Session Chairs
Hussein NASERALDIN
Yariv MARMOR
The Complexity Trap: Why Sophisticated Prediction Models Struggle in Practice
14:30 – 14:45
Yariv MARMOR, Industrial Engineering and Management
Examines when statistical model sophistication translates to real business value in industrial settings. Focuses on identifying critical noise thresholds where complex models cease providing operational advantages over simpler alternatives. Bridges predictive analytics and industrial statistics to develop practical, process-specific model selection frameworks prioritizing operational outcomes over statistical metrics.
Quiet Quitting Across Countries: What Drives It and How to Prevent It
14:45 – 15:00
Hilla PERETZ, Industrial Engineering and Management
My research focuses on cross-cultural human resource management, with particular interest in how national institutions and workplace factors influence employee behavior, motivation, and engagement. I explore topics such as quiet quitting, talent management, flexible work arrangements, and the role of job demands and resources across diverse global contexts.
Increasing willingness to pay in the food supply chain: a blockchain-based approach
15:00 – 15:15
Hussein NASERALDIN, Industrial Engineering and Management
Food products’ quality information is advertised on labels but do customers trust them? We investigate how the consumers’ Willingness-To-Pay (WTP) for food products can be increased by deploying managerial effort and advanced technologies, such as the Blockchain Technology. Our model generates optimal consumers’ WTP and profit. In a multi-echelon supply chain, a buyer holds a Bayesian belief about the quality of the input to be procured. Managerial effort is required both to enhance quality.
A measure of expected agreement between independent classifiers
15:15 – 15:30
Emil BASHKANSKY, Industrial Engineering and Management
My research focuses on investigating metrological characteristics of classification process, when the object’s property under study is presented on a scale consisting of K exclusive categories. The classifier can be a device, a human, an algorithm, or their combination. Often classifications are provided by a group of classifiers. Such metrological characteristics as classification accuracy and inter-classifiers agreement are particularly crucial in scenarios where the cost of false output is high.
Digital Twin Integration for Enhancing Robotic Fastening Systems in Industrial Automation
15:15 – 15:45
Meir THAN and Asi LEVI, Industrial Engineering and Management
This research explores the use of a digital twin in a smart robotic fastening system to enhance efficiency and quality in Industry 4.0. A MATLAB-based model was developed, integrating sensor data with a 3D simulation. Results showed a 30% reduction in downtime and a 15% improvement in fastening quality. The study highlights the potential of digital twins for predictive maintenance, real-time optimization, and integration into systems engineering.
Discrete cooperative coverage problems with general aggregate signal function
15:45 – 16:00
Illana BENDAVID, Industrial Engineering and Management
Project scheduling with stochastic durations: determination of a gate for each activity, a time before which the activity cannot begin, to minimize expected costs using the cross entropy heuristic .Appointment Scheduling in Healthcare: it allows to balance between quality of service and waiting time versus idle times and resource utilization.
Cooperative coverage problems: the selection of facilities to maximize the coverage where all facilities contribute to the coverage of each demand point.
