The Wire Additive Manufacturing (WAM) technology offers high deposition rates allowing to manufacture of large-scale near-net shape components within shorter lead-times. The components manufactured by this technology very often serve is high sensitivity applications in aerospace and defense industries where the demands for quality and integrity standards are markedly high. Therefore, similar to any other manufacturing processes, the WAM components should be examined by Non-Destructive Evaluations (NDE) methods to qualify for the certification. In conventional industrial settings, WAM components are transferred to the inspection cell after completion of manufacturing and cooling down to room temperature for the final inspection stage which can take from hours to days, depending on the component size and the complexity. In contrast, this project aims at robotic deployment and delivery of the NDE during the manufacturing process, and in-situ intelligent analysis of the results to provide early intervention opportunities for repair and remediation activities slowing for reduced material waste and increased throughput.
Ultrasound (UT) and eddy current testing (ECT) are both well-established NDE methods that are frequently used in the industry, and each offers unique opportunities for inspection of WAM components. This Ph.D. aims to investigate the possibility of using a robotically enabled combined NDE approach consisting of ECT sensors, with high sensitivity to surface defects, and UT sensors with their strong capability of bulk coverage in a WAM inspection. Uniting the two sensors and incorporating them within an automated inspection system not only guarantee the quality of the last deposited AM layer through ECT inspections but also ensure a thorough sweep of the previous layers through the UT inspection for any potential delayed cracking. However, forming a bi-sensor inspection unit and merging the sensors data for an improved inspection capability are accompanied by challenges associated with the sensors integration, robotic programming, and signal fusion and interpretation that will be scrutinized in this Ph.D. program.
It is desired that the candidate is familiar with NDE techniques such as ultrasonic and eddy currents inspection. The candidate should have some experience in C#, C++ and Matlab coding and be interested in industrial robotic programming (e.g. with KUKA robots) and automation. The position may require day trips to Lightweight Manufacturing Centre located near Glasgow airport, where the WAAM cell is located, to conduct some experimental and integration activities.
The project is directly relevant to the many industrial sectors that are ready to revolutionize their production strategies to reduce costs and time by adopting AM technology for manufacturing of high-value components – (Aerospace, Marine, Defence & general High-Value Manufacturing). It also has cross-cutting applicability to other arc-based welding processes and high-temperature inspections which are routinely used and accepted by Nuclear and Oil& Gas industries.
The project will make extensive use of the £2.5 million cutting-edge Robotically-Enabled Sensing (RES) hub including several advanced industrial robots and NDE equipment at the Centre for Ultrasonic Engineering (CUE) at the University of Strathclyde. The student will have access to RoboWAAM cell (the first commercial WAM deposition cell) at the manufacturing and research facilities of the National Manufacturing Institute of Scotland and Lightweight Manufacturing Centre.
The student will work within an internationally renowned and growing team of diverse and multi-disciplinary researchers and engineers, physicists, and mathematicians and will have the opportunity to work on the inspection of one of the advanced and fast-growing 3D printing processes to develop the knowledge and the skill set that will be in a very high demand in near future given the widespread use of the AM technology. The student will gain a greater appreciation of the specific industrial challenges of the process and the opportunity for automated inspection during AM deposition.
The project will be primarily supervised by Dr. Ehsan Mohseni, Lecturer in CUE, and the secondary project supervisor will be Prof. Gareth Pierce, Spirit AeroSystems/Royal Academy of Engineering Research Chair and the lead of a multidisciplinary NDE automation team at the University of Strathclyde.
Candidates requiring more information or interested in applying should email Dr. Ehsan Mohseni via firstname.lastname@example.org. Thereafter, they should submit their CV, academic transcript, and a covering letter outlining their suitability for the position, to him. Following the review of the application submissions, selected candidates will be invited for an interview.
The application submission deadline is 31 August 2021.
The project will start on 1 October 2021.
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