Biased Information Passing Between Subsystems Over Time in Complex System Design

Abstract

During the early stage design of largescale engineering systems, design teams are challenged to balance a complex set of considerations. The established structured approaches for optimizing complex system designs offer strategies for achieving optimal solutions, but in practice suboptimal systemlevel results are often reached due to factors such as satisficing, illdefined problems, or other project constraints. Twelve subsystem and systemlevel practitioners at a large aerospace organization were interviewed to understand the ways in which they integrate subsystems in their own work. Responses showed subsystem team members often presented conservative, worstcase scenarios to other subsystems when negotiating a tradeoff as a way of hedging against their own future needs. This practice of biased information passing, referred to informally by the practitioners as adding “margins,â€‌ is modeled in this paper with a series of optimization simulations. Three “biasâ€‌ conditions were tested: no bias, a constant bias, and a bias which decreases with time. Results from the simulations show that biased information passing negatively affects both the number of iterations needed and the Pareto optimality of systemlevel solutions. Results are also compared to the interview responses and highlight several themes with respect to complex system design practice.