1. PG Conf /1 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Managing Project Planning Risk Fouzi A. Hossen

2. PG Conf /2 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Overview Risk and Uncertainty Objectives Project risk management PRM process Capital good companies Product structure Industrial case study Conclusions

3. PG Conf /3 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Risk Risk is defined as “the exposure to the possibility of economic and financial loss or gain, physical damage or injury, or delay as a consequence of the uncertainty associated with pursuing a particular course of action” (Chapman et al., 1991). Project risk exists where uncertainty threaten the project’s ability to meet its objectives within the given limitations (CCTA,1996)

4. PG Conf /4 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Uncertainty Uncertainty is defined as “the unknown future event that cannot be predicted quantitatively within useful limits” (APICS, 1998, p98). Uncertainty has a common meaning which is the lack of certainty; risk also has general meaning which is the exposure to loss or injury as a consequence of uncertainty (Chapman et al., 1987).

5. PG Conf /5 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Objectives The objectives of the paper are to: Review the literature relating to the project risk management process; Investigate the risk associated with project scheduling that result from activity duration uncertainty; Analyse the activity completion time risk quantitatively by developing a simulation model.

6. PG Conf /6 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Project risk management PRM process The PRM process is defined as “the process of taking management action in order to respond appropriately to all identified risks to maximise the likelihood of the project meeting its objectives within its constraints, by monitoring risk exposure and adjusting project strategy to keep risk within acceptable levels” (CCTA, 1996, p12).

7. PG Conf /7 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Project risk management PRM process Risk identification Risk Analysis - Qualitative risk analysis - Quantitative risk analysis Risk mitigation Risk Monitoring and follow up Project risk Management process

8. PG Conf /8 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Capital Goods Companies Product and process usually complex Customised to meet individual customers requirements Engineer-to-order Low production volume

9. PG Conf /9 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Product Structure See the product structure considered in this study

10. PG Conf /10 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Industrial case study Component finishing time Assembly finishing time

11. PG Conf /11 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Industrial case study Normal probability plot of final product finishing time

12. PG Conf /12 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Industrial case study Final product finishing time 0.1 Sd 0.2 Sd Due date Final product finishing time 0.3 Sd

13. PG Conf /13 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Industrial case study Final product finishing time Sd 0.1 Sd 0.4 Due date

14. PG Conf /14 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Conclusions Capital goods are customised and the processing times are uncertain. The uncertainty becomes cumulative throughout the production stages. Due to the uncertainty and complexity of production in ETO products, it is difficult to estimate accurately the product lead-time.

15. PG Conf /15 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Conclusions The effect of cumulative uncertainty is to shift the distribution of product completion time to the right. As a result of this the probability of delivering a product on due date becomes very small. Increasing of the standard deviation from 0.1 to 0.2 and 0.3 times the mean, the distribution of product completion times are increasingly shifted to the right and the uncertainty is additionally increased. Managers need to minimise the risks associated with these uncertainties.

16. PG Conf /16 © F.A. Hossen, M&S Engineering University of Newcastle upon Tyne Acknowledgement I would like to thank my supervisor, Dr C. Hicks, for his advise and Dr P. Pongcharoen for his support. Any Questions?