Open AccessCase studies in estimating subsea systems' readiness level
Author(s) -
Sirous Yasseri,
H. Bahai
Publication year - 2020
Publication title -
underwater technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.229
H-Index - 19
eISSN - 1756-0551
pISSN - 1756-0543
DOI - 10.3723/ut.37.013
Subject(s) - technology readiness level , metric (unit) , subsea , systems engineering , parametric statistics , scale (ratio) , metric system , engineering , estimation , component (thermodynamics) , computer science , industrial engineering , operations research , operations management , mathematics , marine engineering , statistics , geography , physics , astronomy , thermodynamics , cartography
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.