems Engineering Fundamentals, Defense Acquisition University Press.Google Scholar
3. Bashir, H.A. and Thomson, V., Metrics for design projects: a review, 1999, Design Studies, 20, (3), pp 263–277.Google Scholar
4. Ostwald, P.F., Engineering Cost Estimating, 1992, Prentice Hall, ISBN 0-13-276627-2, 576.Google Scholar
5. Curran, R., Kundu, A., Raghunathan, S. and Eakin, D., Costing tools for decision making within integrated aerospace design, J of Concur Eng Research, 2002, 9, (4), pp 327–338.Google Scholar
6. Mileham, A.R., Currie, G.C., Miles, A.W. and Bradford, D.T., A parametric approach to cost estimating at the conceptual stage of design, J of Eng Design, 1993, 4, (2), p 117.Google Scholar
7. Pugh, P., Working top-down: cost estimating before development begins, J of Aero Eng, 1992, 206, pp 143–151.Google Scholar
8. Herrera, A., Design for manufacture and assembly, a cost effective tool supporting lean design initiatives, 1998, Proc of Int Forum on DFMA.Google Scholar
9. Rush, C. and Roy, R., Analysis of cost estimating processes used within a concurrent engineering environment throughout a product life cycle, 2000, Proc 7th Int Conf on Concurrent Engineering, Lyon, France, Technomic Publishing, pp 58–67.Google Scholar
10. Arrow, K.J. and Arrow, S.S., Methodology problems in airframe cost-performance Studies, 1950, Rand Corporation Document No: RM-456-PR, 33.Google Scholar
11. Levenson, G.S. and Barro, S.M., Cost-estimating relationships for aircraft airframes, 1966, Rand Corporation Document No: RM-4845-PR, p 99.Google Scholar
12. Roy, R., Bendall, D., Taylor, J.P., Jones, P., Madariaga, Pa., Crossland, J., Hamel, J. and Taylor, M.I., Identifying and capturing the qualitative cost drivers within a concurrent engineering environment, 1999, Advances in Concurrent Engineering, Tech-nomic Publishing, Pennsylvania (USA), pp 39–50.Google Scholar
13. Curran, R., Kundu, A., Raghunathan, S. and McFadden, R., Influence of manufacturing tolerance on aircraft direct operating cost (DOC), J of Mat Process Tech, 2003, Elsevier Science BV, ISSN; 0924-0136, pp 239–247.Google Scholar
14. Curran, R., Raghunathan, S. and Price, M., A review of aircraft cost modelling and genetic causal approach, Prog in Aero Sci J, 2004, 40, (8), pp 487–534.Google Scholar
15. Curran, R., Rothwell, A. and Castagne, S., A numerical method for cost-weight optimisation of stringer-skin panels, J Aircr, 2005, 43, (1), pp 264–274.Google Scholar
16. Curran, R., Watson, P., Cowan, S., Mahwinney, J. and Raghunathan, S., Development of an aircraft cost estimating model for program cost rationalisation, 2003, Proceedings of the Canadian Aeronautics and Space institute (CASI), April, Montreal.Google Scholar
17. Curran, R., Castagne, S., Rothwell, A., Price, M. and Murphy, A., Integrating manufacturing cost and structural requirements in a systems engineering aspproach to aircraft design, Proc 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics & Materials Conference, AIAA, Reston, VA, 2005.Google Scholar
18. Curran, R., Kundu, A., Raghunathan, S. and McFadden, R., Impact of aerodynamic surface tolerance on aircraft cost driver, 2002, J of Aerosp Eng, 216, (G1), pp 29–39.Google Scholar
19. Raghunathan, S., Curran, S. and Kundu, A.K., Research into tradeoff studies to reduce aircraft cost, Conference on System Integration, 2003, 12-14 March, Stevens Institute of Technology, NJ, USA.Google Scholar
20. Price, M., Early, J.M., Curran, R., Benard, E. and Raghunathan, S., Identifying interfaces in engineering systems, Accepted for publication in AIAA J Aircr, June 2005.Google Scholar
21. Mawhinney, P., Price, M., Armstrong, C.G., Ou, H., Murphy, A., Gibson, A. and Curran, R., Using idealised models to enable integration and analysis driven design, AIAA Paper 2003-6747, AIAA’s 3rd Annual Aviation Technology, Integration, & Operations (ATIO) Forum, Denver, November 2003.Google Scholar
22. Mawhinney, P., Price, M., Armstrong, C., Curran, R., Murphy, A., Early, J., Raghunathan, S. and Ou, H., Design and analysis integration using systems engineering for aircraft structural design, 4th AIAA Aviation Technology and Operations Forum, Chicago, 20-22 September 2004.Google Scholar
23. Mawhinney, P., Price, M., Curran, R., Benard, E., Murphy, A. and Raghunathan, S., Geometry-based approach to analysis integration for aircraft conceptual design, AIAA-2005-7481, 5th Annual Aviation Technology, Integration, & Operations (ATIO) Forum, Washington DC, September 2005.Google Scholar
24. Early, J.M., Price, M., Mawhinney, P., Curran, R., Benard, E. and Raghunathan, S., Framework for modelling and simulation within a flexible integration environment, Paper No. AIAA-2004-6457, AIAA’s 4th Annual Aviation Technology, Integration, & Operations (ATIO) Forum, Chicago, Illinois, September 2004.Google Scholar
25. Department of Defense, Parametric Estimating Handbook, 1999, 2nd Ed, DoD.Google Scholar
26. Unisys, 2005, Unisys R2A Scorecard, Airline Industry Cost Measurement, 3, (10).Google Scholar
27. Dixon, M., The cost of aging aircraft: insights from commercial aviation, 2005, Pardee RAND Graduate School Dissertation Series.Google Scholar
28. Kundu, A.K., Raghunathan, S. and Cooper, R.K., Effect of aircraft surface smoothness requirements on cost, Aeronaut J, 2000, 104, (1039), pp 415–420.Google Scholar
29. Boothroyd, G., Dewhurst, P. and Knight, W., Product Design for Manufacture and Assembly, 1994, Marcel Dekker, New York.Google Scholar
30. Gauthier, B., Dewhurst, P. and Japikse, D., Application of design For manufacture and assembly methodologies to complex aerospace products, 2000, Proc of 36th AIAA/ASME/SAE/ASEE Joint Propulsion Conf.Google Scholar