US Air Force (AFWERX) Microelectronics Supply Chain Provenance Challenge
The team is the Champion of the US Air Force (AFWERX) Microelectronics Supply Chain Provenance Challenge.
The aim of the project was to develop the technology that will allow using low-cost hardware and a minimum of human resources, generate Bill Of Materials (BOM) for microelectronic boards in a timely manner and generate the provenance solution using defined BOM. T
The key features of the technology developed include:
- Generation of the static information about the board and components (BOM)
- Identification of the operational information about the microelectronic boards
- Identification of board tempering at component and operational levels
The unique features for the solution of this problem include:
- The efficient use of 3D printer-based rig to generate microscopic level optical images of the circuit board
- Generation of 3D model of the circuit board
- Efficient OCR system for text recognition printed on the microelectronic board
- Identification of Tampering Detection Threshold Using Capsule Neural Networks
- Virtual Sensor Network (VSN) developed to model unknown analogue and digital I/O relationships within operational boundaries.
- X-ray image analysis
The developed technology will allow to generate board BOM and identify the tampering level at component-based and functional levels.
Virtual Sensor Network (VSN)
3D-printer based rig for optical image generation
Generation of 3D model of the circuit board
Microelectronics Supply Chain Provenance Challenge
Microelectronics Supply Chain Provenance Challenge
Microelectronics Supply Chain Provenance Challenge
Photo of the team
Photo of the team
Meet the Principal Investigator(s) for the project
Dr Tatiana Kalganova - DEGREES AWARDED
PhD Napier University
Research-engineer degree Belarusian State University of Informatics and Radio-electronics, Minsk, Belarus
MSc (distinction) Belarusian State University of Informatics and Radio-electronics, Minsk, Belarus
ACADEMIC POSTS
2000-present Lecturer àËÅöÊÓƵ
2003-2011 Business Fellow London Technology Network, LTN Link between research activities at àËÅöÊÓƵ and industry
1997-2000 PhD student Napier University
1994-1997 Research Assistant Belarusian State University of Informatics and Radio-electronics
Related Research Group(s)
Digital Manufacturing - Being at the forefront of solutions for building smart machines, we create an operational framework for the digital transformation to Industry 4.0.
AI Social and Digital Innovation - Social, economic and strategic effects of AI and associated technologies. Impact of AI and related technologies on societies, organisations and individuals.
Partnering with confidence
Organisations interested in our research can partner with us with confidence backed by an external and independent benchmark: The Knowledge Exchange Framework. Read more.
Project last modified 20/07/2021