Hardware Self-Diagnoses Using On-Component Links to Experts   Systems
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
{'SignBlockName': 'Ritchie B. Coryell', 'PO_EMAI': None, 'PO_PHON': None}
The objective of this research is to determine the                         feasibility of a method to embed diagnostic expertise within                    hardware systems to achieve a self-diagnostic capability.  For                  this purpose, a self-contained electronic device is proposed                    which serves to link hardware, diagnostic information, expert                   diagnostic systems, human diagnosticians.  This link is called                  the Adaptive Memory Module/Template (AMMT), which is an                         intelligent software-controlled information logging device to                   be eventually packaged as a microchip.  This AMMT device is to                  be embedded into a host component as a module, or onto the                      component as a template.  The AMMT is externally powered and                    interrogated through a radio-frequency probe.  It has a                         battery-backed, non-volatile, crash-proof memory which is                       capable of data retention for ten or more years.  As an option,                 electronic links between the AMMT and the host component may                    serve to continuously record host component reliability                         parameters, such as electrical pulsing, temperature, vibration,                 humidity, etc., through embedded microsensors.                                       Based on the Phase I research, the AMMT concept is highly                  feasible with existing technology.  This feasibility is                         significantly enhanced with newer, more comprehensive                           electronic units.  Also, the AMMT has potential commercial                      applications extending beyond hardware maintenance to such                      areas as biotechnology, manufacturing, and robotics.
{'FirstName': 'Eugene', 'LastName': 'Jones', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eugene E Jones', 'EmailAddress': None, 'PI_PHON': '5132336550', 'NSF_ID': '000350347', 'StartDate': '08/01/1989', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Tractell Inc', 'CityName': 'Dayton', 'ZipCode': '454245774', 'PhoneNumber': '5132336550', 'StreetAddress': '4490 Needmore Road', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'OH10', 'ORG_UEI_NUM': None, 'ORG_LGL_BUS_NAME': None, 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '5373', 'Text': 'SBIR Phase II'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8803050.xml'}