Mitigating the influence of uncertainty in design projects without sacrificing performance is challenging, but also important as it may reduce the risk of engineering projects delivering over time or budget. In this paper, we discuss process modelling and simulation as a route to understanding the impact of uncertainty and thereby understanding robustness in design processes. We focus on robustness of process duration with regard to delays in constituent tasks. Firstly, we discuss some patterns by which processes respond to uncertainty by analysing how changes to the duration of an individual task can affect the overall duration of the process. Secondly, we highlight the complexity of process robustness analysis by using a discrete-event Monte-Carlo simulation to investigate the response of a 12-task mechanical component design process to uncertainty in task durations and rework. We argue that valuable insights can be gained by exploring the process response to modifying one input variable at a time. However, due to interdependencies between variables a multivariate approach would be necessary to fully investigate process robustness.@en

The concepts of reliability, robustness, adaptability, versatility, resilience and flexibility have been used to describe how a system design can mitigate the likely impact of uncertainties without removing their sources. With the increasing number of publications on designing systems to have such ilities, there is a need to clarify the relationships between the different ideas. This short article introduces a framework to compare these different ways in which a system can be insensitive to uncertainty, clarifying their meaning in the context of complex system design. We focus on relationships between the ilities listed above and do not discuss in detail methods to design-for-ilities.@en

In this paper, Monte-Carlo simulation is used to investigate how the robustness of hypothetical process fragments is influenced by the number of dependencies between tasks and the resource constraints within the cluster. We show how aggregation of these results on a graphical 'robustness profile' allows conclusions to be drawn about the factors which govern process robustness, and argue that this can provide insight to support the improvement of more complex, realistic processes.@en

The inherent complexity of Product Development (PD) processes, coupled with competitive pressures to deliver products cheaper, faster better, has been a significant source of difficulties in planning and executing many large-scale PD projects. This is evident from the large number of projects that have failed to deliver on their original time or cost expectations. Given the potentially severe consequences of PD process delays, mitigating the impact of uncertainty sources that may affect PD process duration has been a popular research topic. Concepts such as reliability, flexibility, versatility and robustness have been used in the literature to denote process insensitivity to various types and sources of uncertainty. This paper interprets these four related concepts as different types of process insensitivity to uncertainty and thereby contributes to clarifying their meaning in the context of PD processes. We focus on those approaches which aim to mitigate the likely impact of process risks on project performance without removing the sources of these risks.@en