Conclusions

The research has achieved its main goal of improving railway safety by developing safety risk models and tools using FRA and AHP techniques for railway safety risk assessment processes. The research has proved that the proposed risk model can successfully help rail vehicles, infrastructure operators, track & civil engineering designers and maintainers, and health & safety advisors to improve railway safety through design, diagnosis and maintenance of railway systems. The achievements of this research can be summarised as follows:

 The objective of investigation of railway safety risk assessment tools as used in practice and in research literature worldwide has been achieved. This has been accomplished through conducting an extensive literature review of railway safety risk assessment techniques which highlights railway safety concepts and discusses the implementations and applications of current risk assessment techniques in railways. It was found that current techniques applied in railway safety risk assessment may not be appropriate when there is a high level of uncertainty involved in the risk data and information. The application of FRA and Fuzzy-AHP in the risk model may solve such a problem. This research also introduces a new parameter of 'consequence probability' in the risk assessment process, which enhances the risk analysis.

 The objective of development of railway safety risk models and tools to facilitate railway safety risk analysis has been achieved. Safety risk models based on FRA combined with improved Fuzzy-AHP technique have been established for processing safety risk assessment efficiently and effectively. By introducing the parameter of 'consequence probability', it distinguishes a hazard event with a higher

CHAPTER 9: CONCLUSIONS AND RECOMMENDATIONS

probability of consequence to cause fatalities. This will affect the overall risk ranking and finally affect the decision making of potential safety measures or maintenance strategies. Also by the application of improved Fuzzy-AHP, the required number of expert judgements is reduced from to when conducting pairwise comparison. It is a significant advantage to compare with the traditional method when the number of involved alternatives is high. The other advantage of applying improved fuzzy-AHP is that the comparison matrix derived from expert judgements is always consistent, while the consistency test is needed in traditional fuzzy-AHP. Therefore, the proposed model can produce much more reliable results than other risk assessment techniques.

 The objective of validation of the proposed railway safety risk system via case studies with the industrial partners has been achieved. The case studies on risk assessment of shunting at Hammersmith and a track system are used to validate the proposed models, and relevant papers have been published. The proposed model can provide detailed results, which include risk contributions arising at system level, sub-system level as well as component level, and also include RLs in the format of risk score and risk categories with a degree of confidence.

 The objective of developing advanced risk-cost model to assist maintenance decision making process has been achieved. TOPSIS, one of the multi-objective decision-making techniques, has been employed to select the best solution for railway maintenance decision making. This model combines a risk model with a cost model to be developed into a cost benefit based risk decision making tool. It can provide decision makers with a ranking of maintenance options or strategies in terms of preference degrees. A relevant paper has been accepted and will be published soon.

 The objective of application of the proposed methodology and tool to railway maintenance decision making has been achieved. The developed software based on

CHAPTER 9: CONCLUSIONS AND RECOMMENDATIONS

Innovative features of this research are emphasised as follows:

Innovation 1:

The proposed railway safety risk model is developed based on FRA and fuzzy-AHP approaches, where the potential risk to railway operations is assessed in terms of four parameters, i.e. FF, CP, CS and WF. It is quite appropriate for the circumstance where some risk events frequently happen and may possibly lead to serious consequences depending on the existing risk control measures. It is worth noting that by using four parameters could help risk analysts with likelihood analysis and even with risk control measures that are designed to reduce the likelihood aspect of risk, since the CP is introduced in the assessment. More risk information, such as frequency and probability, which can be derived either from expert judgements or past records, can be directly used in the risk estimation. Finally, this will affect the overall risk ranking, so that the hazard event with very high occurrence frequency but very low consequence probability or with very low occurrence frequency but very high consequence probability can be identified.

Innovation 2

In any cases, if no existing risk data and information available, subjective estimations can be used in the proposed risk analysis modules. The proposed railway safety risk model allows vague and imprecise descriptors such as “likely” and “impossible” to be

used directly to capture expert judgements and it also provides a flexible method of combining the opinions of experts with various experiences from different backgrounds.

Innovation 3

Improved Fuzzy- AHP is employed for the risk assessment, which only requires few judgements from experts without any consistency test. This will reduce the complexity of the application of Fuzzy-AHP.

CHAPTER 9: CONCLUSIONS AND RECOMMENDATIONS

Innovation 4

The development of software based on the proposed risk model is designed especially for railways. Compared to other tools, the advantages of the developed software can be summarised as follows:

 It can combine expert knowledge and engineering judgments with other risk historical data for the railway safety and risk assessment in a consistent manner;  It can deal with imprecise, ambiguous, incomplete and uncertain information in the assessment;

 It can apply linguistic expressions directly to the risk assessment;  It can provide a flexible structure for risk analysis.

Innovation 5

The risk-based decision making module that combines the proposed safety risk model and a cost model, has been developed for maintenance option decision making. By using this model, preference degrees of maintenance options can be determined in which risk reduction and cost are taken into consideration. The results from the system can demonstrate that the maintenance option with the highest preference degree can reduce the RL of the system as low as reasonably practicable.