Electronic Reliability and Asset Management for application in Printed Circuit Board Design Test and Maintenance

Applications are invited for a PhD degree in Artificial Intelligence and Machine Learning (AI/ML) to advance the security and reliability of cyber-physical systems, embedded systems, and electronics/electrical systems. The research would focus on building advanced machine learning techniques and edge AI modelling for moving to the next generation of secure and reliable electronic networking specific to applications in the automotive industry.

The advancement of technology has led to the widespread use of electrical and electronic systems in various industrial applications. Although such technological advances have created a large market for printed circuit boards (PCB) and electrical component suppliers, they open new challenges for industries and users concerning design, manufacturing, maintenance, and life-cycle management. The problem is more acute in applications requiring secure, safe, durable, robust, and reliable systems.

Evaluating the performance of complex systems from various aspects of the electrical and electronic system requires deploying integrated and multi-domain processes for automating tests and assessments. It involves building tools for failure diagnosing and advancing system maintenance by developing effective prognoses policies, which should be applied to PCB repair and maintenance.

With this research, you will study state-of-the-art PCD design, test and assessment. Further, you would contribute to the electrical, thermal, structural and fatigue analysis of electronic and electrical components and systems and explore artificial-Intelligent techniques for analyzing the test results from a wide range of system performance and optimization, ultimately leading to advancing PCB life-cycle management.

Cranfield is a unique learning environment with world-class programmes, unrivalled facilities and close links with business, industry and governments, all combining to attract the best students and teaching staff worldwide. 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 14th 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 research on 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 PhD candidate will have access to the facilities held by AIRC and DARTeC in addition to having interactive sessions with experts at AIRC and DARTeC.

IVHM hosts a number of research groups, including ‘Reliable and Secure Electronic Design (Seretonix), which focuses on research in the area of electronic health management, hardware root of trust, smart instrumentation, and secure vehicular communication systems. IVHM is also an active member of Europractice, a consortium of European research organisations supporting academic institutions with access to CAD tools, IC prototyping services, system integration solutions, training activities and possibilities for small volume production. It allows wider adoption of state of the art microelectronics and electronic system design methodologies and technologies. It enables IVHM to provide students with excellent technical support (hardware and software) and training courses based on the needs of the research and availability of the courses within the UK or EU.

The successful culmination of this project envisages the availability of an efficient and intelligent life-cycle test and management regime for highly future innovative, reliable- and safety-critical PCBs. It enhances the design and maintenance of electronics over its entire design, manufacturing and operational service life. Also, the AI-based built-in solutions in this domain would serve as a benchmark for high-end platforms requiring electronics and PCBs, for intense, in the marine, commercial, military, and automotive sectors.

The project will provide active collaboration and exchange of ideas and knowledge with key stakeholders within different centres of the Cranfield University, industrial partners in the automotive industry, Seretonix’s industrial contacts. The paraphernalia of electronic life-cycle testing and maintenance, AI and Machine Learning based applications within the IVHM centre and across other research centres would be helpful for the potential researcher in acquiring essential knowledge and building skills (e.g., PCB and embedded electronic design and AI algorithms’ formulation) required for this specific research project. The IVHM Centre encourages and supports ample opportunities to disseminate individual research through reputed journals and present papers in high profile and well-known IEEE conferences within the UK and across the globe. It also provides a networking platform for promising researchers to lay the foundations of their professional relationships with key representatives from various companies. More significantly, the potential candidate will have the opportunity to present his research work during quarterly technical reviews to the wider research community from within the university and the industrial partners (Boeing, Thales, Airbus, and BAE Systems).

Upon successful completion of the project, the potential candidate will be able to carry out research activities independently and more vigorously. This research will be formative for the potential candidate in building his/her skills in understanding complex systems, reliability analysis, data analytics AI/ML techniques, analytical logic, and algorithm craftsmanship. Understanding the essence and application of futuristic reliable and safe electronic system design would broaden the employability scope appreciably.