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A methodology for predicting operati...

Volkert, Richard E.

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A methodology for predicting operational performance during development of a system of systems.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A methodology for predicting operational performance during development of a system of systems./
Author:	Volkert, Richard E.
Description:	205 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
Contained By:	Dissertation Abstracts International75-04B(E).
Subject:	Engineering, System Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3606941
ISBN:	9781303642845

A methodology for predicting operational performance during development of a system of systems.
Volkert, Richard E.

A methodology for predicting operational performance during development of a system of systems. - 205 p.

Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.

Thesis (Ph.D.)--Southern Methodist University, 2013.

The use of Systems of Systems (SoS) to achieve increased capability is an increasing trend within the U.S. Department of Defense (DoD). Many of these SoS are Acknowledged SoS with a recognized manager, objectives, and resources but where the component systems remain independently funded and managed. In this new environment, metrics and methodologies for management of SoS development have not kept pace with their use. Lessons learned to date have indicated that traditional system level methods fail in effectively aiding a Program Manager in monitoring and predicting performance for an Acknowledged SoS. This has resulted in numerous research activities and proposed methodologies to address this deficiency. In this dissertation trends that are driving the DoD toward an increased use of SoS are reviewed and some of the techniques presently being developed/proposed to aid in their management during development presented. The lack of the present techniques' ability to predict if the SoS can achieve desired operational performance will be discussed and the need for this capability documented. Historically, Program Managers (PM) have used Technical Performance Measures (TPMs) at a system level to aid in predicting if a program is on a path to achieve required operational performance. When extended over a developmental timeline, TPMs have provided a deterministic approach for predicting expected operational performance. However, TPMs are difficult to derive for a complex Acknowledged SoS, and system level TPMs fail to provide the necessary insight. This dissertation presents an SoS Operational Performance Measure (SPM) as an alternative approach to providing this level of insight during SoS development. A methodology that is operative within the knowledge constraints of an Acknowledged SoS PM is presented. The methodology is designed to provide the capability for the calculation of a time variant SPM value which is equivalent in purpose and usage to TPMs. The methodology was first developed for a deterministic state similar to that seen in present TPM usage. However, reality indicates that SoS often have a great deal of variability within the component systems' actual versus predicted capability and sustainability and in the ways they may be operationally employed. Therefore, to more accurately address the ability to predict if an SoS will be able to achieve its desired operational performance, the deterministic approach was modified to incorporate variability. This extends the deterministic SPM concept into a stochastic approach to account for this uncertainty. An Antisubmarine Warfare Mission example is used to verify that the methodology provides equivalent insight to a system level TPM methodology. Finally, the results of the methodology development, verification, and validation efforts are summarized and potential areas of future research identified. The methodology developed predicts SoS operational performance in terms of "best estimate" as well as a tolerance band at any time, especially at major milestones, during U.S. DoD capability acquisition. The methodology was developed and is presented in the dissertation provides a framework for additional research and application in U.S. DoD SoS development programs and is in response to a critical need as the result of increased acquisition by the U.S. DoD of Acknowledged SoS in response to capability-based requirements.

ISBN: 9781303642845Subjects--Topical Terms:

1018128
Engineering, System Science.

A methodology for predicting operational performance during development of a system of systems.
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245 1 2 $a A methodology for predicting operational performance during development of a system of systems.
300 $a 205 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
500 $a Advisers: Jerrell Stracener; Junfang Yu.
502 $a Thesis (Ph.D.)--Southern Methodist University, 2013.
520 $a The use of Systems of Systems (SoS) to achieve increased capability is an increasing trend within the U.S. Department of Defense (DoD). Many of these SoS are Acknowledged SoS with a recognized manager, objectives, and resources but where the component systems remain independently funded and managed. In this new environment, metrics and methodologies for management of SoS development have not kept pace with their use. Lessons learned to date have indicated that traditional system level methods fail in effectively aiding a Program Manager in monitoring and predicting performance for an Acknowledged SoS. This has resulted in numerous research activities and proposed methodologies to address this deficiency. In this dissertation trends that are driving the DoD toward an increased use of SoS are reviewed and some of the techniques presently being developed/proposed to aid in their management during development presented. The lack of the present techniques' ability to predict if the SoS can achieve desired operational performance will be discussed and the need for this capability documented. Historically, Program Managers (PM) have used Technical Performance Measures (TPMs) at a system level to aid in predicting if a program is on a path to achieve required operational performance. When extended over a developmental timeline, TPMs have provided a deterministic approach for predicting expected operational performance. However, TPMs are difficult to derive for a complex Acknowledged SoS, and system level TPMs fail to provide the necessary insight. This dissertation presents an SoS Operational Performance Measure (SPM) as an alternative approach to providing this level of insight during SoS development. A methodology that is operative within the knowledge constraints of an Acknowledged SoS PM is presented. The methodology is designed to provide the capability for the calculation of a time variant SPM value which is equivalent in purpose and usage to TPMs. The methodology was first developed for a deterministic state similar to that seen in present TPM usage. However, reality indicates that SoS often have a great deal of variability within the component systems' actual versus predicted capability and sustainability and in the ways they may be operationally employed. Therefore, to more accurately address the ability to predict if an SoS will be able to achieve its desired operational performance, the deterministic approach was modified to incorporate variability. This extends the deterministic SPM concept into a stochastic approach to account for this uncertainty. An Antisubmarine Warfare Mission example is used to verify that the methodology provides equivalent insight to a system level TPM methodology. Finally, the results of the methodology development, verification, and validation efforts are summarized and potential areas of future research identified. The methodology developed predicts SoS operational performance in terms of "best estimate" as well as a tolerance band at any time, especially at major milestones, during U.S. DoD capability acquisition. The methodology was developed and is presented in the dissertation provides a framework for additional research and application in U.S. DoD SoS development programs and is in response to a critical need as the result of increased acquisition by the U.S. DoD of Acknowledged SoS in response to capability-based requirements.
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710 2 $a Southern Methodist University. $b Engineering Management, Information and Systems. $3 1023597
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