9.1.3 Screening for Real Options “In” an Engineering System: A Step Towards Flexible System Development

The goal of this research is to develop an analytical framework for screening for real options “in” an engineering system. Real options is defined in the finance literature as the right, but not the obligation, to take an action (e.g. deferring, expanding, contracting, or abandoning) at a predetermined cost and for a predetermined time. These are called “real options” because they pertain to physical or tangible assets, such as equipment, rather than financial instruments. Real options improve a system's capability of undergoing classes of changes with relative ease. This property is often called “flexibility.” Recently, the DoD has emphasized the need to develop flexible system in order to improve operational, technical, and programmatic effectiveness. The aim of this research is to apply real options thinking to weapon acquisitions in order to promote the ability of weapon system programs to deftly avoid downside consequences or exploit upside opportunities. The practice of real options in systems engineering is a nascent field of inquiry. One of the most significant challenges in applying real options to engineering systems is the problem of identifying the most efficacious points within the system to create options. In order to identify the points of interest, systems engineers require knowledge about the physical and non physical aspects of the system, insight into sources of change, and the ability to examine the dynamic behavior of the system. We propose a two-phase process to perform this analysis. The first phase is a system representation phase that seeks to create an end-to-end representation of engineering system that includes endogenous interactions across system views and interactions with a systems environment. The next phase is an analysis phase that models the evolution of the engineering system in order to identify the real options in the system. This paper presents the system representation phase and proposes a methodology for creating an end-to-end representation of an engineering system. The methodology for representing an engineering system extends existing systems engineering and architecting methods in two dimensions. First, the framework couples traditional architecting views to represent traceability and endogenous interactions within an engineering system. Second, the framework includes views of the system not represented in traditional engineering frameworks that includes social networks and environmental interactions. The framework uses coupled Design Structure Matrices (DSM) to represent the traditional and new architecting views. The coupled DSMs are organized into an Engineering System Matrix (ESM), which is a holistic representation of an engineering system that captures the critical variables and causal interactions across architectural elements. The result is an analytic framework that captures the qualitative understanding of the system into a single view that is conducive for deep quantitative inquiry. This paper presents a discussion of pertinent literature, an overview of the ESM framework and underlying theory. In addition, this paper previews ongoing research using the ESM to identify options for a mini-air vehicle (MAV) weapon development system.

[1]  Philippe Castagliola,et al.  A Comparison of the Readability of Graphs Using Node-Link and Matrix-Based Representations , 2004, IEEE Symposium on Information Visualization.

[2]  Craig M. Rowles.  System integration analysis of a large commercial aircraft engine , 1999 .

[3]  J. DOUGLAS HILL,et al.  Unified Program Planning , 1972, IEEE Trans. Syst. Man Cybern..

[4]  Ali A. Yassine,et al.  Characterizing complex product architectures , 2004, Syst. Eng..

[5]  Kevin Otto,et al.  An empirical foundation for product flexibility , 2005 .

[6]  Carol Alexander.  The handbook of risk management and analysis , 1996 .

[7]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[8]  R. Neufville.  Real Options: Dealing With Uncertainty in Systems Planning and Design , 2003 .

[9]  Cory A. Cooper,et al.  A Systems Architectural Model for Man-Packable/Operable Intelligence, Surveillance, and Reconnaissance Mini/Micro Aerial Vehicles , 2005 .

[10]  Louis Cohen,et al.  Quality Function Deployment: How to Make QFD Work for You , 1995 .

[11]  Joseph Homer Saleh,et al.  Weaving time into system architecture : new perspectives on flexibility, spacecraft design lifetime, and on-orbit servicing , 2001 .

[12]  Kim B. Clark,et al.  Design Rules: The Power of Modularity , 2000 .

[13]  Steven D. Eppinger,et al.  Managing the integration problem in concurrent engineering , 1993 .

[14]  Dov Dori,et al.  Object-process methodology - a holistic systems paradigm , 2013 .

[15]  Steven D. Eppinger,et al.  Integration analysis of product decompositions , 1994 .

[16]  John N. Warfield,et al.  SOCIETAL SYSTEMS Planning, Policy and Complexity , 1978 .

[17]  Joel Moses,et al.  Foundational issues in Engineering Systems: A Framing Paper , 2004 .

[18]  Tyson R. Browning,et al.  Modeling and analyzing cost, schedule, and performance in complex system product development , 1998 .

[19]  P. John Clarkson,et al.  Change and customisation in complex engineering domains , 2004 .

[20]  Steven D. Eppinger,et al.  Understanding the effects of product architecture on technical communication in product develoment organizations , 2000 .

[21]  Manuel E. Sosa,et al.  Analyzing the Effects of Product Architecture on Technical Communication in Product Development Orga , 2000 .

[22]  John N. Warfield,et al.  A Science of Generic Design: Managing Complexity Through Systems Design , 1994 .

[23]  Lesley F. Wright,et al.  Information Gap Decision Theory: Decisions under Severe Uncertainty , 2004 .

[24]  Warren P. Seering,et al.  THE INFLUENCE OF ARCHITECTURE IN ENGINEERING SYSTEMS , 2004 .

[25]  Steven D. Eppinger,et al.  Organizing the Tasks in Complex Design Projects , 1991, MIT-JSME Workshop.

[26]  Kosuke Ishii,et al.  Design for variety: developing standardized and modularized product platform architectures , 2002 .

[27]  Steven D. Eppinger,et al.  Model-based Approaches to Managing Concurrent Engineering , 1991 .

[28]  T. Copeland.  Real Options: A Practitioner's Guide , 2001 .

[29]  Paul R. Carlile,et al.  Architectural Optimisation Using Real Options Theory and Dependency Structure Matrices , 2002, DAC 2002.

[30]  Eun Suk Suh.  Flexible Product Platforms , 2005 .

[31]  D. V. Steward,et al.  The design structure system: A method for managing the design of complex systems , 1981, IEEE Transactions on Engineering Management.

[32]  Tyson R. Browning,et al.  Applying the design structure matrix to system decomposition and integration problems: a review and new directions , 2001, IEEE Trans. Engineering Management.