Uncertainty Management in the Design of Multiscale Systems

Abstract

In this paper, the opportunities for managing uncertainty in simulation-based design of multiscale systems are explored using constructs from information management and robust design. A comprehensive multiscale design problem, the concurrent design of material and product is used to demonstrate our approach. The desired accuracy of the simulated performance is determined by the trade-off between computational cost for model refinement and the benefits of mitigated uncertainty from the refined models. Our approach consists of integrating: (i) a robust design method for multiscale systems and (ii) an improvement potential based approach for quantifying the cost-benefit trade-off for reducing uncertainty in simulation models. Specifically, our approach focuses on allocating resources for reducing model parameter uncertainty arising due to insufficient data from simulation models. Using this approach, system level designers can efficiently allocate resources for sequential simulation model refinement in multiscale systems.

Managing Sociotechnical Complexity in Engineering Design Projects

“…This section presents aspects of socio-technical design complexity from the perspective of the authors. In the broader scope of Systems Engineering, the term complexity can have multiple facets [14, p.57], yet in the context of Engineering Design, it has always been tied up with the challenges stemming from aspects of uncertainty, iteration, multidisciplinary, and dynamic behaviour of DPs [4,5,[15][16][17]. The socio-technical aspect of design complexity is based on the premise that actors involved in the DP interact and negotiate a solution that can be considered as satisfactory.…”