Case studies in estimating subsea systems' readiness level

IF 0.4 Q4 Engineering
S. Yasseri, H. Bahai
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引用次数: 1

Abstract

Systems readiness level (SRL) is a metric defined for assessing progress in the development of systems. The methodologies to estimate SRLs are built on the technology readiness level (TRL), originally developed by NASA to assess the readiness of new technologies for insertion into a system. TRL was later adopted by governmental institutions and many industries, including the American Petroleum Institute (API). The TRL of each component is mathematically combined with another metric, integration readiness level (IRL), to estimate the overall level of readiness of a system. An averaging procedure is then used to estimate the composite level of systems readiness. The present paper builds on the previous paper by Yasseri (2013) and presents case examples to demonstrate the estimation of SRL using two approaches. The objective of the present paper is to show how the TRL, IRL, and SRL are combined mathematically. The performance of the methodology is also demonstrated in a parametric study by pushing the states of readiness to their extremes, namely very low and very high readiness. The present paper compares and contrasts the two major system readiness levels estimation methods: one proposed by Sauser et al. (2006) for defence acquisition based on NASA's TRL scale, and another based on API's TRL scale. The differences and similarities are demonstrated using a case study.
评估海底系统就绪水平的案例研究
系统准备级别(SRL)是为评估系统开发过程而定义的度量标准。估计srl的方法建立在技术准备水平(TRL)的基础上,TRL最初是由NASA开发的,用于评估新技术插入系统的准备情况。TRL后来被政府机构和许多行业采用,包括美国石油协会(API)。每个组件的TRL在数学上与另一个度量,集成准备水平(IRL)相结合,以估计系统的总体准备水平。然后使用平均程序来估计系统准备就绪的综合水平。本论文建立在Yasseri(2013)的上一篇论文的基础上,并提出了使用两种方法来演示SRL估计的案例。本文的目的是展示TRL, IRL和SRL如何在数学上组合。通过将准备状态推到极端,即非常低和非常高的准备状态,该方法的性能也在参数化研究中得到证明。本文比较和对比了两种主要的系统战备水平估计方法:一种是由Sauser等人(2006)提出的基于NASA TRL量表的国防采掘方法,另一种是基于API的TRL量表。通过一个案例研究来说明两者的异同。
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来源期刊
UNDERWATER TECHNOLOGY
UNDERWATER TECHNOLOGY ENGINEERING, OCEAN-
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