Systems and Methods for Intelligent Quality Control of Instruments and Processes
Description of Invention:
Available for licensing and commercial development is a cost-effective system and method for evaluation of instruments and processes for real-time detection of error. The subject invention includes the capacity to identify imprecision in a variety of data analysis tools, which may be susceptible to malfunction. Such processes include instrumental analysis of patient specimens, assembly line manufacturing and general plant or factory operation. This system provides an automated platform for the dual purpose of 1) monitoring data to detect unusual events in real time and 2) enhancement of human and machine recognition and analysis of improper occurrences based on time-varying patterns of measured values.
The scheme of the current system is straightforward and in general the method involves the following steps: 1) collection of data elements from an instrument or process 2) counting data elements having values within predetermined intervals of the data range 3) applying counts of data to a neural network that monitors data trends and 4) production of an output based on the neural network, which demonstrates whether the instrument or process is generating results within an appropriate range. This system is advantageous because output is generated in real time and thus available without delay for immediate correction of malfunctions.
Applications:
Quality control for processes and instruments
Automated system for real time notification of malfunctions in an instrument or process for immediate correction of the procedure
Development Status:
The technology is fully developed.
Inventors:
James M. Deleo (CIT) and Alan T. Remaley (CC)
Licensing Status: Available for non-exclusive and exclusive licensing.
Collaborative Research Opportunity:
The National Institutes of Health Clinical Center, Radiologic and Imaging Sciences, is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize Intelligent Quality Control of Instruments. Please contact Elaine Ayres at 301/594-3019 for more information.
For Additional Information Please Contact: Cristina Thalhammer-Reyero PhD MBA
NIH Office of Technology Transfer
6011 Executive Blvd, Suite 325
Rockville, MD 20852-3804
Phone: (301) 435-4507
Email: thalhamc@mail.nih.gov
Fax: (301) 402-0220
