The German Jordanian University (GJU) has achieved a new accomplishment, with the graduation project titled “A Machine Learning Enabled Methodology for Forecasting and Managing Obsolescence in the Aerospace Industry” winning third place in the 2026 Graduation Projects Competition organized by the Jordan Engineers Association (JEA), under the Mechanical Engineering/Industrial Engineering Division. The annual competition aims to encourage students to pursue innovation and excellence in their engineering projects.
The project was completed by Rawda Nasser Al-Deen, a graduate of the School of Engineering at GJU, under the supervision of Dr. Anas Attieh, with active contribution and support from Eng. Saif Al-Zyoud. The graduation project was carried out at Diehl Aerospace in Germany after she completed the requirements of the German Year and extended her stay to complete the project within a specialized industrial environment.
The competition featured nearly 300 graduation projects from various Jordanian universities. This year’s edition was characterized by a highly competitive level and a new and innovative project evaluation mechanism based on reviews by judges and experts from academic institutions and the industrial sector, according to Prof. Yasmin Murad, Chair of the Evaluation Committee.
The project addresses one of the key challenges facing the aerospace industry: Electronic Obsolescence, which arises from the gap between the long operational lifespan of aircraft and the shorter lifespan of electronic components. This creates significant challenges related to continued product support, increased maintenance costs, and supply chain management.
To address these challenges, the project presents an innovative methodology supported by artificial intelligence and machine learning technologies. It aims to advance component obsolescence management from a reactive approach, which addresses problems after they occur, to a proactive approach based on data analysis and early prediction. The methodology also incorporates an integrated framework covering forecasting, risk analysis, automation, and decision support, contributing to more efficient product lifecycle management in the aerospace industry.
The project also involved developing a predictive model based on machine learning techniques to analyze historical data and forecast future needs, in addition to designing a prototype user interface that enables the automation of data entry, model execution, and results extraction. This enhances the applicability of the methodology in industrial environments and contributes to improving the efficiency of obsolescence management processes.
This achievement reflects the integration of academic research and industrial application, as well as the importance of leveraging artificial intelligence technologies to develop practical solutions to challenges facing industries with long product lifecycles. It also highlights the ability of GJU graduates to deliver high-quality projects that address the needs of global industrial sectors.
The project further demonstrates the success of GJU’s model of integrating academic education with practical application through its partnerships with global industrial institutions. The project’s excellence resulted in Rawda Nasser Al-Deen receiving a job offer to return to Diehl Aerospace in the same department where she completed the project, where she will serve as a Product Support Manager. This further underscores the quality of the University’s graduates and their ability to compete in the international job market.