As part of an ongoing initiative to using modeling and simulation techniques as a discovery tool for envisioned systems, Abhinay Paladugu, Alicia Fernandez, and Martijn Ijtsma from the Cognitive Systems Engineering Lab (CSEL) have published a new article. This study highlights how work modeling and simulation—considering the dynamics of the environment—can reveal key interactions and uncover emergent behavior in complex systems. Importantly, the study emphasizes that these techniques are not used to validate the system but rather to discover new insights about system behavior and design.
The paper introduces a three-lens approach to analyzing envisioned systems:
• Feasibility
• Comparing alternate versions
• Robustness
Through case studies and detailed walkthroughs, the research demonstrates how modeling and simulation can be systematically applied, starting with paper-based descriptions and evolving into fully simulated work models. This research provides valuable guidance for designers and engineers, integrating modeling and simulation into the design process to make more informed decisions. The case study highlights the benefits of leveraging computational modeling and simulation as a discovery-driven method.
If you want to learn more or explore additional examples, you can view the dissertation of Abhinay Paladugu for further insights into this methodology.
To read the full article, visit Sage Journals: Computational Simulation of Distributed Work as a Discovery Tool for Envisioning Future Operations.
Abstract
Envisioning new kinds of operations requires systematically developing architectures, work procedures, and artifacts to support human and machine agents in coordinating within dynamic environments. Accurately predicting how envisioned operations will unfold is challenging as (1) early design-phase descriptions of architectures, work procedures, and artifacts are often underspecified, and (2) key outcomes of interest emerge from interactions between cognitive work and environmental dynamics. This paper discusses how computational simulation of work can serve as a discovery tool for envisioning future operations. We introduce a three-phase approach using the Work Models that Compute (WMC) framework, which involves converting paper-based representations of work into computational models, developing scenarios and test conditions, and simulating work dynamics to analyze emergent behaviors. We illustrate this approach through a case study on developing contingency management procedures for envisioned air transport operations, specifically Urban Air Mobility (UAM). The case study demonstrates how computational simulation can (1) reveal the need for clearer design specifications, (2) uncover interactions and emergent behavior that may lead to undesirable outcomes, such as coordination surprises, and (3) identify trade-offs between multiple design options. Insight from simulation can complement other cognitive systems engineering methods to refine and enhance the feasibility and robustness of envisioned operations.