System Readiness Level Research Articles

Analysis and Critique of the System Readiness Level

The system readiness level (SRL) developed by Sauser (referred to as the SC but they have limited usefulness. The effective and efficient development of technically advanced systems and upgrades of heritage systems requires a systems engineering (SE) process based on a sound quantitative assessment and management of technical, cost, and schedule risks. The use of the S&C_SRL and other flawed decision and risk analysis models is symptomatic of a mathematical vulnerability in the SE practice. Corrective actions are presented.

Subsea system readiness level assessment

Both the American Petroleum Institute (API) 17N: 2009 and Det Norske Veritas (DNV) RP-A203 (2011) recommend that the technologies inserted into subsea installations should be assessed during design and manufacturing using a technology readiness level (TRL) scale. This should be used as a measure of maturity of all the individual technologies, for qualification and readiness assurance. This paper proposes the creation of a system-based approach for managing the development of subsea systems and making effective decisions to ensure the efficient progress of the project. It recommends complementing TRL with an integration readiness level (IRL) scale, to address IRL between the inserted technologies, along with a system readiness level (SRL) scale to assess the overall project status. It also presents a method for combining the current TRL scale and the proposed new IRL scale to determine an estimate of SRL at all stages of a subsea system development. This provides a composite metric for determining the system readiness level for project delivery. The application of the new proposed scales is demonstrated using a case example.

Mathematical properties of System Readiness Levels

AbstractSystems engineers need quantifiable metrics for measuring the readiness of a system. The recently developed System Readiness Level (SRL) is such a metric. SRL is a function of Technology Readiness Level (TRL) and Integration Readiness Level (IRL). The mathematical operations used to define this function have some inherent properties. Four desired mathematical properties of SRL models are developed from these inherent properties and other properties suggested from a review of the literature. Matrix algebra and tropical algebra are discussed in the literature as possible mathematical operations. These mathematical operations are reviewed to determine if they meet the desired properties. Tropical Algebra (TA) is found to inherently meet these desired properties. Future research will be conducted to determine if an SRL model using TA is a viable option. ©2012 Wiley Periodicals, Inc. Syst Eng 16:

Integration-centric approach to system readiness assessment based on evidential reasoning

An integration-centric approach is proposed to handle inadequate information in the system readiness level (SRL) assessment using the evidential reasoning (ER) algorithm. Current SRL assessment approaches cannot be applied to handle inadequate information as the input. The ER-based approach is proposed to synthesize inadequate input information and an integration-centric perspective is applied to reduce the computational complexity. Two case studies are performed to validate the efficiency of the proposed approach. And these studies are also performed to study how the inadequate information will affect the assessment result. And the differences caused by the system's structure. The importance of the system's structure in the SRL assessment is demonstrated and the contributions made in this study are summarized as conclusions.

Analyzing Component Importance in Multifunction Multicapability Systems Developmental Maturity Assessment

Recently, a system maturity scale, i.e., system readiness level (SRL), was proposed to measure the maturity that a system achieves during development. However, this SRL assesses maturity for systems from only a single function and capability perspective, and is unable to assess maturity for multifunction multicapability (MFMC) systems. With ever increasing systems that provide multiple functions and capabilities, it is challenging for managers to properly allocate resources to ensure the achievement of critical capabilities and functions. In order to prioritize the allocation of resources for component development, it is common to perform importance analysis during system development and maintenance. Therefore, this paper first enhances the original SRL definition for maturity assessment at the capability, function, and system levels, and then, proposes the use of component importance analysis for the identification of the most important components for system development. This paper approaches component importance by introducing three important measures with respects to three main factors: technology readiness level/integration readiness level, developing cost, and developing effort. The paper uses an illustrative example of a MFMC system to show the proposed methodology and enhanced definitions and concludes with a discussion of the added value and future work.

A probabilistic approach to system maturity assessment

AbstractPrescriptive 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. © 2010 Wiley Periodicals, Inc. Syst Eng 14

System development planning using readiness levels in a cost of development minimization model

AbstractThe purpose of this paper is to describe a methodology that enables systems engineers or program managers to formulate a system‐wide optimal development plan in order to facilitate monitoring and evaluation of the development process in terms of the actual readiness of the system. It proposes the use of the System Readiness Level (SRL) scale to measure the maturity of a system composed of technological elements, which are being developed based on cost‐driven strategies (as opposed to time‐to‐market‐driven strategies). A constrained optimization model is used to identify which critical technology elements and integration links can be matured to which levels at a particular time such that the development costs are minimized while a targeted SRL value is attained on schedule. While the algorithm does not necessarily reduce the total cost of development, it is able to find the minimal amount of expenditures which will achieve the desired maturity level during the earlier part of the development process. Essentially, it shifts the rest of the expenditures towards the latter part of the development during which model‐based integration and testing procedures which have been suggested by others can be applied to reduce costs and time further. This can be a useful option to have when there is substantial uncertainty with the system due to its high novelty and technological content. As a value added approach, the model gives the systems engineer the information needed to understand what a delay may mean to development, so a more informed decision can be made. The paper concludes by discussing the possible use of the optimal development plan to monitor and control the progress of systems under development. © 2009 Wiley Periodicals, Inc. Syst Eng

System Development Planning via System Maturity Optimization

Many U.S. government agencies and their contractors have subscribed to using the prescriptive metric of technology readiness level (TRL) as a measure of maturity of an individual technology, with a view toward operational use in a system context. A comprehensive set of concerns becomes relevant when this metric is abstracted from an individual technology to a system context, which may involve interplay among multiple technologies that are integrated through a system development life cycle. This paper proposes a system-focused approach for managing system development and making effective and efficient decisions during this life cycle. A system readiness level (SRL) index that incorporates both the current TRL scale and the concept of an integration readiness level is presented with methods for determining current and future readiness of a system. Using techniques in evolutionary algorithms, the SRL index is optimized based on resource allocation to provide a decision support approach that enhances managerial capabilities in the system's development life cycle. The optimization model for the SRL is then executed with a case example and resource constraints of 75%, 60%, 45%, 30%, and 15% to demonstrate how it can be used to make strategic planning decisions in the system's development life cycle.

7.3.2 Monte‐Carlo Simulation Approach for System Readiness Level Estimation

AbstractA system‐focused prescriptive metric, called System Readiness Level (SRL), which incorporates both the current Technology Readiness Level (TRL) scale and the concept of an Integration Readiness Level (IRL) has recently been established to measure current and future readiness status of a system under development. In previous research, deterministic values for components' TRLs and IRLs estimation were assumed, which involves much human subjectivity. Moreover, only point estimation from calculation was proposed in previous research. In order to reduce the subjective influence, we propose a probabilistic method here to combine all evaluators' estimation towards a system's components and integration points. Based on the probabilistic form of TRLs and IRLs, a Monte‐Carlo simulation methodology is followed herein to assess the maturity status (SRL) of a system. An illustrative example is examined to show how to employ the proposed methodology. The paper concludes with the discussion of the gained value of the new methodology as well as its limitation.

A system maturity index for the systems engineering life cycle

In the United States (USA) National Aeronautics and Space Administration (NASA) and the USA Department of Defense (DoD) the Technology Readiness Level (TRL) scale is a measure of maturity of an individual technology, with a view towards operational use in a system context. A comprehensive set of concerns becomes relevant when this metric is abstracted from an individual technology to a system context. This paper proposes the development of a system-focused approach for managing system development and making effective and efficient decisions during a systems engineering life cycle. This paper presents a System Readiness Level (SRL) index that incorporates both the current TRL scale and an Integration Readiness Level (IRL) and provides a method for determining readiness of a system in the systems engineering life cycle. This paper concludes with a general discuss of the implication of the proposed SRL and how this may be applied to four case