Yetkin Ekren, Banu
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Name Variants
Banu Yetkin Ekren
B. Yetkin Ekren
B. Yetkin Ekren
Job Title
Doç.Dr.
Email Address
Main Affiliation
01.01.09.03. Endüstri Mühendisliği Bölümü
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
1
Research Products
3GOOD HEALTH AND WELL-BEING
0
Research Products
4QUALITY EDUCATION
2
Research Products
5GENDER EQUALITY
0
Research Products
6CLEAN WATER AND SANITATION
0
Research Products
7AFFORDABLE AND CLEAN ENERGY
4
Research Products
8DECENT WORK AND ECONOMIC GROWTH
2
Research Products
9INDUSTRY, INNOVATION AND INFRASTRUCTURE
22
Research Products
10REDUCED INEQUALITIES
0
Research Products
11SUSTAINABLE CITIES AND COMMUNITIES
4
Research Products
12RESPONSIBLE CONSUMPTION AND PRODUCTION
12
Research Products
13CLIMATE ACTION
1
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14LIFE BELOW WATER
5
Research Products
15LIFE ON LAND
0
Research Products
16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
17PARTNERSHIPS FOR THE GOALS
10
Research Products
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Documents
71
Citations
2216
Scholarly Output
67
Articles
33
Views / Downloads
0/11
Supervised MSc Theses
0
Supervised PhD Theses
0
WoS Citation Count
770
Scopus Citation Count
955
Patents
0
Projects
0
WoS Citations per Publication
11.49
Scopus Citations per Publication
14.25
Open Access Source
26
Supervised Theses
0
| Journal | Count |
|---|---|
| International Journal of Production Research | 7 |
| Sustainability | 6 |
| Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE) | 6 |
| 11th IFAC Conference on Manufacturing Modelling, Management and Control (MIM) -- JUN 30-JUL 03, 2025 -- Trondheim, NORWAY | 4 |
| Proceedings of the 5th NA International Conference on Industrial Engineering and Operations Management IOEM 2020 | 3 |
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67 results
Scholarly Output Search Results
Now showing 1 - 10 of 67
Article Citation - WoS: 49Citation - Scopus: 52Graph-based solution for performance evaluation of shuttle-based storage and retrieval system(TAYLOR & FRANCIS LTD, 2017) Banu Yetkin Ekren; Yetkin Ekren, Banu; Ekren, Banu YetkinThe aim of this study is to provide a graph-based solution for performance evaluation of a new autonomous vehicle-based storage and retrieval system shuttle-based storage and retrieval system (SBS/RS) under various design concepts. By the graph-based solution it is aimed the decision-maker (i.e. warehouse manager) evaluates a pre-defined system's performance promptly and decides on the correct design concept based on his/her requirements from thousands of alternative design scenarios of SBS/RS. The design concepts include number of bays (NoB) aisles (NoA) and tiers (NoT) for the rack design and arrival rate of storage/retrieval (S/R) transactions to an aisle of the warehouse (AR). The performance of the system is evaluated in terms of average utilisation of lifts and average cycle time of S/R transactions. Simulation is utilised for the modelling purpose. Seven NoT seven NoB and six AR scenarios are considered in the experiments. Hence 294 experiments are completed to obtain the graphs. By this study to the best of our knowledge it is the first time a graph-based solution including comprehensive design concepts of SBS/RS is presented.Conference Object Citation - WoS: 2Citation - Scopus: 2Parallel Workforce Assignment Problem for Battery Production(SPRINGER-VERLAG SINGAPORE PTE LTD, 2022) Aslihan Erdosan; Aysenur Tali; Berfu Kircali; Buket Gunal; Ecem Nazli Dedecengiz; Damla Yuksel; Banu Yetkin Ekren; Yüksel, Damla; Erdosan, Aslihan; Günal, Buket; Dedecengiz, Ecem Nazlı; Ekren, Banu Yetkin; Erdoğan, Aslıhan; Talı, Ayşenur; Kırcalı, Berfu; NM Durakbasa; MG GencyilmazThis paper studies workforce assignment problem for battery production in a company in Turkey. Several types of batteries are produced in the studied company. Mostly the operations are semi-automated. In the production process the workers are assigned to multiple operations irregularly based on the priority of productions. In the company average utilization of worker is low and average cycle time of a product is high due to inefficient allocation of the workforce within the operations. In order to analyze the main system problem we simulate the system and observe the queue lengths to identify the bottlenecks. By dynamic assignment of workers at stations based on real time queue conditions the workloads can be balanced throughout the production lines. In this project a simulation-based system improvement is completed by applying: (i) dynamic utilization of workforce to reduce average cycle time of a battery (ii) assignment of parallel workforce where they can work for the same operation simultaneously and (iii) observation of real-time queue lengths of stations. Three dynamic assignment policies are developed and compared with each other. The best policy providing minimum cycle time for a battery production is selected to be the best.Book Part Citation - Scopus: 2Additive manufacturing and its impact on pharmaceutical supply chains(Elsevier, 2024) Wenqi Li; Banu Yetkin Yetkin Ekren; Emel Aktas; Li, Wenqi; Aktas, Emel; Ekren, Banu Y.Additive manufacturing (AM) also known as 3D printing has the potential to improve the performance of the pharmaceutical supply chain (PSC). By using 3D printing for manufacturing drugs pharmaceutical companies can reduce waste by using only the required number of raw materials and eliminating excess inventory. This chapter will provide a systematic literature review of the state of the art of AM in PSC and develop a conceptual framework to explain their interconnections. It was found that 3D printing impacts the SC in three main ways: reducing complexity moving manufacturing facilities closer to the end user and shifting production from make-to-stock to make-to-order. These changes influence the inventory level which in turn affects SC sustainability efficiency responsiveness and resilience. This study provides a conceptual framework that illustrates the interrelationships between various variables in the medical SC impacted by 3D printing technology. © 2024 Elsevier B.V. All rights reserved.Conference Object Quantitative Methods for Agri-Food Supply Chain Resilience: A Systematic Literature Review Using Text Mining(Elsevier, 2025) Çali, Sedef; Toy, Ayhan Özgür; Ekren, Banu YetkinAgri-food Supply Chains (AFSCs) face increasing disruptions from natural disasters, pandemics, and economic crises, necessitating robust quantitative analysis for resilience. This study conducts a Systematic Literature Review (SLR) using text mining and Latent Dirichlet Allocation (LDA) to identify six key research themes, including risk management, pandemic effects, simulation-based resilience, climate change, market price volatility, and optimization models. Findings reveal that multi-criteria decision-making, simulation, optimization, and machine learning are widely used, yet gaps remain in Artificial Intelligence (AI)-driven risk prediction, real-time data integration, and adaptive decision-making This review offers insights for researchers and practitioners, emphasizing the need for AI, digital twins, and blockchain to enhance AFSC resilience. Copyright (C) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Article Citation - WoS: 24Citation - Scopus: 28Simulation-Based Performance Analysis for a Novel AVS/RS Technology with Movable Lifts(MDPI, 2021) Boris Jerman; Banu Yetkin Ekren; Melis Kucukyasar; Tone Lerher; Jerman, Boris; Kucukyasar, Melis; Lerher, Tone; Ekren, Banu YetkinThis paper studies a novel autonomous vehicle-based storage and retrieval system (AVS/RS) design with movable lifts (AVS/RS/ML). In the proposed system there are aisle-captive lifts that are able to travel along the warehouse aisle to position themselves at the target column location. Those lifts can lift up/down the autonomous vehicles to/from the target storage compartment when they are in standstill. This novel design is proposed as an alternative to existing AVS/RSs to balance the resource utilizations as well as to provide an inexpensive solution with highly utilized autonomous vehicles (i.e. AGVs). As an initial work for this novel system two alternative operating designs under different racking configurations are experimented. We compare those two designs by their throughput rate performance metrics under the arrival rate scenarios with highly utilized AGVs (i.e. 95%). Besides we experiment with two warehouse capacity scenarios: 900 and 1800 storage compartments. The results show that designs with two separate I/O point locations provide a better throughput rate than designs with single I/O point location. Besides a decreased number of columns in the system improves the system's performance.Conference Object Citation - Scopus: 2Intelligent Supply Chains Through Implementation of Digital Twins(Springer Science and Business Media Deutschland GmbH, 2022) Oray Kulaç; Banu Yetkin Yetkin Ekren; Ayhan Özgür Toy; Toy, A. Ozgur; Kulac, Oray; Ekren, Banu Y.; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. CebiData-driven decision-making process can be defined to be the sequential activities of real-time data collection data analytics optimization and decision making. Developments in Industry 4.0 technologies have made it possible to realize that new quality decision-making process. When that decision-making process is performed under the simulation model of a system developed on real-time data-based and end-to-end connection manner to prevent the disruption risks and to improve resilience in a system then it constitutes a digital twin (DT). A DT is a virtual representation of an object or system that can help organizations monitor operations perform predictive analytics and improve processes. For instance a DT could provide a digital replica of the operations of a factory communications network or the flow of goods through a supply chain system. In this work we focus on DT implementations in supply chain networks. We present state of the art implementation of DTs in supply chains and their prospective utilizations towards creating intelligent supply chains. © 2022 Elsevier B.V. All rights reserved.Conference Object Citation - Scopus: 2Smart transaction picking in tier-to-tier SBS/RS by deep Q-learning(IEOM Society, 2021) Bartu Arslan; Banu Yetkin Yetkin Ekren; Arslan, Bartu; Ekren, Banu Y.By the rapid growth of e-commerce the intralogistics sector is facing new challenges. Intralogistics sector requires more flexible scalable processes with maximum reliability and availability. They are complicated and interconnected systems whose all components are required to be perfectly coordinated with each other for optimal functionality. In this work we study an intralogistics technology shuttle-based storage and retrieval system (SBS/RS) where shuttles are tier-to-tier. In this novel system design in an effort to increase shuttle utilization as well as decrease initial investment cost shuttles are designed in a more flexible travel manner so that they can change their tiers within an aisle by using a separate lifting mechanism. Due to the complexity of such system design as well as aiming to obtain fast transaction process time by the decreased number of shuttles in the system we implement a Deep Q-Learning (DQL) approach to let shuttles select the best transaction to process based on its targets. We compare the performance of the DQL by the average cycle time per transaction performance metric with the other well-known selection rules First-in-First-Out (FIFO) and Shortest Process Time (SPT). Results show that Deep Q-Learning approach produces better results than those FIFO and SPT. © 2021 Elsevier B.V. All rights reserved.Conference Object Optimal Inventory Share Policy Search for e-Grocery Food Supply Network(SPRINGER-VERLAG SINGAPORE PTE LTD, 2022) Berk Kaya; Dilara Dural; Mehmet Sager; Melike Akdogan; Asime Bengisu Ildesler; Mert Paldrak; Banu Yetkin Ekren; Dural, Dilara; Sağer, Mehmet; Kaya, Berk; Ekren, Banu Yetkin; Akdoğan, Melike; İldeşler, Asime Bengisu; Paldrak, Mert; NM Durakbasa; MG GencyilmazThe study focuses on intercompany inventory share policies between e-groceries. Companies are attempting to adapt to the Internet of Things environment considering the increased amount of e-commerce throughout the world as well as the effect of the COVID-19 pandemic. The goal of the study is to create a strong bond between companies by taking advantage of today's technology and helps in the reduction of capital risk. These relationships may also lead to greater market share reduced inventory enhanced delivery services higher quality and faster product development cycles with the help of inventory visibility. This research studies two inventory sharing strategies among e-grocers to improve the supply network's efficiency and responsiveness. The policies considered in this study include share policies based on expiration dates and share policies based on distance - inventory. We use a simulation modeling technique to represent such policies. Besides in an effort to compare how lateral inventory share implementation affects the system performance non-inventory sharing policy has been modeled and these three policies were compared. The goal of this study is to determine the best s S inventory management levels in e-groceries under those rules. Here s and S represent re-order and order-up-to levels for replenishment of products. We are motivated to do this study to decrease food waste in such a food network since management of perishable food products is important owing to their perishable feature. Distance average freshness average inventory and waste product numbers were compared in this project based on the lowest inventory number in line with three main policies. The opt quest tool was used in the arena to find the results. Consequently company owners should choose Expiration Date policy as it has advantages such as total number of waste products and average inventory level.Corrigendum Integrating sustainability across the lifecycle of electric vehicle batteries: Circular supply chain challenges- innovations- and global policy impacts (vol 216- pg 1- 2025)(PERGAMON-ELSEVIER SCIENCE LTD, 2025) V. M. Aishwarya; Banu Yetkin Ekren; Tej Singh; Vedant Singh; Singh, Tej; Aishwarya, V.M.; Ekren, Banu Yetkin; Singh, VedantArticle Citation - WoS: 16Citation - Scopus: 19Transaction selection policy in tier-to-tier SBSRS by using Deep Q-Learning(Taylor and Francis Ltd., 2023) Bartu Arslan; Banu Yetkin Yetkin Ekren; Arslan, Bartu; Ekren, Banu YetkinThis paper studies a Deep Q-Learning (DQL) method for transaction sequencing problems in an automated warehousing system Shuttle-based Storage and Retrieval System (SBSRS) in which shuttles can move between tiers flexibly. Here the system is referred to as tier-to-tier SBSRS (t-SBSRS) developed as an alternative design to tier-captive SBSRS (c-SBSRS). By the flexible travel of shuttles between tiers in t-SBSRS the number of shuttles in the system may be reduced compared to its simulant c-SBSRS design. The flexible travel of shuttles makes the operation decisions more complex in that system motivating us to explore whether integration of a machine learning approach would help to improve the system performance. We apply the DQL method for the transaction selection of shuttles in the system to attain process time advantage. The outcomes of the DQN are confronted with the well-applied heuristic approaches: first-come-first-serve (FIFO) and shortest process time (SPT) rules under different racking and numbers of shuttles scenarios. The results show that DQL outperforms the FIFO and SPT rules promising for the future of smart industry applications. Especially compared to the well-applied SPT rule in industries DQL improves the average cycle time per transaction by roughly 43% on average. © 2023 Elsevier B.V. All rights reserved.
