This paper employs the concept of real options to quantitatively assess resilience. First, the definitions of resilience are distilled from literature in the fields of engineering, management and ecology to give requirements for further assessment. From this, it was found that resilience requires a system to be robust, adaptable and flexible in the face of uncertainty. The main contribution of the paper is to connect these requirements to real options valuation and demonstrate the evaluation of the robust and flexible cases through real options methods. Specifically, Least Squares Monte Carlo method is used to value each option with the robust case being the benchmark and flexibility representing upgrades to the system. This is applied to an illustrative telecommunications case and the properties of the model assessed. The results show that uncertainties on the system can be captured and valued through this method so that it can aid a decision maker to assess which technology option or investment to select for future planning.@en

The concept of resilience has emerged from various domains to address how systems, people and organizations can handle uncertainty. This paper presents a method to improve the resilience of an engineering system by maximizing the system economic lifecycle value, as measured by Net Present Value, under uncertainty. The method is applied to a Waste-to-Energy system based in Singapore and the impact of combining robust and flexible design strategies to improve resilience are discussed. Robust strategies involve optimizing the initial capacity of the system while Bayesian Networks are implemented to choose the flexible expansion strategy that should be deployed given the current observations of demand uncertainties. The Bayesian Network shows promise and should be considered further where decisions are more complex. Resilience is further assessed by varying the volatility of the stochastic demand in the simulation. Increasing volatility generally made the system perform worse since not all demand could be converted to revenue due to capacity constraints. Flexibility shows increased value compared to a fixed design. However, when the system is allowed to upgrade too often, the costs of implementation negates the revenue increase. The better design is to have a high initial capacity, such that there is less restriction on the demand with two or three expansions.@en

The development of models, especially simulation models of both products and processes, has increased in industry and now offer substantial competitive advantages in decision support across many fields. Even so, little is known about the structures of applied modelling processes as the focus so far has primarily been on improving modelling tools and software, methodologies, and modelling outcomes. In this paper, we gain insights into the value creation activities in modelling practice through the analysis of activity structures from 12 different modelling processes across two large UK companies. The results show that modelling process structures can be divided into three distinct process types; ad-hoc modelling for decision support, new model development, and model change management. Existing research mainly considers new model development and therefore it is suggested that the other two types are also part of modelling practice, and therefore should be included in modelling process management. The process types are categorized from a modelling management perspective and a tentative modelling process management toolbox is suggested for further research.@en

Resilience has mostly been thought of as the ability to recover from adversity. However, it is now increasingly recognised that resilience should not only serve as a means for organisations to survive hardship, but also to thrive and prosper. For large-scale engineering systems, such as telecommunications networks and power grids, this is vital due to relatively long life cycles leading to large uncertainties, and also due to the significant investments involved. Exactly how this and thus resilience should be designed into such systems, however, is less well defined. Here, the term resilience is explored through engineering, organisational and ecological literature to understand differing perspectives from select domains before distilling these into the three engineering design lifecycle properties: robustness, adaptability and flexibility. In particular, a distinction is highlighted between adaptability and flexibility following findings in literature. These properties and the concept of resilience are discussed with reference to system performance in order to serve as requirements for designing large-scale resilient engineering systems.@en