Seminar: Adaptive Control of a Hybrid Production System with Partial Orbit Information by Seval Ata
Department of Industrial Engineering
Adaptive Control of a Hybrid Production System with Partial Orbit Information
Recently, with the efforts in switching to a circular economy, reprocessing of products has gained importance. Both original equipment manufacturers and third-party remanufacturers collect products back from the end users and reprocess them to satisfy the demand. Such systems are called hybrid production systems. In these systems, the return process is a function of product quantity in-use which is essential to build an optimal decision policy. The possibility that each satisfied demand is a potential return that can satisfy another demand after being reprocessed further complicates the production control. Under the full observability of orbit assumption, the optimal control policy helps to decrease the system cost significantly depending on the return probability. However, orbit is at most partially observable in reality and changes continuously. A proper estimation of orbit size is essential to utilize the optimal control policy. In this study, we aim to analyze a hybrid production system with indirect observations about orbit. As the indirect information, we use the time intervals between product returns. As a test bed, we build a simulation environment that represents the complex characteristics of a hybrid production system and allows continuous control of the production. In this way, we aim to apply production decisions online as the orbit estimation is updated.
Seval Ata is currently a Doctoral Candidate in the Industrial Engineering department at Bogazici University. Her research interests are stochastic modeling of hybrid manufacturing systems, optimal production decision mechanisms and currently, she is mainly focusing on adaptive production control mechanisms. She received her BS and MS degrees in Industrial Engineering from Bogazici University. She is currently employed as a research assistant at Istanbul Technical University.
Date: Friday, June 4, 2021
Online Seminar Link:
Meeting ID: 934 3051 2540