Viravanh SOMVANG
WELBEES
Viravanh is CEO and co-founder of WELBEES. She is a graduate engineer from the French National School of Civil Aviation (ENAC). She also holds a master of science (MSc) in Human Factors and Safety Assessment from the University of Cranfield (United Kingdom). Her expertise includes Human Factors, safety management, fatigue risk management and workload assessment, particularly within aviation.
Viravanh has been working in close collaboration with Philippe Cabon for several years on fatigue issues including the development of fatigue guidance documents and training courses and the implementation of fatigue risk management systems within the transportation industry. Her work covers a range of consulting services for many French and European airlines. These include customised support to managing fatigue-related risk to the full implementation of an operational Fatigue Risk Management System (FRMS). Her experience also encompasses the evaluation of bus drivers’ fatigue.
Viravanh has been involved in numerous studies involving subjective and objective fatigue data collection on the field. She has expertise in the chronobiological evaluation of work schedules, including the use of biomathematical models of fatigue. Viravanh has recently led a research project on behalf of RSSB (Rail Safety and Standards Board, UK) aiming at comparing the sensitivity of five biomathematical models of fatigue.
Many rail companies use fatigue assessment tools based on biomathematical models (BMM) as one part of their assessments of likely staff fatigue. The primary purpose of these tools is to estimate the impact of hours of work on sleep, fatigue, and performance. Whilst guidance is available on the role and generic limitations of BMMs, it does not compare how well each predicts fatigue, and omits the most commonly used tool in GB rail - Health and Safety Executive’s Fatigue and Risk Index. Further work was needed to complement the existing guidance documents with an analysis of the relative merits of the available BMMs. In this context, the Rail Safety and Standards Board (RSSB) commissioned a research project to produce practical guidance on the use of BMMs and assist GB rail companies in selecting the most appropriate model for their particular needs and circumstances.
The research was carried out in five stages:
1. Analyse the GB rail industry needs regarding the use of BMMs
2. Compare the 5 selected models against a set of evaluation criteria relevant to the GB rail industry
3. Compare the sensitivity of the models towards various fatigue factors
4. Assess the impact of individual parameters on model estimates
5. Develop a guidance document to meet the information needs of the GB rail industry regarding the use of BMMs.
The research included consultation with staff from the GB rail industry including safety/operational safety staff, rostering staff and managers who use tools to predict fatigue.
A sensitivity analysis compared the outputs of the five BMMs studied to evaluate how they compare in their assessment of likely staff fatigue. The results show that, in general, the models tend to correlate with each other. However, the comparison of their relative sensitivity to specific fatigue factors relevant for the GB rail industry emphasised the great variability among the models. Depending on the type of fatigue issues which the company may wish to focus on in terms of fatigue management and scheduling, the choice of BMMs may vary. There is actually no one model that clearly stands out as the overall best or worst. Each of the currently available fatigue models has their own benefits and limitations and there is no model that will perfectly match the GB rail industry needs. The final aim of the research project was to design a practical guidance for GB rail companies which are willing to invest in a model within the framework of their Fatigue Risk Management Systems (FRMS) enabling them to select the appropriate tools. Industry should then be better equipped to evaluate their base rosters to identify shifts that have a higher risk of resulting in worker fatigue, and re-roster accordingly to reduce the risk.
Fatigue risk management, work hours, breaks, shift work and on-call work
