Page 65 - tech fest 2025 אשדוד חוברת תקצירים

Design and Development of a Daily Scheduling and Allocation System for Patients in the Oncology and Hematology Departments at Assuta Hospital, Ashdod
IEM-A-05
Shalev Shlomo; sshalev1056@gmail.com Yedidya Glazer; yedidyag1@gmail.com
Advisor: Dr. Hagai Ilani
SCE - Shamoon College of Engineering, Ashdod
This project is developing a scheduling and allocation system for Oncology and Hematology patients at Assuta Hospital, Ashdod. Currently, patient assignments are done manually by the administrative staff, leading to inefficiencies, delays, and lack of synchronization between medical and administrative teams, ultimately impacting patient experience. The proposed system will optimize nurse and treatment station allocation using advanced algorithms that consider treatment types, arrival times, patient preferences, and logistical constraints. By improving scheduling efficiency and resource management, the system will enhance patient care and streamline operations. Key objectives include developing a decision-support system, implementing an advanced optimization algorithm, and improving overall service quality. The system is expected to reduce delays, optimize workflow, and provide a more personalized and efficient treatment experience.
Keywords: Assuta Hospital, decision support system, oncology and hematology departments, optimal allocation, patient experience, personalized treatment, scheduling system, treatment planning
“FabExpert”: A Smart Platform Connecting Factories and Service Providers in the Semiconductor Industry
IEM-A-06
Gil Mansharof; mansharofgil@gmail.com Valentin Bogach; valentinbogach6@gmail.com
Advisor: Dr. Adi Katz
SCE - Shamoon College of Engineering, Ashdod
“FabExpert” addresses the challenge of finding expert service providers for machines without manufacturer warranties in the semiconductor industry. Many factories rely on a single provider due to difficulties in finding alternatives, leading to high costs and limited competition.
The system we have developed connects factories with service providers, enabling factories to upload malfunctions and hire experts based on criteria such as quality, availability and price. It also enables the sharing of essential machine data, including descriptions, images and videos.
“FabExpert” integrates ‘augmented reality’ (AR) for remote support and predictive maintenance to detect faults before they occur. This improves failure management, reduces downtime, and enhances efficiency. This platform optimizes service provider selection, increases competitiveness and supports the transition to “Industry 4.0.”
Keywords: augmented reality, “Industry 4.0”, information system, predictive maintenance, process optimization, repair services, semiconductors
Book of Abstracts | 2025
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