About the Project
Introduction
Applications are invited for a PhD degree in the area of Reliable Electronics. The research is focused on building advanced testability techniques for moving from conventional functional tests to AI-Based performance analysis for the next generation of reliable electronics systems specific to applications in the harsh environment.
Background
Despite improvements in the design for testability techniques such as JTAG that widely has been accepted by industries, current VLSI technologies have still failed to implement a complete on-chip health monitoring and management mechanism. The reason is that conventional testability techniques have been developed explicitly for fault detection by testing the function of devices’ building blocks against various test scenarios. As a result, conventional built-in test techniques have limited capabilities for monitoring the performance of the electronic devices needed to observe function variations raised from degradation mechanisms. Additionally, there is still a lack of technological approach for building prognostic, diagnostic, and reasoning techniques for supporting electronics with effective health management capabilities. With this research, you contribute to moving beyond conventional design for testability technique toward design for prognostics and further explore Artificial-Intelligent techniques for analysing the test results for assessing the health state of the electronics.
This research project aims at designing and developing highly reliable electronic systems for applications in harsh environments such as in aerospace (not limited to) where there is a wide request for optimising the performance of aircraft, decreasing maintenance costs. These primarily require the aircraft industries to move toward more electric aircraft (MEA) with added smart instruments; hence, use of more embedded electronics, smart transceiver, and so on. The reliability of electronics for such applications is limited by aging mechanisms accelerated at the high temperature. Hence, assessing the performance of electronics is seen as a critical enabler for the aircraft industry to drive more effective life cycle tests and costs, maintainability, and reliability.
Cranfield is a unique learning environment with world-class programmes, unrivaled facilities, close links with business, industry, and governments, all combining to attract the best students and teaching staff from around the world. In 2014, 81% of research at Cranfield was rated as world-leading or internationally excellent in the Research Excellence Framework (REF).
The Integrated Vehicle Health Management (IVHM) Centre is in its 12th year of operation. Founded by Boeing and a number of aerospace partners (BAE Systems, Rolls-Royce, Meggitt, and Thales) in 2008, it has grown to perform work in sectors such as transport, aerospace, and manufacturing. The Centre integrates a multidisciplinary research effort to develop cost-effective component and system health management technologies capable of supporting ground and on-board applications of high-value, high-complexity systems. IVHM Centre is a member of the Digital Aviation Research and Technology Centre (DARTeC), which focuses its researchon aircraft electrification, connected systems, unmanned traffic management, seamless journey, distributed airport/airspace management, and conscious aircraft. Research England, Thales, Saab, Aveillant IVHM Centre, and Boxarr are some of the prominent members of DARTec. IVHM Centre also works in close collaboration with Aerospace Integration Research Centre (AIRC), founded in partnership with Airbus and Rolls-Royce. The potential Ph.D. candidate will have access to the facilities held by AIRC and DARTeC in addition to having interactive sessions with experts at AIRC and DARTeC.
The successful culmination of this project envisages the availability of an efficient and intelligent prognostics regime for highly reliable and dependable smart electronic systems, thereby enhancing aircraft availability over its entire operational service life. Also, the AI-based built-in prognostics’ system would serve as a benchmark for other high-end platforms such as ships, autonomous vehicles as well as smart semiconductor industries in optimising their operations.
