Modernizing systems engineering : cognitive systems and model-based approaches for spacecraft architecture development
Author(s)Karlow, Brandon (Brandon James)
Cognitive systems and model-based approaches for spacecraft architecture development
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Brian N. London.
MetadataShow full item record
Systems engineering exists as a discipline to enable organizations to control and manage the development of complex hardware and software. These methods are particularly essential in the development of space systems, which feature extremely challenging demands for engineering performance, coupled with extremely limited resources for accomplishing them. Success requires careful attention to the relationships between various components as well as the organizations constructing them. Unfortunately, aerospace organizations routinely struggle with the traditional systems engineering process, and as a result, program managers experience pressure to conclude, curtail or ignore critical elements. The consequence is that cost overruns, slipped schedules and outright failures are a regular feature of the industry. Recent advances in Model-Based Systems Engineering (MBSE) tools and methods provide an opportunity to rectify these issues by better integrating systems engineering capabilities into the engineering development process. By directly networking the engineering models used in the development process to each other and the systems diagrams which describe them, MBSE has the potential to make the development process more responsive to design evolutions and account for changes across the entire space system. In this way, systems engineering could become a more integrated part of the development process and better contribute to successful space systems. Unfortunately, current-generation MBSE tools and methods have yet to fully realize this potential. Critical capability gaps have deterred adoption and relegated their use to academic endeavors. This thesis argues that many of the difficulties encountered in current systems engineering practice - as well as attempts to reform that practice - can be explained with reference to distributed cognition, control theory and the wider field of cognitive systems engineering. Existing tools and techniques, while nominally fulfilling the purposes assigned to them, generally fail to adequately support systems engineers in the cognitive tasks associated with the control and management of development processes. As a result, systems engineers are frequently overburdened in their roles and are unable to fully address the myriad of concerns relevant to the design of good system solutions. A cognitive analysis of the software and hardware devices situated in practical instantiations of development activities can reveal opportunities to improve performance and enhance effectiveness. Such changes would make systems engineering tools easier to use and better tailored to the needs of the system engineering task, encouraging adoption and accomplishing the goals of the MBSE community. A cognitively-informed MBSE approach, in addition to better linking the elements of the engineering effort, can also be used to link the engineering effort to the higher-level needs which drive the engineering process in the first place. One of the biggest challenges any engineering organization faces is managing the "how," "why," and "what" of system development, that is, the engineering logic which determines "how" a given program or system will be built and the business, political or policy logic which determines "why" and "what" system will come into being. Often, these latter concerns are poorly addressed by the space system development process, which can lead to sub-optimal outcomes for the wider organizations involved in the engineering project. Methods which better systematize, quantify and direct the process of stakeholder analysis, concept generation and architecture exploration can aid in the selection of system architectures that better meet the strategic objectives of the organizations which develop and operate space systems. Such methods are demonstrated with respect to an evaluation of possible architectures for a notional large, ultraviolet-visible-near-infrared (UV-VIS-NIR) optical space telescope to succeed Hubble in the late 2020s to early 2030s timeframe. This research draws on MBSE concepts and the legacy of tradespace modeling for system design to extend tradespace modeling to the realm of architectural exploration. Its particular interest is the quantitative treatment of "programmatic factors": the business, policy and political considerations which govern high-level decision-making. Through modeling, these considerations can be directly associated with engineering performance factors, enabling better selection decisions and reinforcing linkages and understanding between the engineering and management levels within an organization. It is intended to leverage existing work in stakeholder modeling, real options, strategic evolution and tradespace exploration to bridge existing divisions between systems engineering and programmatic decision-making processes which can lead to poorly optimized architectures. It is geared towards systems engineers and program managers seeking to account for organizational and higher-level stakeholder needs during the tradespace exploration process and more efficiently and practically integrate these decision frameworks in real-world engineering environments.
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, 2014.Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 230-239).
DepartmentMassachusetts Institute of Technology. Engineering Systems Division.; Massachusetts Institute of Technology. Technology and Policy Program.; Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Massachusetts Institute of Technology
Engineering Systems Division., Technology and Policy Program., Aeronautics and Astronautics.