Systems Engineering Advancement Research Initiative

RESEARCH BULLETIN DECEMBER 2006 Vol. 1, Issue 3

About SEAri The Systems Engineering Advancement Research Initiative, known as SEAri, brings together a set of sponsored research projects and a consortium of systems engineering leaders from industry, government, and academia. SEAri is uniquely positioned within the Engineering Systems Division (ESD) at the Massachusetts Institute of Technology (MIT), a new kind of interdisciplinary academic unit that spans most departments within the School of Engineering, as well as the School of Science, the School of Humanities, Arts, and Social Sciences, and the Sloan School of Management. This setting offers a robust research and learning environment for advancing systems engineering to meet the contemporary challenges of complex socio-technical systems. SEAri has strategic relationships with several educational and research programs at MIT, including the MIT System Design & Management Program (SD+M) and the Lean Aerospace Initiative (LAI) Research Program at MIT. Find out more at http://seari.mit.edu/

SEAri Consortium Launched SEAri is launching a new consortium focused on the advancement of systems engineering to enhance its ongoing sponsored research program. The consortium’s goals include expanding the current research, accelerating the transition of research outcomes to industry practice, and engaging members in collaborative projects. Whereas SEAri sponsored research projects are designed to suit an individual sponsor’s interest, the consortium research projects will address the broad needs of the membership for advanced theory, methods and practices. The research will leverage the participation of multiple members in a collaborative manner, performing research that can not adequately be accomplished within the bounds of a single sponsor’s organization and resources. The consortium membership structure is tiered (Platinum, Gold, Silver, Bronze), offering varying degrees of benefits and engagement commensurate with the membership level. The members of the Lean Aerospace Initiative (LAI) Consortium and the partner companies for the MIT System Design & Management (SDM) Program, both historically the major sponsors and advocates for systems engineering research in the MIT Engineering Systems Division, will be receiving Bronze level benefits; some may also elect to participate in SEAri at an enhanced membership level. The consortium will be an important enabler for bringing academia, industry, and government experts together for collaborative learning and joint research on advanced systems engineering topics. For further information on consortium membership, please see the SEAri website (http://seari.mit.edu/) or contact us at seari@mit.edu.

A Message from the Director In this inaugural issue of the SEAri Research Bulletin, it is worth reflecting on what motivates our overall research program, as well as our decision to complement the existing sponsored research with a new consortium. During recent years, systems engineering has received increased focus and expanded its footprint on a global scale. Many new university departments and programs have been developed in response to higher demand for skilled engineers who can think systemically about complex systems. As a systems community, we see the enterprises in which systems engineering is practiced reaching new levels of complexity. At the same time, the advancement of technology opens new possibilities for conducting engineering analysis, modeling, simulation and design. With these changes in systems, their environments, and the enabling infrastructure, we have an urgent need for more research to advance the theory and practice of systems engineering. Yet, traditional research structures and educational institutions do not easily accommodate broad interdisciplinary systems research. Further, the ability to transition new knowledge and research outcomes to the community of practice is weak; innovations in the mechanisms to do so are essential. In the domain of complex systems there are tremendous opportunities for success and equally tremendous risks of failure. Recent studies highlight what we believe to be

Table of Contents Message from the Director ................................ 1-2 Research Spotlight 1 ......................................... 3 Research Spotlight 2 ......................................... 5 SEAri News........................................................ 7 Upcoming Events............................................... 8

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the four most significant challenges: (1) while sound traditional systems engineering practices exist, these are not always effectively applied; (2) traditional systems engineering practices are not sufficient for the engineering of complex systems of systems; (3) the current and future workforce is both insufficient and inadequately prepared for addressing complex systems challenges; and (4) successfully evolving systems engineering will require understanding how to manage the conflict and cooperation of large sets of stakeholders. SEAri seeks to solve these challenges by bringing together experts from industry, government, and academia to engage in collaborative research. Our sponsored research program has proven successful in targeting specific problems of a single sponsor. The new consortium is designed as a mechanism for undertaking problems that are both appropriately and more feasibly undertaken as joint endeavors. While professional societies play a significant role in identifying and addressing global issues through technical exchange and focused working groups, a university setting provides the rigor, venue, and mechanisms necessary to conduct deeper levels of research. The MIT Engineering Systems Division (ESD) provides a unique enabling environment for the mission of SEAri to advance the theories, methods, and effective practice of systems engineering applied to complex socio-technical systems through collaborative research. MIT ESD is a “division,” a new kind of interdisciplinary academic unit that spans most departments within the School of Engineering, as well as the School of Science, School of Humanities, Arts, and Social Sciences, and Sloan School of Management. This setting offers a robust, interdisciplinary research and learning environment for tackling the challenges of complex socio-technical systems. As further leveraging factors, SEAri has strategic relationships with several educational and research programs at MIT, which include the Lean Aerospace Initiative (LAI) and the System Design & Management (SDM) Program. Our current sponsored research portfolio is diverse, and includes government agencies and academic partners from several countries, defense contractors, and commercial product and services enterprises. We actively collaborate with university colleagues from other institutions to create synergies in research outcomes and alignment in research agendas. Through our new consortium we seek to engage with many more systems engineering leaders to better understand their problems and environments so that we can shape our research programs to achieve and deliver more impactful research outcomes. By engaging in the consortium at their desired level, systems engineering

leaders can gain early access to research findings, guide priorities for research, and participate in research summits and deep technical exchanges. Since industry and government have limited resources to invest in systems research, the consortium provides a structure for pooling talent and resources for addressing significant problems of the broader systems community. We recognize it is unlikely such problems will be solved by the single-sponsor research investment model, and seek to develop a consortium that can deliver research outcomes that benefit the systems community at large.

Donna H. Rhodes, SEAri Director

SEAri Community Leadership Dr. Donna Rhodes, Director, acting SE-Field lead Dr. Adam Ross, V-STARS lead Dr. Ricardo Valerdi, R-STARS lead Professor Daniel Hastings, Aero/Astro, ESD Professor Deborah Nightingale, Aero/Astro, ESD Pat Hale, SDM Fellows Program Director Affiliated Faculty Professor Missy Cummings, Aero/Astro Professor Richard de Neufville, Civil E., ESD Professor Olivier de Weck, Aero/Astro, ESD Professor Daniel Frey, Mech E., ESD Professor Christopher Magee, Mech E., ESD Professor Daniel Roos, Civil E., ESD Professor Joseph Sussman, Civil E., ESD Professor Annalisa Weigel, Aero/Astro, ESD Graduate Research Assistants Matthew Richards Nirav Shah Jason Bartolomei Tsoline Mikaelian Spencer Lewis Jennifer Wilds David Broniatowski Sponsored Research Partners Singapore DSTA US AFOSR NSF/IGERT POET Aerospace Corp. NASA Goddard LAI MITRE

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Exploratory Research Studies Best Practices in Collaborative Distributed Systems Engineering Research by: Darlene Utter, S.M., Eng. Systems

Darlene Utter recently completed her masters research investigating emerging best practices in collaborative distributed systems engineering (CDSE), focused on three major objectives. The first was to define successful social and technical CDSE practices by examining how US aerospace and defense companies are performing this practice, and lessons they have learned. Successful CDSE involves many factors; eleven are addressed in the research: use of CDSE and collaboration tools; scheduling and conduct of meetings; communication; training of engineers; overcoming social and cultural differences; making decisions; adapting the product; overcoming issues and barriers; determining and measuring CDSE benefits; managing knowledge and data; and coordination of processes. The second research objective was to identify key CDSE issues encountered; barriers and how these were overcome; and practices that were tried and failed in an effort to assist companies who are starting to perform CDSE and prevent them from repeating the same mistakes. The third objective was to identify topics for future research. Utter’s thesis summarizes the motivation for the research: The United States aerospace and defense budgets are shrinking, resources are scarce and requirements are more demanding; aerospace and defense enterprises are expected to deliver a more capable product in less time and with fewer resources. To achieve this tough mission, the enterprises that comprise the US aerospace and defense industries must form strategic partnerships and collaborations to utilize their respective resources, knowledge, and expertise to meet their customers’ needs. Collaboration, be it between competing companies or within different divisions of the same company, is necessary for the survival of each company and the defense industry. In the past, aerospace and defense company relationships consisted mostly of a prime contractor, with sub-contractors providing a specific hardware or software subsystem, as specified by the prime contractor. Today, aerospace and defense company relationships are moving more toward that of “partners” where the previous supplier or sub-contractor for hardware or software subsystems is now sharing in the overall system design and engineering efforts. Since the partner companies and intra-company divisions are still geographically distributed throughout the US, it is

necessary for contractors to perform collaborative, distributed systems engineering (CDSE) over several geographical locations. Previous research has demonstrated that the design practices of distributed design teams differ from those of traditional, co-located teams. However, many companies today are performing CDSE using processes and methods developed for traditional SE environments and are therefore encountering many issues. Successful SE practices are difficult to carry-out when performed by a traditional, collocated enterprise. The addition of geographic distribution and cross-company or intra-company collaboration in SE presents a myriad of social and technological challenges that necessitate new and different SE methods for success. Best practices for CDSE are currently unknown (or undocumented). In a preliminary effort to benchmark the current state of practice, this research presents the collection of CDSE lessons learned and success factors from two case studies carried out at two US aerospace and defense companies. The case studies examine many different factors that pertain to current CDSE efforts, including collaboration scenarios; collaboration tools; knowledge and decision management; SE practices and processes; SE process improvements; SE culture; SE project management, SE organization; and SE collaboration benefits and motivation. The research has resulted in a preliminary set of CDSE “success factors” which extend from the research, as well as from factors uncovered in the literature. Five examples of success factors are summarized below:

1. Establish Trust: Trust enables open communications between team members, and inspires confidence in the final product and cooperation between teams.

2. Invest in up-front Planning Activities: Spending more time on the front end activities and gaining team consensus shortens the implementation cycle (and especially avoids the pitfalls they may occur if issues of team mistrust, conflict, and mistakes surface during implementation).

3. Perform Visual Management of the Development Process: Visual management of the development process, may be useful in establishing a sense of team, as well as keeping the team immediately up-to-date on important programmatic and product related issues. This visual management may be possible by using the collaboration tools or environments and/or team room displays. Imagine

Research Spotlight 1

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signing on to a collaborative environment, and upon logging in, immediately being informed of a subsystem’s current testing or development status (perhaps in red, yellow, green). Or similarly, entering a CDSE team room to find the color-coded schedule progress of each team on an LCD display. These visual cues provide immediate feedback without having to scour schedules, requirements, or test data and would be relatively simple to implement.

4. Define Decision Making Responsibilities: This matrix outlines the roles a group’s managers would play in each of the major decisions. Included in the matrix was not only which manager would make the actual decision, but also which managers needed to be consulted beforehand, and which should be informed after decisions were made.

5. Provide CDSE Training: Training can make a huge impact, as exemplified in a case of the GE 6sigma black belts. GE recognized the need for virtual teaming as a future key mission critical need, and has trained all of their “Black Belts” since 1998 in virtual teaming. The same type of training can be used throughout SE organizations for how to work in CDSE environment.

Utter’s research confirms that success in CDSE can not be achieved without first overcoming several possible barriers, including many of the issues encountered by co-located teams and additional ones unique to the collaborative distributed team. In addition to typical issues with time zones and misaligned schedules, the thesis identifies potential barriers unique to CDSE, for example: Too many Perspectives: Although also cited as a CDSE benefit, research has demonstrated that the diversity of knowledge held by collaborating systems engineers (or any collaborating teams with diverse experiential and intellectual backgrounds) can also be a barrier to successful knowledge sharing. It is difficult to share and understand knowledge when engineers do not share the same social, occupational or cultural background. This is because different experiential and intellectual backgrounds can lead to different “perspectives, priorities, typical approaches to problem solving, and even terminology.” These differences can often be overcome when collaborators work together frequently in highly interactive settings. However, in distributed collaboration, engineers are limited in their face-to-face contacts and the collaboration settings are not highly interactive or very frequent. Although the primary purpose of this research was to document current CDSE practices in industry, including issues encountered, lessons learned, and success

factors, thirteen emerging CDSE-related “success themes” have been identified based on this CDSE research. These relate to collaboration situation and management; collaboration tools; knowledge, data and decision management; SE processes and practices; and the social and cultural environment. Elaborated in the thesis, an example of one of these success themes is: Program kick-off face-to-face, and regularly scheduled face-to-face meetings are necessary to build and maintain relationships and trust between teams. One project team in the study cited that issues of mistrust, company cultural differences, and misunderstandings have been remedied by repeated interactions and the ability to build relationships over time. The thesis recommends several areas for follow-on research, and SEAri researchers are presently exploring the concept for a “SE Collaboration Maturity Factor” proposed by Utter. The research cases indicated differences in maturity in regard to several factors which foster or impede CDSE; using a capability maturity model framework may lead to a useful assessment and process improvement instrument for organizations performing CDSE types of projects. Utter’s research was sponsored by Raytheon Corporation, in affiliation with the Lean Aerospace Consortium. Plans are to publish results of the research in a journal article under development by Utter and her research advisor, Donna Rhodes. A pre-release paper will be posted on the SEAri website. Darlene Utter

Darlene Utter is currently a systems engineer at Raytheon Integrated Defense Systems in Massachusetts, where she has worked on requirements development, systems design and analysis, system modeling, and system integration for radar systems planned for the Navy's next generation destroyer. Previously,

Darlene held several internships in academia and the US aerospace and defense industry. Darlene recently completed her S.M. in Engineering Systems at MIT (2007) with research interests including collaborative SE, SE processes, and system analysis methods. While at MIT for her graduate research, Darlene collaborated with the Lean Aerospace Initiative (LAI). Darlene received her S.B. from MIT in Aerospace Engineering and Information Technology (2004).

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Managing Unarticulated Value: Changeability in Multi-Attribute Tradespace Exploration Research by Adam Ross, Ph.D., Eng. Systems

One of the principal goals for systems engineering is to maximize the perception of system success by system stakeholders. Success can be defined narrowly in terms of meeting performance, cost, and schedule expectations, or more broadly in terms of stakeholders perceiving a net benefit from having the system. Focusing on the broad interpretation, maximizing net benefit, requires attention on how value is perceived by stakeholders through interaction with the system. Understanding how people perceive value is fundamental to creating valuable systems. While an assumption of static needs, often captured in terms of requirements, simplifies the creation of systems and criteria for success, such an assumption violates how people actually perceive value and will not ensure the creation of a valuable system. Since needs are context dependent, which includes changing environments and limited access to information, the value perceptions of system stakeholders will inevitably change as well. How can systems achieve success when the criteria for true success, delivery of value, changes over time? One approach is to design systems for Value Robustness. A framework for creating value robust systems in the face of changing value perceptions during the architecting and design of systems was proposed by Ross in his doctoral dissertation. Both unarticulated value, that which is not explicitly communicated to system designers, and dynamic value, that which changes over time, are used to motivate the dynamic Multi-Attribute Tradespace Exploration (MATE) process. Value can be represented as decision maker perceived attributes, which are metrics that reflect how well decision maker defined objectives are met. One approach to ensuring that system designers account for future changed value perceptions is to think about these attributes according to the ease by which the system can display them. Since attributes can be on function or form, to “display” an attribute means that the system does or is the attribute. For example, an attribute could be the color of the system, or the spatial resolution of the images it generates. The cost to display these attributes is how much it takes to either have or change color, or have or change an image spatial resolution. The attribute class spectrum from least to most costly

ranges from articulated “designed for”, class 0 attributes, to inaccessible value, class 4 attributes.

Value Spectrum: Attribute Classes

As values become articulated, system can respond with change

CBA D

UnarticulatedArticulatedE

FC

BA DUnarticulatedArticulated

E

F

Articulated Value

Cheap Latent ValueAccessible Value

Inaccessible Value

0

0

small

small/large

∞

Cost to Display

Perceived Value SpectrumArticulated Unarticulated

Free Latent Value

Class

01234

Articulated Value

Cheap Latent ValueAccessible Value

Inaccessible Value

0

0

small

small/largesmall/large

∞

Cost to Display

Perceived Value SpectrumArticulated Unarticulated

Free Latent Value

Class

01234

Value Spectrum: Attribute Classes

As values become articulated, system can respond with change

CBA D

UnarticulatedArticulatedE

FC

BA DUnarticulatedArticulated

E

F

Articulated Value

Cheap Latent ValueAccessible Value

Inaccessible Value

0

0

small

small/large

∞

Cost to Display

Perceived Value SpectrumArticulated Unarticulated

Free Latent Value

Class

01234

Articulated Value

Cheap Latent ValueAccessible Value

Inaccessible Value

0

0

small

small/largesmall/large

∞

Cost to Display

Perceived Value SpectrumArticulated Unarticulated

Free Latent Value

Class

01234

Over time, decision makers may change their mind on which attributes provide value and the system that can change displayed attributes to match the new expectations will provide more value than a system locked in to a fixed attribute set. Displaying matching attributes does not necessarily require a physical system change, especially if the system already contains latent value. More generally, however, a system may not have the attributes as latent value and must respond to changing expectations with system change. In discussing change, the concepts of flexibility, adaptability, rigidity, robustness, scalability, and modifiability are often used in a somewhat loose fashion. Without concrete specification of these terms they cannot be used to drive system design. Ross proposed these “-lities” to be different aspects of the same concept: changeability. In order to have a change, three aspects must be defined: the change agent, change effect, and change mechanism. The change agent is the motivator of the change itself, for example a user or an autonomous software agent. The change effect is the difference in states from before and after the change has occurred, for example the magnitude of an attribute could change from small to large. The change mechanism is the path the system takes to get from the before to after state of the change, for example the color of a car could change from dark to light blue due to a new paint job or to fading caused by the sun. Adaptability, rigidity, and flexibility relate to the location of the change agent: external, none, or internal to the system boundary respectively. Robustness, scalability, and modifiability relate to the effect of change in the attributes: none, level, or set respectively.

Research Spotlight 2

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Classifying Change: -ility TaxonomyChangeability: Adaptability, Rigidity, Flexibility,

Robustness, Scalability, Modifiability

Change Agent

System changeability can be specified in terms of change agents, effects, and mechanisms

Change EffectChange Effect

Parameter level(Scalable)

Parameter set(Modifiable)

None(Robust)

Change Effect

Parameter level(Scalable)

Parameter set(Modifiable)

None(Robust)

Change Effect

Parameter level(Scalable)

Parameter set(Modifiable)

None(Robust)

Change Agent

Internal(Adaptable)

External(Flexible)

None(Rigid)

Change Agent

Internal(Adaptable)

External(Flexible)

None(Rigid)

Classifying Change: -ility TaxonomyChangeability: Adaptability, Rigidity, Flexibility,

Robustness, Scalability, ModifiabilityChangeability: Adaptability, Rigidity, Flexibility,

Robustness, Scalability, Modifiability

Change Agent

System changeability can be specified in terms of change agents, effects, and mechanisms

Change EffectChange Effect

Parameter level(Scalable)

Parameter set(Modifiable)

None(Robust)

Change Effect

Parameter level(Scalable)

Parameter set(Modifiable)

None(Robust)

Change Effect

Parameter level(Scalable)

Parameter set(Modifiable)

None(Robust)

Change Agent

Internal(Adaptable)

External(Flexible)

None(Rigid)

Change Agent

Internal(Adaptable)

External(Flexible)

None(Rigid)

The change agent and effect specification allows for discussion on types of change for a system, for example a flexibly scalable change in attribute X means that the change agent is outside of the system and will change the level of attribute X. There are many possible mechanisms for such a change and the system that can follow more is, in a sense, more changeable than one that can only follow a few. Systems can be quantitatively compared in terms of number of possible change mechanisms, or transition paths, to other system states. If a design is considered to be a node in a design space of options, then the transition paths are arcs that connect that design to other design options. According to network theory, such a representation can be captured in terms of the outdegree of the design, which is the number of outgoing arcs. But counting the arcs alone is not enough to account for disagreements between experts on the changeability of a particular design. In order to account for the disagreement, only transitions at acceptable cost should be counted. A quantification of changeability is the Filtered Outdegree of a design within a networked tradespace formed through explicit consideration of transition paths between design instantiations. The apparent changeability of a design will differ by decision maker based on their own thresholds for acceptable cost.

Quantified Changeability: Filtered Outdegree

# outgoing arcs from design at acceptable cost (measure of changeability)

OD( )C

<C

>C>C

OD( )C

<C

>C>C

OD( )C

<C<C

>C>C>C>C

Outdegree

100 101 102 103 104 105 106 …

Yes No

100 101 102 103 104 105 106 …

Yes NoYes No

“Cost”100 101 102 103 104 105 106 …

Yes NoYes No

100 101 102 103 104 105 106 …

Yes NoYes No

“Cost”

Acceptable Cost Threshold

Perceived changeability is limited by subjective acceptability

Quantified Changeability: Filtered Outdegree

# outgoing arcs from design at acceptable cost (measure of changeability)

# outgoing arcs from design at acceptable cost (measure of changeability)

OD( )C

<C

>C>C

OD( )C

<C

>C>C

OD( )C

<C<C

>C>C>C>C

Outdegree

100 101 102 103 104 105 106 …

Yes No

100 101 102 103 104 105 106 …

Yes NoYes No

“Cost”100 101 102 103 104 105 106 …

Yes NoYes No

100 101 102 103 104 105 106 …

Yes NoYes No

“Cost”

Acceptable Cost Threshold

Perceived changeability is limited by subjective acceptability

The achievement of value robustness can be accomplished through either passive or active means. Passive value robustness can be achieved by developing “clever” systems, with a large set of latent value attributes, increasing the likelihood of being able to match new value expectations without requiring a system change. Active value robustness can be achieved through a strategy of pursuing designs with increased changeability and accessibility to likely high value regions of a tradespace. As value perceptions and expectations change, the active value robust system can change itself in order to display the newly desired attributes. In the Ross dissertation, these concepts are developed in depth and applied to several aerospace system case studies, including the Joint Direct Attack Munition (JDAM), the Terrestrial Planet Finder (TPF) mission, and the X-Terrestrial Observer Satellite (X-TOS) mission. The framework is shown to be applicable at both quantitative and qualitative levels, giving insight into assessing and designing for changeability and value robustness for systems. It is only when designers have a good grasp of the dynamic flow of value that they can develop truly long-lasting high value systems. From the mind of the decision maker through a system in its context and back through the eyes of the decision maker, perception of value passes through many phases and transformations. The role of a good designer is not about technical achievement, but about value creation and sustainment.

Adam Ross Dr. Ross is a Postdoctoral Associate in the Engineering Systems Division at MIT. His research focuses on managing unarticulated value, designing for changeability, and dynamic tradespace exploration for complex systems. Dr. Ross received his Ph.D. degree from the MIT Engineering Systems Division in June 2006, and was previously a

research assistant with the Lean Aerospace Initiative at MIT. Dr. Ross has published papers in the area of space systems design. He has work experience with government, industry, and academia including NASA Goddard, JPL, Smithsonian Astrophysical Observatory, Boeing Satellite Systems, MIT, Harvard, and Florida State University. He holds a dual A.B. in Physics and Astronomy and Astrophysics from Harvard University and a dual S.M. in Technology and Policy and Aeronautics and Astronautics from MIT.

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Prof. Hastings Awarded Research Contract by Singapore DSTA The purpose of this three year project, initiated September 2006, is to develop an analytical framework for representing a group of homogeneous Mini Air Vehicles. The project is entitled An Engineering Systems Analysis of Systems Architecture Issues with a Swarm of Mini Air Vehicles (MAV), and involves SEAri doctoral student Tsoline Mikaelian. An objective of the research is to identify places in a system architecture where real options can mitigate performance risk. Hastings, a Professor of Engineering Systems and Aeronautics and Astronautics, previously served as Director of ESD, and now serves as the Dean for Undergraduate Education.

Systems Thinking Development Study A mini-research study is investigating the enablers, barriers, and precursors to the development of systems thinking in engineers at NASA Goddard. This research is an extension of the recent MIT ESD doctoral studies of Dr. Heidi Davidz (2006), sponsored by the Lean Aerospace Consortium. The study leverages the prior research methodology and protocols, and will be the first look at engineers in a government agency as the previous study looked only at private industry. MIT masters student Danielle Adams is spending January at Goddard, under the sponsorship of Maria So, Goddard’s Mission Engineering Branch Head. The research involves structured interviews with expert panelists, senior systems engineers, senior technical specialists, and junior systems engineers. Detailed research findings will be presented to NASA Goddard leadership, and selected highlights of the study will be released in a future publication. The research is advised by Dr. Donna H. Rhodes, in collaboration with Dr. Davidz, a Senior Member of The Aerospace Corporation Technical Staff.

Commercial Systems Engineering Pat Hale, Director of the MIT System Design and Management Program taught a special seminar during the Fall 2006 semester on the topic of commercial SE. Seven highly experienced students, from a variety of commercial companies, developed a framework for characterizing commercial products as a basis for understanding what systems engineering practices are best incorporated into the product development process. Plans are to publish the results in a future journal article.

COSYSMO Book Coming in 2007 In 2007, SEAri is anticipating the publication of the book Systems Engineering Cost Estimation with COSYSMO by Dr. Ricardo Valerdi. The book describes the anatomy and application of the Constructive Systems Engineering Cost Model (COSYSMO) together with lessons learned from implementation and calibration at companies such as BAE Systems, General Dynamics, Lockheed Martin, Northrop Grumman, L3 Communications, Raytheon, and SAIC. Prepublication copies of the book are available to selected individuals affiliated with SEAri by contacting Dr. Valerdi (rvalerdi@mit.edu). For information on COSYSMO visit www.valerdi.com/cosysmo.

MIT/MITRE Joint Research Progress The third annual MIT ESD/MITRE Research Workshop was held on November 30 at MITRE Center in Bedford, MA. The workshop featured briefings from MIT ESD students, faculty and representatives from MITRE who are working collaboratively on four joint, three-year research projects, funded by MITRE Corporation. Dr. Donna Rhodes and Dr. Brian White, Director of MITRE SE Process Office (SEPO) oversee the collaboration projects that presently include: Enterprise Dynamics & Modeling; Social Contexts of Enterprise Systems Engineering; Real Options Analysis of Public Sector Investments; and Real Options and Ilities.

SEAri Relocates to Kendall Square In August 2006, SEAri researchers and graduate students relocated to offices at Three Cambridge Center, the heart of Kendall Square above the MIT Coop Bookstore. This location is part of the Cambridge

Center complex, a 2.7 million square foot urban center with offices, research labs, retail, restaurants, hotel facilities and public parks, and offers access to the MBTA Red Line and public parking. The new space includes SEAri headquarters, offices for staff and students, and two collaborative venues. The Socio-Technical Architecting of Systems Collaborative Workspace used for several SEAri research projects, enables development of shared models and case studies. The Tradespace Visualization and Context Experimentation Laboratory supports research in computation and visualization of complex tradespaces for enhanced decision analysis, and also supports exploratory research seeking to understand how immediate context impacts requirements elicitation.

SEAri News

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Spring 2007

9-12: IEEE Systems Conference, Honolulu, HI17-19: Lean Aerospace Initiative Annual Plenary, Cambridge, MD26: SEARI/AIAA Value Driven Design Workshop, Cambridge, MA

April

14-16: Conference on SE Research, Hoboken, NJ7: COSYSMO Knowledge Exchange Event, LAI co-sponsoredMarch

February

27-30: INCOSE Int’l Workshop, Albuquerque, NMJanuary

9-12: IEEE Systems Conference, Honolulu, HI17-19: Lean Aerospace Initiative Annual Plenary, Cambridge, MD26: SEARI/AIAA Value Driven Design Workshop, Cambridge, MA

April

14-16: Conference on SE Research, Hoboken, NJ7: COSYSMO Knowledge Exchange Event, LAI co-sponsoredMarch

February

27-30: INCOSE Int’l Workshop, Albuquerque, NMJanuary

SEAri 2007 Annual Research Summit Planning is underway for the first annual research summit, bringing together SEAri researchers and consortium members, to be held in late summer 2007.

SEAri Plans for Conference on Systems Engineering Research Nine papers were submitted to the 5th Annual Conference on Systems Engineering Research (CSER), to be held at the Stevens Institute of Technology in Hoboken, NJ in March 2007. [1] Bartolomei, J.E., de Neufville, R., and Wilds, J., Real Options In a Mini-UAV System. [2] Lamb, C.T., and Rhodes, D.H., Promoting Systems Thinking Through Alignment of Culture and Process: Initial Results. [3] Lewis, S.L., Evolution of Stakeholder Composition and Value Preference within the NAVSTAR Global Positioning System. [4] Mikaelian, T. and Bartolomei, J.E., Managing Operational Uncertainty with Real Options. [5] Richards, M.G., Hastings, D.E., Rhodes, D.H., and Weigel, A.L., Defining Survivability for Engineering Systems. [6] Shah, N.B., Rhodes, D.H. and Hastings, D.E., Systems of Systems and Emergent System Context. [7] Valerdi, R. and Gaffney, J., Reducing Risk and Uncertainty in COSYSMO Size and Cost Drivers: Some Techniques for Enhancing Accuracy. [8] Fong, A., Valerdi, R., Srinivasan, J., Boundary Objects as a Framework to Understand the Role of Systems Integrators. [9] Valerdi, R. and Davidz, H., Empirical Research in Systems Engineering: Challenges and Opportunities of a New Frontier.

Systems Engineering Doctoral Student Workshop in June 2007 SEAri researchers participated in the April 2006 INCOSE Systems Engineering and Architecting Doctoral Student Network (SEANET) Workshop held at USC, where 30 systems engineering doctoral students representing six countries and fourteen universities, came together to discuss systems engineering research challenges and opportunities. A number of the students also presented highlights of their doctoral research at a poster session at the opening reception of the Conference on Systems Engineering Research (CSER) held the following day. SEAri continues to play a leadership role in the evolution of SEANET and is currently planning for a 2007 workshop to be held in conjunction with the INCOSE International Symposium 25-29 June in San Diego, CA.

Voice of the Expert -- What Do You Think? SEAri is continuously shaping our research agenda and seeks input from experts form the systems community. The following are examples of some potential research questions that SEAri researchers have proposed.

What do you think?

1. What development strategies have other professions used to evolve their theory and field? What can SE learn from this?

2. What are the relevant “ilities” to apply to Systems of Systems?

3. How can architecting be transformed from an “art” to a “science”?

4. Are there leading indicators for system flexibility, architectural integrity, etc.?

5. How do you determine the appropriate level of SE (incl. up front analyses) given a particular system and its development context?

6. How do senior leaders actually make decisions regarding systems? (incl. needed information, process, timing, effort, etc.)

7. What are the impacts on systems caused by using architectural frameworks?

8. How do human biases and heuristics affect cost estimation?

We encourage your feedback on these or other research questions of interest that fall within the research scope of SEAri. (Please email seari@mit.edu with your thoughts.)

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