Uncertainty quantification for maintenance in complex engineering systems

This PhD will focus on how technical/engineering uncertainties and the wider enterprise related uncertainties associated to the supply chain, logistics solutions and requirements definition can be quantified. The PhD will aim to offer techniques to quantify uncertainty in a scientific manner for various scenarios where the data is potentially incomplete, inconsistent, inaccessible, and relies on expert opinion. Uncertainty prevents the ability to estimate the equipment operational availability and cost of maintaining equipment with confidence. Thus, there is a need for uncertainty quantification approaches, which sets the focus for this PhD project. The project is co-sponsored by Dstl and the UK MoD, which will enable applied research to be conducted. Uncertainty is the stochastic behaviour of any physical phenomenon that causes the indefiniteness of outcomes, which means the expected and actual outcomes are typically not the same. The technical uncertainties for maintenance may include: degradation, no-fault found, obsolescence, and failure. On the other hand, the enterprise related uncertainties may include: enterprise resilience, requirements, supply chain integration, and organisational re-structuring. In this PhD there are multiple challenges of interest: How can we aggregate the overall impact of uncertainties e.g. across multiple elements, systems, organisations? Expert opinion driven uncertainty quantification; where there is a lack of standardised way to quantify uncertainty and the experiences of individuals play a key role in determining the potential impact on cost and availability.  As part of the PhD there will be a range of training offerings for the student, including: Manufacturing Department – Doctoral Training Programme Operations Excellence Institute – Visualisation programme A range of MOOC based training offerings will be offered Visits to other uncertainty...