A probabilistic approach to system maturity assessment

Weiping Tan, Jose Ramirez-Marquez, Brian Sauser

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Prescriptive metrics have been widely accepted and used in engineering management to assess the progress and success of engineering efforts. However, these types of metrics have two major challenges: human subjectivity and confidence in data estimates. In this paper we use a system-focused prescriptive metric entitled System Readiness Level (SRL) [a function of Technology and Integration Readiness Levels (TRL/IRL)], to propose a probabilistic approach to estimating the development maturity of a system of interest. In order to reduce the subjective impact, we propose a probabilistic method by assigning probability distributions to the estimated TRLs and IRLs to reflect the reality of evaluators' subjective estimates. Based on these probability distributions of TRLs and IRLs, a Monte-Carlo simulation methodology is used to assess the maturity status of the whole system and its components. An illustrative example is examined to show the proposed methodology and to investigate its implication to engineering management. The paper concludes with a discussion of the added value of this new methodology, its limitation, and future work.

Original languageEnglish
Pages (from-to)279-293
Number of pages15
JournalSystems Engineering
Volume14
Issue number3
DOIs
StatePublished - Sep 2011

Keywords

  • Integration Readiness Level
  • System Readiness Level
  • Technology Readiness Level
  • prescriptive metric
  • subjectivity

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