  The classical approach to design a system is based on a deterministic
perspective where the assumption is that the system and its environment are
fully predictable, and their behaviour is completely known to the designer.
Although this approach may work fairly well for regular design problems, it is
not satisfactory for the design of highly sensitive and complex systems where
significant resources and even lives are at risk. In addition it can results in
extra costs of over-designing for the sake of safety and reliability. In this
paper, a risk-based design framework using Simulation Based Probabilistic Risk
Assessment (SIMPRA) methodology is proposed. SIMPRA allows the designer to use
the knowledge that can be expected to exist at the design stage to identify how
deviations can occur; and then apply these high-level scenarios to a rich
simulation model of the system to generate detailed scenarios and identify the
probability and consequences of these scenarios. SIMPRA has three main modules
including Simulator, Planner and Scheduler, and it approach is much more
efficient in covering the large space of possible scenarios as compared with,
for example, biased Monte Carlo simulations because of the Planner module which
uses engineering knowledge to guide the simulation process. The value-added of
this approach is that it enables the designer to observe system behaviour under
many different conditions. This process will lead to a risk-informed design in
which the risk of negative consequences is either eliminated entirely or
reduced to an acceptable range. For illustrative purposes, an earth observation
satellite system example is introduced.
