SBIR Phase I: Software Tools for Self-Diagnosable Intelligent Sensor Networks for Process Control

Award Information
Agency:
National Science Foundation
Branch
n/a
Amount:
$99,516.00
Award Year:
2005
Program:
SBIR
Phase:
Phase I
Contract:
0512949
Agency Tracking Number:
0512949
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
ITN Energy Systems Inc
8130 Shaffer Parkway, Littleton, CO, 80127
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Bharat Joshi
Dr
(704) 687-8407
bsjoshi@uncc.edu
Business Contact:
Janet Casteel
Ms
(303) 285-5111
jcasteel@itnes.com
Research Institution:
n/a
Abstract
This Small Business Innovation Research (SBIR) Phase I project will exploit advances in sensor technologies and recently approved IEEE 1451 family of standards to design and develop tools to create highly autonomous fault-tolerant distributed sensor networks with plug-and play capabilities. This multi-phase effort will enable diagnosis of faulty sensors and reconfiguration of the network in real time to ensure that the control of the manufacturing process can continue with accurate information in the presence of sensor faults. Currently sensor reliability issues are not considered when the systems are designed and developed although the reliability of the information collected and interpreted is highly dependent on the sensors used and sensor networks employed. Existence of appropriate technologies in the areas of sensors, computing, communication, and standards suggest that it is an opportune time to develop such networks. The innovative feature of the proposed effort will be the IEEE 1451-based architecture, algorithms for the distributed fault-tolerant sensor networks that will enable plug-and-play capability, and the development of a new member in the IEEE 1451 standards that will address reliability issues of the sensor networks. The proposed effort on enabling software tools for highly reliable sensor networks to ensure that the manufacturing processes do not continue with incorrect process settings would enable U.S. to maintain its leadership in the manufacturing sector. The reliability of sensors is a critical issue in thin-film deposition systems where they are typically exposed to harsh chemical and thermal environments, but no substantial work has been done in the area of fault-tolerant sensor networks for these systems. Although no formal study has been conducted to quantify production losses in thin-film industry the number is expected to be in the high millions. The proposed IEEE 1451-based tools for fault-tolerant networks will be highly useful in a wide range of disciplines. However, the initial target market will be the barrier and TCO coatings, such as flexible displays, followed by thin-film in general and semiconductor industry. Successful demonstration on these systems will create opportunities in other markets.

* information listed above is at the time of submission.

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