2348264
Project Grant
Overview
Grant Description
Sttr phase I: A digital engineering tool for integrated software and hardware reliability.
The broader/commercial impact of this small business technology transfer (STTR) phase I project aims to streamline system reliability analysis, catering to industries such as healthcare, telecommunications, and transportation, where system failures can be life-threatening.
With a projected $20.8 billion software quality assurance market by 2030, the project's impact can be substantial.
The proposed solution employs automation and advanced data analytics to revolutionize system reliability.
It introduces data-driven reliability analysis, offering automated, collaborative, cloud-based, and visually intuitive tools to enhance system dependability.
Positioned at the convergence of software-as-a-service, software quality assurance, and data analytics markets, the solution holds significant commercial potential.
Given the critical role of system reliability across industries, the successful implementation of this project will be a key enabler for Industry 4.0.
This small business technology transfer (STTR) phase I project focuses on the domain of system quality assurance.
In this domain, the state-of-the-art approach focuses on either hardware reliability or software reliability before deployment.
However, in practice, the most critical part of the system lifecycle is during software operation, and failure depends on both software and hardware.
Therefore, the project introduces a pioneering system-level reliability model to merge software and hardware reliability.
It also aims to create advanced analytics algorithms for estimating failure intensity and pinpointing critical system flaws.
Additionally, the project plans to design, implement, evaluate, and deploy quantitative models for system reliability within a cloud-based software-as-a-service platform.
This platform will facilitate collaborative analysis, offering descriptive, predictive, and prescriptive analytics on integrated software and hardware reliability.
Through interactive reliability block diagrams, the platform democratizes system reliability assessment, lessening reliance on manual expertise for the first time.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
The broader/commercial impact of this small business technology transfer (STTR) phase I project aims to streamline system reliability analysis, catering to industries such as healthcare, telecommunications, and transportation, where system failures can be life-threatening.
With a projected $20.8 billion software quality assurance market by 2030, the project's impact can be substantial.
The proposed solution employs automation and advanced data analytics to revolutionize system reliability.
It introduces data-driven reliability analysis, offering automated, collaborative, cloud-based, and visually intuitive tools to enhance system dependability.
Positioned at the convergence of software-as-a-service, software quality assurance, and data analytics markets, the solution holds significant commercial potential.
Given the critical role of system reliability across industries, the successful implementation of this project will be a key enabler for Industry 4.0.
This small business technology transfer (STTR) phase I project focuses on the domain of system quality assurance.
In this domain, the state-of-the-art approach focuses on either hardware reliability or software reliability before deployment.
However, in practice, the most critical part of the system lifecycle is during software operation, and failure depends on both software and hardware.
Therefore, the project introduces a pioneering system-level reliability model to merge software and hardware reliability.
It also aims to create advanced analytics algorithms for estimating failure intensity and pinpointing critical system flaws.
Additionally, the project plans to design, implement, evaluate, and deploy quantitative models for system reliability within a cloud-based software-as-a-service platform.
This platform will facilitate collaborative analysis, offering descriptive, predictive, and prescriptive analytics on integrated software and hardware reliability.
Through interactive reliability block diagrams, the platform democratizes system reliability assessment, lessening reliance on manual expertise for the first time.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Naperville,
Illinois
60563-2221
United States
Geographic Scope
Single Zip Code
Sakura Software Solutions was awarded
Project Grant 2348264
worth $274,880
from National Science Foundation in October 2024 with work to be completed primarily in Naperville Illinois United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
STTR Phase I
Title
STTR Phase I: A digital engineering tool for integrated software and hardware reliability
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project aims to streamline system reliability analysis, catering to industries such as healthcare, telecommunications, and transportation, where system failures can be life-threatening. With a projected $20.8 billion software quality assurance market by 2030, the project's impact can be substantial. The proposed solution employs automation and advanced data analytics to revolutionize system reliability. It introduces data-driven reliability analysis, offering automated, collaborative, cloud-based, and visually intuitive tools to enhance system dependability. Positioned at the convergence of Software-as-a-Service, software quality assurance, and data analytics markets, the solution holds significant commercial potential. Given the critical role of system reliability across industries, the successful implementation of this project will be a key enabler for Industry 4.0.
This Small Business Technology Transfer (STTR) Phase I project focuses on the domain of system quality assurance. In this domain, the state-of-the-art approach focuses on either hardware reliability or software reliability before deployment. However, in practice, the most critical part of the system lifecycle is during software operation, and failure depends on both software and hardware. Therefore, the project introduces a pioneering system-level reliability model to merge software and hardware reliability. It also aims to create advanced analytics algorithms for estimating failure intensity and pinpointing critical system flaws. Additionally, the project plans to design, implement, evaluate, and deploy quantitative models for system reliability within a cloud-based software-as-a-service platform. This platform will facilitate collaborative analysis, offering descriptive, predictive, and prescriptive analytics on integrated software and hardware reliability. Through interactive reliability block diagrams, the platform democratizes system reliability assessment, lessening reliance on manual expertise for the first time.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
AA
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 9/25/24
Period of Performance
10/1/24
Start Date
9/30/25
End Date
Funding Split
$274.9K
Federal Obligation
$0.0
Non-Federal Obligation
$274.9K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2348264
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Other
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
W647R1NM9DH8
Awardee CAGE
9NGX1
Performance District
IL-11
Senators
Richard Durbin
Tammy Duckworth
Tammy Duckworth
Modified: 9/25/24