Learn as much as possible from the past is the main purpose of modern knowledge-management approaches which allows continuous improvement of new products design and verification applied methods. In the space domain, data acquired from successful and unsuccessful missions should be aggregated to highlight effective and poor practices, basing on the comparison between actual results of several projects. The first step to reach this objective is to collect relevant data and gather them in a structured information system, as the ESA Model and Test Effectiveness Database (MAT€D) experience learns. The second step is to analyze and compare the historical information to understand better trends and effectiveness of design and verification philosophies, but space systems may be extremely different one from another, and the comparison requires a normalization method able to compare "apples and oranges", assigning to each system its complexity level, according to the objective of the single analysis that can be devoted to risk, cost and schedule evaluations. Rough methods have been used since now, using the spacecraft mass or the number of electronic parts as normalization factors, but they are not able to describe with good approximation the real complexity of the system and specialize it for the specific purpose. This problem has been driving the joint Thales Alenia Space Italia- Politecnico di Torino Research Group for the last years. The objective is the transition in the ESA Model and Test Effectiveness Database (MAT€D) analysis from the number of Electronic Parts (EP) to complexity indexes, as variable to normalize the data from different spacecraft programs, including technical, industrial and operational dimensions of the complexity. The objective of this paper is to present the latest definition of the methodology for the calculation of complexity indexes for space, based on the functional analysis of a generic space project, validated preliminarily with scientific satellites and pressurized modules data, but conceived to be used also for exploration systems. The methodology is then applied to eleven heterogeneous spacecrafts whose data are contained in MAT€D (including earth observation satellites, planetary probes and manned pressurized modules) for the comparison of ground (AIT) and flight anomalies and of cost evaluation. Copyright ©2010 by Thales Alenia Space Italia S.p.A.

Comparison of heterogeneous space projects through complexity indexes, for technical and managerial evaluations / Pasquinelli, M.; Messidoro, P.; Basso, V.; Voglino, S.; Maggiore, P.. - 11:(2010), pp. 8915-8923. ((Intervento presentato al convegno 61st International Astronautical Congress 2010, IAC 2010 tenutosi a Prague, cze nel 2010.

Comparison of heterogeneous space projects through complexity indexes, for technical and managerial evaluations

Pasquinelli M.;Maggiore P.
2010

Abstract

Learn as much as possible from the past is the main purpose of modern knowledge-management approaches which allows continuous improvement of new products design and verification applied methods. In the space domain, data acquired from successful and unsuccessful missions should be aggregated to highlight effective and poor practices, basing on the comparison between actual results of several projects. The first step to reach this objective is to collect relevant data and gather them in a structured information system, as the ESA Model and Test Effectiveness Database (MAT€D) experience learns. The second step is to analyze and compare the historical information to understand better trends and effectiveness of design and verification philosophies, but space systems may be extremely different one from another, and the comparison requires a normalization method able to compare "apples and oranges", assigning to each system its complexity level, according to the objective of the single analysis that can be devoted to risk, cost and schedule evaluations. Rough methods have been used since now, using the spacecraft mass or the number of electronic parts as normalization factors, but they are not able to describe with good approximation the real complexity of the system and specialize it for the specific purpose. This problem has been driving the joint Thales Alenia Space Italia- Politecnico di Torino Research Group for the last years. The objective is the transition in the ESA Model and Test Effectiveness Database (MAT€D) analysis from the number of Electronic Parts (EP) to complexity indexes, as variable to normalize the data from different spacecraft programs, including technical, industrial and operational dimensions of the complexity. The objective of this paper is to present the latest definition of the methodology for the calculation of complexity indexes for space, based on the functional analysis of a generic space project, validated preliminarily with scientific satellites and pressurized modules data, but conceived to be used also for exploration systems. The methodology is then applied to eleven heterogeneous spacecrafts whose data are contained in MAT€D (including earth observation satellites, planetary probes and manned pressurized modules) for the comparison of ground (AIT) and flight anomalies and of cost evaluation. Copyright ©2010 by Thales Alenia Space Italia S.p.A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2886798