Conceptually Robust Knowledge Generation in Early Stage Complex Design

Abstract

Modern engineering design is a complex, path dependent process in which knowledge is generated for decision making through time. While this in and of itself poses an immense challenge, designers must also coordinate their efforts across a number of design disciplines to produce a converged design in the presence of exogenous factors such as shifting requirements and changing information landscapes. The presence of such factors all too often requires large portions of the design to be revised, leading to excessive rework, design churn, and integration failures in the design process. This has spurred an interest in the notion of conceptual robustness, however the approaches to date remain focused on the product being developed rather than on the knowledge generated to create the product. As such, little has been done to understand the conceptual robustness of a design process, and focusing on knowledge structures provides a novel method for designers to effectively manage these complex design tasks. This helps ensure design activities are robust against future changes in the design landscape.

The framework presented in this thesis, the Knowledge-Information (K-I) Framework, utilizes a multi-layer network approach to represent how information sources are translated into knowledge structures and is analyzed using a number of novel entropy metrics. The framework considers the information-knowledge interplay at two scales: (1) at a local, intra-discipline level and (2) at a global, design integration level. These multi-layer networks are analyzed to reveal conceptual robustness insights for individual disciplines, and throughout the process of integrating disparate sources of knowledge between disciplines. The framework provides a novel perspective of what it means for a knowledge structure to be robust, and enables emergent design failures to be identified earlier on in the design process.

The utilization and analysis of the K-I Framework enable design knowledge to be explored in the context of conceptual robustness. First, novel entropy-based temporal metrics are developed which leverage concepts from both Network Theory and Information Theory to provide new perspectives to analyze knowledge and information structures over the course of a design activity. Second, the theoretical basis of the K-I Framework is outlined, along with the processes by which local and global structures are developed and the way in which they interact. Third, a case study is presented which highlights how different calculation strategies yield different local knowledge structures in relation to calculating the same desired knowledge entity. Finally, an additional case study is presented which focuses on capturing global knowledge integration dynamics in performing an Analysis of Alternatives (AoA) study of a naval distribution system. The results of the case studies are used to draw conclusions about the conceptual robustness of design knowledge generation.