| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | July 11, 2016 |
| Latest Amendment Date: | August 5, 2020 |
| Award Number: | 1644991 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Kathryn Jablokow
kjabloko@nsf.gov (703)292-7933 CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | August 1, 2016 |
| End Date: | July 31, 2021 (Estimated) |
| Total Intended Award Amount: | $149,999.00 |
| Total Awarded Amount to Date: | $149,999.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
3720 S FLOWER ST FL 3 LOS ANGELES CA US 90033 (213)740-7762 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
3720 S. Flower St. Los Angeles CA US 90089-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | SYS-Systems Science |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
The objective of this EArly-concept Grant for Exploratory Research (EAGER) collaborative project is to create a series of educational videos on foundational areas from which systems engineering theory will be able to draw. The field of systems engineering has developed largely as a process driven discipline, with much of the process lacking rigorous foundations. Across government agencies, industry, and academia, methods that are process-driven, heuristic in nature, and even inherently flawed, are used and taught routinely, without an understanding of their limitations, thereby contributing to significant cost and time overruns, delays, and cancellations of major engineering projects. One estimate is that the loss to the Federal Government resulting from current systems engineering processes exceeds $200 million per day. This educational outreach effort is aimed at introducing rigorous foundations of systems engineering to engineering students in order to influence practice as well as training of the future systems engineering workforce, and provide rigorous foundations for decision making in systems engineering.
This project will promote the use of rigorous foundations in the development of a theory of systems engineering in ways that are accessible to a broad group of educators, researchers and practitioners. If the practice of systems engineering is to change, advances must take place to lay rigorous foundations for the methods, processes and tools for practitioners. These advances must then be taught in a way that is both rigorous and accessible to the community. Three overall areas are targeted in this EAGER: 1) Utility Theory; 2) Probability Theory; and 3) Flawed Methods. Two to three videos will be produced in each of these areas. All of these will be developed in the context of systems engineering needs and opportunities. As an introduction to these topics, one overview video will be produced to provide the context for why the videos are important to systems engineering education and practice. The adoption of rigorous mathematical theory in systems engineering will have significant ramifications for government agencies as well as the industries engaged in design and development of complex engineered systems. Promoting the implementation of well-vetted theories, methods and tools from other disciplines into the discipline of systems engineering through these videos has the potential for a significant impact. These videos will be developed so as to be useful in the classroom and for practitioners in order to increase the range of their impact.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The primary objective of this proposal was to explore topics that fill an educational gap in decision making in systems engineering curricula.
These objectives arose from various workshops on decision making in engineering design; from a literature survey; student workshops; faculty input, and practitioner input at professional conferences.
The work resulted in a survey of decision-making methods used and also identified some common misuses of sound decision making methodologies in systems engineering. This paper won first prize in Systems Engineering journal titled On the Misuse of Utility Theory in Engineering Design.
The work also resulted in a journal paper currently under review discussing a widely used (and widely misused) method of decision making known as the Weight and Rate.
The work resulted in the production of 14 videos by professors around the country
https://projects.vrac.iastate.edu/sefoundations/
1. Understanding Preferences in Engineering Design, Ali Abbas, USC
The topic of direct and indirect values, and the need for sound decision making is introduced in this video. The video also presented examples of flawed methods of decision making and the implications they may have on issues such as rank reversal.
2. Constructing Preference and Value Functions, Ali Abbas, USC
This video resulted from the need to distinguish between preference, value and utility functions. The video also explains how there are many possible forms of value functions beyond the simple additive and multiplicative forms.
3. Understanding Probability, Sheldon Mark Ross, USC
Sheldon Ross has a series of textbooks on probability with various publishers and his books are used in numerous programs in operations research. In this video, Professor Ross discusses representing uncertainty with probability.
4. Reliability Systems, Sheldon Mark Ross, USC
In this video Sheldon discusses the use of probability in determining the reliability of a system, with applications in systems engineering.
5. Poisson Paradigm, Sheldon Mark Ross, USC
In this video, Sheldon provides a simple model of capturing uncertainty using Poisson processes as a first step.
6. Decision Analysis: Milling Stability, Tony L. Schmitz, UNCC
Tony Schmitz was selected because he was worked in engineering systems and high-speed machining. With a background in Mechanical engineering, Schmitz has also published on the formulation of engineering problems using decision analysis with the PI. Schmitz was selected because he is an example of a person with mechanical engineering background who is using decision tools. In this video, Tony shows how to formulate high speed machining as a decision problem with uncertainty about stability and chatter. A value function for high-speed machining is presented that converts the outcomes into monetary equivalents.
7. Decision Analysis: Value of Information, Tony L. Schmitz, UNCC
Value of information is an important topic in decision analysis, yet it is not widely used for optimal testing in engineering design. In this video, Schmitz builds on the value function for high-speed machining and formulates the high-speed machining testing problem as a value of information problem to select the test points that maximize the valuer of information.
8. Decision Analysis of Parameter Selection: Remaining Useful Life, Tony L. Schmitz, UNCC
Selection of machining parameters such as spindle speed and axial depth of cut has implication on the cutting tool life. This video formulates the parameter selection as a decision problem using a value function that takes into account the wear of tool life as a function of the selected parameters.
9. Decisions: Engineering, Elections, Corporate Boards, and Elsewhere: So Much Can Go Wrong!, Donald Saari, UC, Irvine
There is a big difference between making a decision solo or making it in the presence of a large system with multiple decision makers. This video by Don Sari emphasizes common errors in decision making in large enterprises.
10. Systems Analysis and the Reductionist Philosophy, Donald Saari, UC, Irvine
There is a balance between increasing the number of variables leading to computational complexity, and focusing on the important aspects of a decision. Further, when a complex problem is divided into components parts, issues arise with the reduction and distribution of the decision. This video discusses the philosophy of reducing complexity within systems analysis.
11. Resolutions, Donald Saari, UC, Irvine
When a complex problem is divided into components, different silos may arise and the silos may not communicate with each other. The video emphasis the importance of information sharing and communication between silos and how (and which) the information needs to be coordinated. The video discusses a framework for information sharing using a consistency condition.
Three other videos were produced by Professor Andrea Hupman at University of Missouri , St Louis.
https://drive.google.com/drive/folders/1f4syi4lyG7TfCUEz4B3JWDcIqF63fFh_
Decision Diagrams, Calculating the Value of Information, and the misuse of utility theory in engineering design.
Last Modified: 09/29/2021
Modified by: Ali E Abbas
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