Abstract
System readiness level (SRL) is used to measure the maturity of a system technical scenario so as to cover the shortage of Technical Readiness Level (TRL) by adopting Integration Readiness Level (IRL). When SRL is calculated based on TRL and IRL, the maturity of the Critical Technology Elements (CTEs) and their interplay would change with time going on. Thus, when SRL is calculated based on TRL/IRL, it may have time lags and the decision made according to the SRL will be also out of time. It may cost a large quantity of time and money. In order to solve the problem, markov chain is adopted. The concept of initial distribution, transition probability matrix and stationary distribution are used to describe and obtain the initial and stationary TRL/IRL/SRL. The markov chain-based System Readiness Assessment (SRA) method can reduce the time lag of the TRL/IRL/SRL. Thanks to the advantage, decision can be made more accurately and scientifically. An illustrative example is given to test and verify the method. The method is easy to operate and can be generalized to other field.
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Guo, Q., Li, G., Li, L., Song, J. (2012). Study on Markov Chain-Based System Readiness Assessment Method. In: Xiao, T., Zhang, L., Fei, M. (eds) AsiaSim 2012. AsiaSim 2012. Communications in Computer and Information Science, vol 323. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34384-1_58
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DOI: https://doi.org/10.1007/978-3-642-34384-1_58
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