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Barış Tan - Design and Control of Production Systems and Supply Chains by Using Supervised Learning Methods

Overview

This project aims at developing a general method to design and control production systems and supply chains.  First, the output flow characteristics of a given building block will be determined as a function of input flow characteristics by using a supervised learning algorithm.  Discrete-event simulation will be used to generate the training data for the learning algorithm.   Each analyzed building block will be combined in different configurations to evaluate the performance of different production system and supply chain structures in order to design production systems and supply chains effectively.  Release control and inventory control problems in production systems and supply chains will also be analyzed by using machine learning and simulation.

Apply now! Summer Semester 2020/21
Application period has ended
Studies commence
Jun 28, 2021

Application deadlines apply to citizens of: United States

Apply now! Summer Semester 2020/21
Application period has ended
Studies commence
Jun 28, 2021

Application deadlines apply to citizens of: United States