Showing papers on "Technical performance measure published in 2012"

A framework for performance prediction during development of systems of systems

Abstract: This paper addresses the need for predicting performance in a system of systems (SoS) during development. Historically, technical performance measures (TPMs) along with modelling and simulation have been used by senior decision makers to predict if a system under development will meet the required performance needs. This methodology does not appear to be directly translatable to SoS’s for several reasons including the inherent complexity of the SoS and the operational flexibility the end user has in employing the SoS. An approach to dealing with the SoS performance prediction need is presented that addresses the use and integration of multiple technologies into a SoS and the decision maker’s options in the use of these technologies. This approach is used to develop a metric defined as a ‘SoS performance measure (SPM)’, an equivalent to a TPM for a SoS. An anti-submarine warfare mission construct is used to demonstrate this new metric.

Securability for system of systems

Abstract: As the Department of Defense (DoD) pursues methods within the systems engineering process to combat potential information assurance (IA) vulnerabilities, a new paradigm is required. This paper introduces the concept of securability as a new ility to be considered within the systems life cycle. Alongside the traditional system ilities (i.e., reliability, maintainability, supportability, etc.), securability will establish a standardised, measurable and rigorous approach to ensuring a system meets its mission objectives in a secure manner. DoD systems security capability analysis continues to mature today with the improvement of information assurance controls (DoD 8500 and NIST 800-53), but it is still conducted in a non-standard ad hoc fashion in various phases of the systems life cycle. This paper provides a foundation for the concept of securability which will focus on the technical performance measures of a systems’ security from the beginning stages (e.g., concept development) to the end point (e.g., retirement and disposal). The time has come to establish securability as an integral part of the design and operational criteria for systems and the larger more vexing systems of systems through a formal and rigorous engineering approach instead of the current external and ad hoc approach.

Development and Extension of a Deterministic System of Systems Performance Prediction Methodology for an Acknowledged System of Systems

Abstract: : This paper addresses the need for predicting performance in a system of systems (SoS) during incremental development and for dealing with the inherent variability associated with predicting performance. Historically, senior decision-makers have used technical performance measures (TPM), along with modeling and simulation, to predict whether a system under development will meet performance requirements. This methodology does not appear to be directly translatable to SoS for several reasons, including the inherent complexity of the SoS and the operational flexibility the end user may have in employing the SoS. An approach for dealing with the SoS performance prediction has been presented previously. It laid out a notional approach to dealing with this issue. This approach has been generalized to address the use and integration of multiple technologies into an SoS and into the decision-maker's options in the use of these technologies that is rooted in using subject matter expert input and historical data. This methodology is used to develop a metric defined as an SoS performance measure (SPM), which serves as an equivalent in functionality to a TPM for a SoS. Similar to TPMs, an approach to developing tolerance bands is presented to be used for predicting the status of development as a function of time. The methodology is first presented as a deterministic method for predicting SoS performance during development. This method is then demonstrated using an example case to illustrate the methodology. However, many of the component variables have significant uncertainty associated with them during SoS development and integration into the SoS. The paper provides an approach for expanding the SPM concept to account for this uncertainty using a stochastic approach to address this issue.

A Performance‐based Statistical Expert Judgment Model to Assess Technical Performance and Risk

Abstract: The rapidly changing environment and asymmetric threats currently encountered on the modern battlefield requires the timely delivery of effective weapons systems. Unfortunately in fiscal year 2008, according to the US Government Accountability Office, research and development costs of the United States Department of Defense major weapons acquisition programs increased 42 percent above original estimates, and delays in initial operational capability deliveries slipped to 22 months. While there are several quantitative methods to estimate acquisition program cost and schedule performance and to identify their risks (e.g., Earned Value Management), the estimation of technical performance and technical risk identification is generally heuristic in nature and based on expert judgment because of limited quantitative data for constructive modeling. The proposed research in this paper expands upon the Technical Risk Index Distribution method developed by Lewis, Mazzuchi and Sarkani by incorporating a performance-based method of mathematically combining quantified expert opinion for technical performance estimation and risk analysis.