The Design of Cost and Availability in Complex Engineering Systems

Part of the Decision Engineering book series (DECENGIN)


A lot has been covered in literature about equipment/system availability, through-life engineering services (TES) and cost. However, there are still many challenges remaining in the implementation of TES solutions (e.g. maintenance, training, etc.) to achieve cost and availability targets in complex engineering systems. Industry practitioners seek to improve their ability to predict the evolution of complex engineering systems so that it can embrace proactive behaviour to reduce the through-life cost and increase the level of availability. Contracting for Availability (CfA), a commercial process which seeks to sustain a system or capability at an agreed level of availability, is a good example of how many industry organisations have been implementing TES in their business and experiencing difficulties in performing effective cost and availability estimates, in particular at the early stages of the contracts (e.g. bidding stage), where the most of the costs are committed. This chapter focuses on cost and availability trade-off analysis at the bidding stage of CfA, in the defence context. At this phase there is a need to predict the through-life behaviour of the system (e.g. in a 20/30 year life span), which will be affected by risks and uncertainties that complicate the prediction of the total cost and level of system (e.g. platforms) availability. Two case studies with the UK Ministry of Defence (MoD) enabled the identification of the attributes that impact the cost and availability targets of CfA and the key performance indicators (KPIs) to measure the availability. This led to the development of a framework that gives a major contribution to the decision makers by analysing the required investment in each attribute in order to effectively balance availability and affordability at the bidding stage of CfA. This is a novel research in this context as no other similar approach has been found in literature. It can be further implemented in practice as a simulation model using mathematical equations and appropriate software tools such as excel or matlab.


  1. 1.
    Weiss A (2005) Conquering complexity: lessons for defence systems acquisition. The Stationaty Office, LondonGoogle Scholar
  2. 2.
    Jones KH, Parker PA, Detweiler KN, Mcgowan AMR, Dress DA, Kimmel WM (2013) Analysis and perspectives from the complex aerospace systems exchange (case)Google Scholar
  3. 3.
    (2013) World energy scenarios: composing energy futures to 2050, LondonGoogle Scholar
  4. 4.
    Roy R, Shaw A, Erkoyuncu JA, Redding L (2013) Through-life engineering services. Meas Control (UK) 46:172–175. doi: 10.1177/0020294013492283 CrossRefGoogle Scholar
  5. 5.
    United States Government Accountability Office (2008) Defence logistics: improved analysis and cost needed to evaluate the cost-effectiveness of performance based logisticsGoogle Scholar
  6. 6.
    Deloitte Consulting (2010) Performance based logistics in aerospace and defenceGoogle Scholar
  7. 7.
    Datta PP, Roy R (2010) Cost modelling techniques for availability type service support contracts: a literature review and empirical study. CIRP J Manuf Sci Technol 3(2010):142–157. doi: 10.1016/J.Cirpj.07.003 CrossRefGoogle Scholar
  8. 8.
    Jeang A (2014) Project management for uncertainty with multiple objectives optimisation of time. Cost Reliab Int J Prod Res 53:1503–1526. doi: 10.1080/00207543.2014.952792 CrossRefGoogle Scholar
  9. 9.
    T.N. Archives (2008) Acquisition operating framework. https://www.Gov.Uk/Guidance/Acquisition-Operating-Framework. Accessed 06 June 2016
  10. 10.
    Ministry of Defence (2014) Integrated logistic support Part 1. In: JSP 886 defence support chain management, pp 11–13Google Scholar
  11. 11.
    Ministry of Defence (2015) JSP 912 human factors integration for defence systems Part 2Google Scholar
  12. 12.
    Wendel CH, Braun RJ (2016) Design and techno-economic analysis of high efficiency reversible solid oxide cell systems for distributed energy storage. Appl Energy 172(2016):118–131. doi: 10.1016/J.Apenergy.03.054 CrossRefGoogle Scholar
  13. 13.
    Murthy DNP, Yeung V (1995) Modelling and analysis of maintenance service contracts. Math Comput Model 22:219–225. doi: 10.1016/0895-7177(95)00199-C MathSciNetCrossRefMATHGoogle Scholar
  14. 14.
    Bokor Z (2011) Performance-based logistics costing. In: Lindi 2011—3rd IEEE international symposium on logistics and industrial informatics, proceedings, 2011, pp 171–175. doi: 10.1109/Lindi.2011.6031141
  15. 15.
    Rahman A, Chattopadhyay G (2008) Cost estimation for maintenance contracts for complex asset/equipment. In: 2008 IEEE international conference of industrial engineering and management, IEEM 2008, pp 1355–1358. doi: 10.1109/Ieem.2008.4738091
  16. 16.
    Settanni E, Newnes LB, Thenent NE, Parry G, Goh YM (2014) A through-life costing methodology for use in product–service-systems. Int J Prod Econ 153(2014):161–177. doi: 10.1016/J.Ijpe.02.016 CrossRefGoogle Scholar
  17. 17.
    Curran R, Raghunathan S, Price M (2004) Review of aerospace engineering cost modelling: the genetic causal approach. Prog Aerosp Sci 40(2004):487–534. doi: 10.1016/J.Paerosci.10.001 CrossRefGoogle Scholar
  18. 18.
    Russell R, Chung M, Balk EM (2009) AHRQ technical reviews and summaries, issues challenges conducting systematics reviews to support development of nutrient reference values: workshop summary, US, 2009. http://Www.Ncbi.Nlm.Nih.Gov/Books/Nbk44081/. Accessed 07 June 2016
  19. 19.
    Perkins MJ, Ng TPT, Dudgeon D, Bonebrake TC, Leung KMY (2015) Conserving intertidal habitats: what is the potential of ecological engineering to mitigate impacts of coastal structures? Estuar Coast Shelf Sci 167(2015):504–515. doi: 10.1016/J.Ecss.10.033 CrossRefGoogle Scholar
  20. 20.
    Esteban J, Starr A, Willetts R, Hannah P, Bryanston-Cross P (2005) A review of data fusion models and architectures: towards engineering guidelines. Neural Comput Appl 14:273–281. doi: 10.1007/S00521-004-0463-7 CrossRefGoogle Scholar
  21. 21.
    Rodrigues D, Erkoyuncu J, Starr A, Wilding S, Dibble A, Laity M (2016) A framework to trade-off cost and availability in military contractGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Duarte Rodrigues
    • 1
  • John Erkoyuncu
    • 1
  • Andrew Starr
    • 1
  1. 1.EPSRC Centre for Innovative Manufacturing in Through-Life Engineering ServicesCranfield UniversityCranfieldUK

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