Qualitative Knowledge Construction for Engineering Systems: Extending the Design Structure Matrix Methodology in Scope and Procedure

Abstract

This thesis presents a new modeling framework and research methodology for the study of engineering systems. The thesis begins with a formal conceptualization of Engineering Systems based upon a synthesis of various literatures. Using this conceptualization, a new modeling framework is presented called the Engineering Systems Matrix (ESM). The ESM is an improvement to existing system-level modeling frameworks, such as the Design Structure Matrix (DSM), by providing a dynamic, end-to-end representation of an engineering system. In support of this contribution, a new research methodology is presented called Qualitative Knowledge Construction (QKC). QKC can be thought of as a Bayesian-type approach to grounded theory. The methodology integrates qualitative social science with quantitative methods by developing a procedure for translating textual reports of observations, interview transcripts, system documentation, and figures into coded data represented in the ESM. The thesis develops the ESM framework and the QKC methodology in the context of - a real world engineering system, a US Air Force miniature uninhabited air vehicle (MAV) product development system.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2007
Accession Number
ADA470222

Entities

People

  • Jason E. Bartolomei

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Airframes
  • Business Administration
  • Computer Programming
  • Engineers
  • Health Services
  • Information Systems
  • Knowledge Management
  • Medical Personnel
  • Military Science
  • Network Science
  • Operations Research
  • Organizational Structure
  • Spreadsheet Software
  • Systems Engineering
  • Warfare

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Software Engineering
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML