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Biography
Dr Afaf Remani is an Assistant Professor at the Department of Mechanical, Materials and Manufacturing Engineering (M3) at the University of Nottingham. At the same university, Afaf completed a PhD in Manufacturing Engineering with the Advanced Manufacturing Technology (AMT) research group preceded by a MSc in Mechanical Engineering. Earlier, she studied a BSc Honours degree in General Engineering at Al Akhawayn University (Morocco) and the University of San Diego (United States). Afaf has research and development experience in industrial robotics, vast academic teaching experience in mechanical and aerospace engineering, and research expertise in additive manufacturing.
Expertise Summary
Afaf has extensive expertise in the additive manufacturing (AM) of metal parts and the implementation of in-situ sensing solutions to infer meaningful information on their quality and study the effects of the dynamics governing their manufacture. Specifically, Afaf worked with laser-based powder bed fusion (PBF-LB), an AM technique that selectively melts metal powder layer-by-layer using a rapidly moving laser, but that is afflicted by the occurrence of in-process defects that do not always look like the anomalies present in the final bulk of the part. To inspect this phenomenon, Afaf led an in-depth study starting with the design of a multi-sensor measurement system for an industrial PBF-LB machine, the Renishaw AM250. The system consisted of three sub-systems: an optical fringe projection system to reconstruct layer topography, an infrared thermography system to measure layer thermal gradients, and a high-speed imaging system to monitor the melt pool (spot where the interaction between the laser and the material occurs). This multi-sensor measurement system was used during an experimental campaign to collect a rich and varied data bank (of a PBF-LB build, in addition to X-ray computed tomography scans of the as-built part post-manufacture. Since Afaf's research focuses on the investigation of the relationships that connect the layer-by-layer development of a part with its final condition, a thorough analysis of the datasets collected was conducted, leading to the development of a registration approach between in-process and post-process data and the establishment of a model (using statistical process control) that links layer topographical characteristics with cross-sectional densities in the as-built part.
Afaf's research is primarily centered around the establishment of meaningful correlations that could serve as a tool for the industrialist to predict the overall quality of a part (as acceptable or poor) without having to wait for a build to conclude. This would not only save time and effort, but could potentially reduce material wastage (i.e., less scrap) and reduce the risk of parts failing mid-operation. To this aim, Afaf's research led, so far, to the development of bespoke mathematical indicators, based on in-process topography, that could simply be monitored during the build and support real-time decision-making on whether a build should carry on or be stopped (GO or NO-GO). This method also enables the discrimination between low- and high-quality parts solely based on their monitored layer-by-layer topographies. Combined with predictive modeling and/or machine learning classifiers, this solution could prove even more invaluable for quality monitoring via the implementation of closed-loop feedback control technologies.
Teaching Summary
Afaf is currently an Assistant Professor teaching engineering design modules to BEng and MEng Mechanical Engineering students at the University of Nottingham. Her duties include the delivery of… read more
Afaf is currently an Assistant Professor teaching engineering design modules to BEng and MEng Mechanical Engineering students at the University of Nottingham. Her duties include the delivery of teaching material, designing and conducting assessment, enabling technologies and practical teaching methods, and contributing to module and curricula development. Afaf was awarded an Associate Fellowship of the Higher Education Academy (AFHEA) after satisfying the requirements of the UK's Professional Standards Framework and was also granted a "Preparing To Teach in Higher Education" certificate by the University of Nottingham. Earlier in her career, Afaf worked in teaching assistantship supporting teaching and laboratory demonstration activities and acquired experience in academic tutoring and lecturing from the University of San Diego.