Open Access Open Access  Restricted Access Subscription Access

Integrated Cost / Schedule Risk Analysis for Defence Acquisition Projects


Affiliations
1 Development Canada Centre for Operational Research and Analysis Ottawa, Canada
 

Risk assessment is a crucial component in defence acquisition project management. It allows analysts to examine the impact of individual risks on the overall project cost and schedule. This paper suggests a new integrated cost/schedule risk assessment approach that combines cost risk and schedules risk analyses within a single mathematical model. Optimization and Monte Carlo simulation techniques are used to determine the expected cost and completion time of an acquisition project. A case study using a military aircraft replacement project for the Canadian Armed Forces is used to illustrate the approach.

Keywords

Risk Analysis, Schedule Buffer, Cost Contingency, Military, Aircraft.
User
Notifications
Font Size

  • Pinnell, S.S., and Busch, J.S. (1993), How do you measure the quality of your project management?, PM Network, December, 35-36.
  • Hulett, D. (2011). Integrated Cost-Schedule Risk Analysis. Gower Publishing.
  • Vanhoucke, M. (2012). Project management with dynamic scheduling: baseline scheduling. Risk Analysis and Project Control. Springer-Verlag Berlin and Heidelberg GmbH & Co. K .
  • Ghanmi, A., Rempel, M., Abderrahmane Sokri, A., Solomon, B., and Ghergari, V. (2014). Cost Risk Framework. DRDC Scientific Report, DRDC-RDDC-2014-R167, Ottawa, Canada.
  • Sokri, A. and Ghanmi, A. (2015). Cost Risk Analysis Methods for Defence Acquisition Projects. International Conference on Risk Analysis, Barcelona, Spain, May 26-29.
  • Sokri, A. and Ghanmi, A. (2017). Cost risk analysis and learning curve in the military shipbuilding sector. International Journal of Data Analysis Techniques and Strategies (In press).
  • Sokri, A., and Ghanmi, A. (2016). Schedule Risk Analysis for Defense Acquisition Projects, Book Chapter in Risk Management: Perspectives and Open Issues – A Multidisciplinary Approach, McGraw-Hill Education, pp. 266-279.
  • Brucker P., Drexl, A., M¨ohring, R., Neumann, K., and Pesch, E. (1999). Resource-constrained project scheduling: Notation, classification, models, and methods. European Journal of Operational Research, 112 (1): 3–41.
  • Herroelen, W., Demeulemeester, E., and De Reyck, B. (1999). Classification Scheme for Project Scheduling Problems, Chapter 1. In: Handbook of Recent Advances in Project Scheduling, Weglarz, J. (Ed.). Kluwer Academic Publishers. Boston (USA). 1999. pp. 1-26.
  • Vanhoucke, M. and Debels, D. (2008). The impact of various activity assumptions on the lead time and resource utilization of resourceconstrained projects. Computers & Industrial Engineering, Vol 54, pp. 140–154.
  • A.H. Russell, Cash flows in networks, Management Science 16 (1970) 357–373.
  • Mika, M., Waligóra, G., We˛glarz, J., 2005. Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models. European Journal of Operational Research 164 (3), 639–668.
  • Kazaz,B. and Sepil, C. Project scheduling with discounted cash flows and progress payments, Journal of the Operational Research Society 42 (1996) 1262–1272.
  • Dayanand, N. Padman, R. (1997). On modelling payments in projects, Journal of the Operational Research Society, 48: 906–918.
  • Etgar, R., Shtub, A., and LeBlanc, L.J. (1997). Scheduling projects to maximize net present value – the case of time-dependent, contingent cash flows, European Journal of Operational Research, 96 (1): 90–96.
  • Liberatore M.J., Pollack-Johnson B., Smith C.A. (2001). Project management in construction: software use and research direction. J Constr Eng Manage 2001, Vol. 127, Issue 2, pp.101–7.
  • Kastor, A. and Sirakoulis, K. (2009). The effectiveness of resource levelling tools for resource constraint project scheduling problem. International Journal of Project Management, 27: 493–500.
  • Ranjbar, M., Kianfar, F., and Shadrokh, S. (2008). Solving the resource availability cost problem in project scheduling by path relinking and genetic algorithm. Applied Mathematics and Computation, vol. 196, pp. 879–888
  • Hyari, K., El-Rayes, K. (2006). Optimal planning and scheduling for repetitive construction projects, Journal of Management in Engineering, Vol. 22, Issue 1, pp. 11–19.
  • Liberatore, M.J. and Pollack-Johnson, B.(2006). Extending project time–cost analysis by removing precedence relationships and task streaming. International Journal of Project Management, 24: 529–535.
  • Alvarez-Benitez, J. E., Everson, R. M., and Fieldsend, J. E. (2005). A Mopso Algorithm Based Exclusively On Pareto Dominance Concepts. Evolutionary Multi-Criterion Optimization, 3410: 459–473.
  • Sokri, A. and Solomon, B. (2013). Cost Risk Analysis and Contingency for the NGFC DRDC CORA Technical Memorandum TM 2013-224.

Abstract Views: 194

PDF Views: 0




  • Integrated Cost / Schedule Risk Analysis for Defence Acquisition Projects

Abstract Views: 194  |  PDF Views: 0

Authors

Abderrahmane Sokri
Development Canada Centre for Operational Research and Analysis Ottawa, Canada
Ahmed Ghanmi
Development Canada Centre for Operational Research and Analysis Ottawa, Canada

Abstract


Risk assessment is a crucial component in defence acquisition project management. It allows analysts to examine the impact of individual risks on the overall project cost and schedule. This paper suggests a new integrated cost/schedule risk assessment approach that combines cost risk and schedules risk analyses within a single mathematical model. Optimization and Monte Carlo simulation techniques are used to determine the expected cost and completion time of an acquisition project. A case study using a military aircraft replacement project for the Canadian Armed Forces is used to illustrate the approach.

Keywords


Risk Analysis, Schedule Buffer, Cost Contingency, Military, Aircraft.

References