ArticlePDF Available

Technology Readiness Level – A White Paper

Authors:
  • Artemis Innovation Management Solutions LLC
028
TECHNOLOGY READINESS LEVELS
A White Paper
April 6, 1995
Edited: 22 December 2004
John C. Mankins
Advanced Concepts Office
Office of Space Access and Technology
NASA
Introduction
Technology Readiness Levels (TRLs) are a systematic metric/measurement system that
supports assessments of the maturity of a particular technology and the consistent
comparison of maturity between different types of technology. The TRL approach has
been used on-and-off in NASA space technology planning for many years and was
recently incorporated in the NASA Management Instruction (NMI 7100) addressing
integrated technology planning at NASA. Figure 1 (attached) provides a summary view
of the technology maturation process model for NASA space activities for which the
TRLs were originally conceived; other process models may be used. However, to be
most useful the general model must include: (a) basic research in new technologies
and concepts (targeting identified goals, but not necessary specific systems), (b)
focused technology development addressing specific technologies for one or more
potential identified applications, (c) technology development and demonstration for each
specific application before the beginning of full system development of that application,
(d) system development (through first unit fabrication), and (e) system launch and
operations.
Technology Readiness Levels Summary
TRL 1 Basic principles observed and reported
TRL 2 Technology concept and/or application formulated
TRL 3 Analytical and experimental critical function and/or characteristic proof-
of-concept
TRL 4 Component and/or breadboard validation in laboratory environment
TRL 5 Component and/or breadboard validation in relevant environment
TRL 6 System/subsystem model or prototype demonstration in a relevant
environment (ground or space)
TRL 7 System prototype demonstration in a space environment
TRL 8 Actual system completed and “flight qualified” through test and
demonstration (ground or space)
TRL 9 Actual system “flight proven” through successful mission operations
028
Discussion of Each Level
The following paragraphs provide a descriptive discussion of each technology readiness
level, including an example of the type of activities that would characterize each TRL.
TRL 1
Basic principles observed and reported
This is the lowest “level” of technology maturation. At this level, scientific research
begins to be translated into applied research and development. Examples might include
studies of basic properties of materials (e.g., tensile strength as a function of
temperature for a new fiber).
Cost to Achieve: Very Low Unique Cost
(investment cost is borne by scientific research programs)
TRL 2
Technology concept and/or application formulated
Once basic physical principles are observed, then at the next level of maturation,
practical applications of those characteristics can be invented or identified. For
example, following the observation of high critical temperature (Htc) superconductivity,
potential applications of the new material for thin film devices (e.g., SIS mixers) and in
instrument systems (e.g., telescope sensors) can be defined. At this level, the
application is still speculative: there is not experimental proof or detailed analysis to
support the conjecture.
Cost to Achieve: Very Low Unique Cost
(investment cost is borne by scientific research programs)
TRL 3
Analytical and experimental critical function and/or
characteristic proof-of-concept
At this step in the maturation process, active research and development (R&D) is
initiated. This must include both analytical studies to set the technology into an
appropriate context and laboratory-based studies to physically validate that the
analytical predictions are correct. These studies and experiments should constitute
“proof-of-concept” validation of the applications/concepts formulated at TRL 2. For
example, a concept for High Energy Density Matter (HEDM) propulsion might depend
on slush or super-cooled hydrogen as a propellant: TRL 3 might be attained when the
concept-enabling phase/temperature/pressure for the fluid was achieved in a laboratory.
Cost to Achieve: Low Unique Cost
(technology specific)
028
TRL 4
Component and/or breadboard validation in laboratory
environment
Following successful “proof-of-concept” work, basic technological elements must be
integrated to establish that the “pieces” will work together to achieve concept-enabling
levels of performance for a component and/or breadboard. This validation must devised
to support the concept that was formulated earlier, and should also be consistent with
the requirements of potential system applications. The validation is relatively “low-
fidelity” compared to the eventual system: it could be composed of ad hoc discrete
components in a laboratory. For example, a TRL 4 demonstration of a new fuzzy logic
approach to avionics might consist of testing the algorithms in a partially computer-
based, partially bench-top component (e.g., fiber optic gyros) demonstration in a
controls lab using simulated vehicle inputs.
Cost to Achieve: Low-to-moderate Unique Cost
(investment will be technology specific, but probably
several factors greater than investment required for TRL 3)
TRL 5
Component and/or breadboard validation in relevant
environment
At this, the fidelity of the component and/or breadboard being tested has to increase
significantly. The basic technological elements must be integrated with reasonably
realistic supporting elements so that the total applications (component-level, sub-system
level, or system-level) can be tested in a simulated or somewhat realistic environment.
From one-to-several new technologies might be involved in the demonstration. For
example, a new type of solar photovoltaic material promising higher efficiencies would
at this level be used in an actual fabricated solar array blanket that would be integrated
with power supplies, supporting structure, etc., and tested in a thermal vacuum chamber
with solar simulation capability.
Cost to Achieve: Moderate Unique Cost
(investment cost will be technology dependent, but likely to be several factors
greater that cost to achieve TRL 4)
TRL 6
System/subsystem model or prototype demonstration
in a relevant environment (ground or space)
A major step in the level of fidelity of the technology demonstration follows the
completion of TRL 5. At TRL 6, a representative model or prototype system or system
which would go well beyond ad hoc, patch-cord or discrete component level
breadboarding would be tested in a relevant environment. At this level, if the only
028
relevant environment is the environment of space, then the model/prototype must be
demonstrated in space. Of course, the demonstration should be successful to represent
a true TRL 6. Not all technologies will undergo a TRL 6 demonstration: at this point the
maturation step is driven more by assuring management confidence than by R&D
requirements. The demonstration might represent an actual system application, or it
might only be similar to the planned application, but using the same technologies. At
this level, several-to-many new technologies might be integrated into the demonstration.
For example, a innovative approach to high temperature/low mass radiators, involving
liquid droplets and composite materials, would be demonstrated to TRL 6 by actually
flying a working, sub-scale (but scaleable) model of the system on a Space Shuttle or
International Space Station pallet. In this example, the reason space is the relevant
environment is that microgravity plus vacuum plus thermal environment effects will
dictate the success/failure of the system — and the only way to validate the technology
is in space.
Cost to Achieve: Technology and demonstration specific; a fraction
of TRL 7 if on ground; nearly the same if space is required
TRL 7
System prototype demonstration in a space environment
TRL 7 is a significant step beyond TRL 6, requiring an actual system prototype
demonstration in a space environment. It has not always been implemented in the past.
In this case, the prototype should be near or at the scale of the planned operational
system and the demonstration must take place in space. The driving purposes for
achieving this level of maturity are to assure system engineering and development
management confidence (more than for purposes of technology R&D). Therefore, the
demonstration must be of a prototype of that application. Not all technologies in all
systems will go to this level. TRL 7 would normally only be performed in cases where
the technology and/or subsystem application is mission critical and relatively high risk.
Example: the Mars Pathfinder Rover is a TRL 7 technology demonstration for future
Mars micro-rovers based on that system design. Example: X-vehicles are TRL 7, as
are the demonstration projects planned in the New Millennium spacecraft program.
Cost to Achieve: Technology and demonstration specific,
but a significant fraction of the cost of TRL 8
(investment = “Phase C/D to TFU” for demonstration system)
TRL 8
Actual system completed and “flight qualified” through test and
demonstration (ground or space)
By definition, all technologies being applied in actual systems go through TRL 8. In
almost all cases, this level is the end of true system development for most technology
elements. Example: this would include DDT&E through Theoretical First Unit (TFU) for
a new reusable launch vehicle. This might include integration of new technology into an
existing system. Example: loading and testing successfully a new control algorithm into
028
the onboard computer on Hubble Space Telescope while in orbit.
Cost to Achieve: Mission specific; typically highest unique cost for a new technology
(investment = “Phase C/D to TFU” for actual system)
TRL 9
Actual system “flight proven” through successful
mission operations
By definition, all technologies being applied in actual systems go through TRL 9. In
almost all cases, the end of last bug fixing aspects of true system development. For
example, small fixes/changes to address problems found following launch (through 30
days or some related date). This might include integration of new technology into an
existing system (such operating a new artificial intelligence tool into operational mission
control at JSC). This TRL does not include planned product improvement of ongoing or
reusable systems. For example, a new engine for an existing RLV would not start at
TRL 9: such technology upgrades would start over at the appropriate level in the TRL
system.
Cost to Achieve: Mission Specific; less than cost of TRL 8
(e.g., cost of launch plus 30 days of mission operations)
... NASA proposed the technology readiness levels (TRLs) decades ago to guide managers in assessing the aeronautical technology's readiness and risks at specific development key points [33,34]. The concept has spread over many innovation fields and is currently used in pharmacology by development-fostering agencies [35][36][37][38][39]. TRLs fit very well in the proposal of a roadmap providing hierarchized development concepts and enabling a step-by-step approach. ...
... Following the original Mankins style [33,48,49], we discuss each technology readiness level (TRL) main attribute, citing examples and providing brief descriptions of associated costs and funding sources. Table 1 outlines the primary deliverables for each level defined by Mankins, alongside our proposed adaptations for herbal medicinal products (HMPs). ...
... TRLs for Herbal Medicinal Products 2.1.1. TRL-1 TRL-1 was described as "basic science envisioning an application" [33,[49][50][51]. For chemicals, it was summarized as a "concept" [40]. ...
Article
Full-text available
Despite the vast global botanical diversity, the pharmaceutical development of herbal medicinal products (HMPs) remains underexploited. Of over 370,000 described plant species, only a few hundred are utilized in HMPs. Most of these have originated from traditional use, and only a minority come from megadiverse countries. Exploiting the pharmacological synergies of the hundreds of compounds found in poorly studied plant species may unlock new therapeutic possibilities, enhance megadiverse countries’ scientific and socio-economic development, and help conserve biodiversity. However, extensive constraints in the development process of HMPs pose significant barriers to transforming this unsatisfactory socio-economic landscape. This paper proposes a roadmap to overcome these challenges, based on the technology readiness levels (TRLs) introduced by NASA to assess the maturity of technologies. It aims to assist research entities, manufacturers, and funding agencies from megadiverse countries in the discovery, development, and global market authorization of innovative HMPs that comply with regulatory standards from ANVISA, EMA, and FDA, as well as WHO and ICH guidelines.
... In 2018, the LIFT team sought to identify suitable instruments for assessing the technological maturity of existing products on the market. In the investigation of such instruments, article "Technology readiness level (TRL)" written by John Mankins was identifi ed, in which the concept of technological maturity was presented (Mankins, 1995 The choice, in 2018, proved to be correct. Today, the TRL is the standard instrument used to assess technological maturity in diff erent industries. ...
... At this level, the principles and patterns are observed and their opportunities and possibilities are described and reported. It is addressed by the LIFT ecosystem in the LEARNING initiatives (Mankins, 1995). ...
... These concepts are investigated so that their elements can be properly understood, and their application possibilities can be described. It is addressed by the LIFT ecosystem in the LEARNING and LAB initiatives (Mankins, 1995). ...
Article
Full-text available
LIFT is an ecosystem that aims to develop innovation within the Brazilian fi nancial industry. In the form of a descriptive report, this paper presents the LIFT experience, its history and structure. Based on the technological readiness levels (TRL), LIFT resulted in a signifi cant increase in competitiveness in the National Financial System and the off ering of new products and services by means of sixty (60) Fintechs which arose from it. Due to its characteristics and modus operandi, it can be concluded that LIFT is a social business: its objectives are oriented towards serving a community; the ecosystem has independent management and a democratic decision-making process, focusing on the engagement of people and eff ectiveness in the contribution of work and the lack of income distribution. Its educational character results from the practical application of technologies in sharing knowledge between participants, causing a learning model very similar to that described by Vygotsky (2007) as “Zone of Proximal Development”.
... This aim of this paper is to develop a risk assessment framework that addresses both the complexities of the risk landscape that green transition portfolios face but is recognizable and easily understandable by a wide range of stakeholders. For this purpose, we build upon the widely adopted framework of NASA Technology Readiness Levels (TRLs) (Mankins, 1995(Mankins, , 2009, which among other organizations has been adopted by the EU other funding bodies supporting ambitious green transition portfolios (Innovationsfonden, 2019;De Rose et al., 2017). The core hypothesis is to explore the applicability of using a "simple" understandable framework as a foundation to communicate the specific complex risk profile of engineering portfolios. ...
... Olechowski et al. (2020) addresses as challenges in TRL and system development gates is the lack of guidance to establish alignment between an organization's major development milestones and the TRLs (Olechowski et al., 2020). To address this gap, this paper proposes an approach to support the governance of green transition project portfolios, building on the Technology Readiness Levels (Mankins, 1995) as a framework for risk assessment. Such framework must be balanced between multiple factors to grasp the complexity of the green transition. ...
Article
Full-text available
This paper aims to develop a risk assessment framework that addresses both the complexities of the risk landscape that green transition portfolios face, but is recognizable and easily understandable by stakeholders. For this purpose, we build upon the framework of NASA Technology Readiness Levels (TRLs). This study analyzes six existing readiness levels framework that are held towards uncertainty factors from the Green Transition. The TRL scale are coupled with Risk, Uncertainty, and Ignorance to score the individual level of uncertainty. The paper ends with suggestion for further studies.
... While the results of this investigation towards an autonomous MT navigation system fall under a technology readiness level (TRL) of 3 [35], this proof-of-concept work showed that IRL can be leveraged effectively as part of reward shaping to deduce a suitable reward function for RL training, there are limitations to the methodology employed in terms of utility. In vitro (e.g., phantom) and clinical validation steps would be required to progress the TRLs. ...
Preprint
Full-text available
Purpose: Autonomous navigation of catheters and guidewires can enhance endovascular surgery safety and efficacy, reducing procedure times and operator radiation exposure. Integrating tele-operated robotics could widen access to time-sensitive emergency procedures like mechanical thrombectomy (MT). Reinforcement learning (RL) shows potential in endovascular navigation, yet its application encounters challenges without a reward signal. This study explores the viability of autonomous navigation in MT vasculature using inverse RL (IRL) to leverage expert demonstrations. Methods: This study established a simulation-based training and evaluation environment for MT navigation. We used IRL to infer reward functions from expert behaviour when navigating a guidewire and catheter. We utilized soft actor-critic to train models with various reward functions and compared their performance in silico. Results: We demonstrated feasibility of navigation using IRL. When evaluating single versus dual device (i.e. guidewire versus catheter and guidewire) tracking, both methods achieved high success rates of 95% and 96%, respectively. Dual-tracking, however, utilized both devices mimicking an expert. A success rate of 100% and procedure time of 22.6 s were obtained when training with a reward function obtained through reward shaping. This outperformed a dense reward function (96%, 24.9 s) and an IRL-derived reward function (48%, 59.2 s). Conclusions: We have contributed to the advancement of autonomous endovascular intervention navigation, particularly MT, by employing IRL. The results underscore the potential of using reward shaping to train models, offering a promising avenue for enhancing the accessibility and precision of MT. We envisage that future research can extend our methodology to diverse anatomical structures to enhance generalizability.
... While the results of this investigation towards an autonomous MT navigation system fall under a technology readiness level (TRL) of 3 [35], this proof-of-concept work showed that IRL can be leveraged effectively as part of reward shaping to deduce a suitable reward function for RL training; there are limitations to the methodology employed in terms of utility. In vitro (e.g. ...
Article
Full-text available
Autonomous navigation of catheters and guidewires can enhance endovascular surgery safety and efficacy, reducing procedure times and operator radiation exposure. Integrating tele-operated robotics could widen access to time-sensitive emergency procedures like mechanical thrombectomy (MT). Reinforcement learning (RL) shows potential in endovascular navigation, yet its application encounters challenges without a reward signal. This study explores the viability of autonomous guidewire navigation in MT vasculature using inverse reinforcement learning (IRL) to leverage expert demonstrations. Employing the Simulation Open Framework Architecture (SOFA), this study established a simulation-based training and evaluation environment for MT navigation. We used IRL to infer reward functions from expert behaviour when navigating a guidewire and catheter. We utilized the soft actor-critic algorithm to train models with various reward functions and compared their performance in silico. We demonstrated feasibility of navigation using IRL. When evaluating single- versus dual-device (i.e. guidewire versus catheter and guidewire) tracking, both methods achieved high success rates of 95% and 96%, respectively. Dual tracking, however, utilized both devices mimicking an expert. A success rate of 100% and procedure time of 22.6 s were obtained when training with a reward function obtained through ‘reward shaping’. This outperformed a dense reward function (96%, 24.9 s) and an IRL-derived reward function (48%, 59.2 s). We have contributed to the advancement of autonomous endovascular intervention navigation, particularly MT, by effectively employing IRL based on demonstrator expertise. The results underscore the potential of using reward shaping to efficiently train models, offering a promising avenue for enhancing the accessibility and precision of MT procedures. We envisage that future research can extend our methodology to diverse anatomical structures to enhance generalizability.
... TRL is a measurement system that verifies the level of maturity of a given technology on a scale from one to nine, where one is a basic scientific principle, and nine is an actual system that was proven in an operational environment. The TRL system makes it consistent and systematic to compare the maturity of different types of technology [33]. ...
ResearchGate has not been able to resolve any references for this publication.