Kaya, Berk
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Araş.Gör.
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01.01.09.03. Endüstri Mühendisliği Bölümü
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| Journal | Count |
|---|---|
| International Symposium for Production Research ISPR 2023 | 2 |
| 21st International Symposium on Production Research (ISPR) - Digitizing Production System | 1 |
| 22nd International Symposium for Production Research ISPR 2022 | 1 |
| Sustainability | 1 |
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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.Conference Object Citation - Scopus: 2Inventory Management Optimization for Intermittent Demand(Springer Science and Business Media Deutschland GmbH, 2024) Berk Kaya; Oktay Karabağ; Fatma Ravza Çekiç; Bekir Can Torun; Aleyna Ömrüm Başay; Zeynep Eda Işıklı; Çağlar Çakır; Çekiç, Fatma Ravza; Kaya, Berk; Torun, Bekir Can; Çakır, Çağlar; Başay, Aleyna Ömrüm; Işıklı, Zeynep Eda; Karabağ, Oktay; N.M. Durakbasa , M.G. GençyılmazThis report discusses inventory management and demand forecasting issues faced by a well-known electrical equipment company. The company requires a precise inventory management system with a wide range of products to handle its high production volume. The company has trouble forecasting intermittent demand patterns due to a lack of appropriate analytical methodologies. To overcome these challenges this study developed an inventory management system that integrates Newsvendor and Order Up Policy whose analytical methods are optimized with the inventory management policy. A comprehensive review of the existing literature on inventory management is undertaken to gather valuable information and best practices. This study has been developed based on the research conducted by Syntetos (2009). A mathematical model has been included to maximize order levels considering lead time and costs. In the model SBA and Croston methods are used for intermittent demand forecasting. This model includes various parameters and assumptions that allow calculating expected total costs and determining the optimum order level that efficiently meets customer demand while minimizing expenses. The methods employed optimize inventory management minimize inventory cost and enhance customer satisfaction. © 2024 Elsevier B.V. All rights reserved.Master Thesis Simulation Model of Condition-Based Maintenance with a Decision of Spare Part Quantity(2024) Kaya, Berk; Fadıloğlu, Mehmet MuratIndustries are depending more and more on sophisticated machinery for production and services as a result of technological advancements. However, firms may suffer large financial losses due to these machines breaking down. As a result, the maintenance of machinery has become increasingly important in ensuring smooth operations and minimizing potential economic losses. Condition-based maintenance (CBM) has emerged as a crucial approach to estimating and preventing machinery failures by collecting and analyzing sensor data that reflects the machine's state of deterioration. However, due to the high cost of sensors and the confidentiality concerns of firms, the information available from the system is often incomplete. This study focuses on the CBM of systems with identical serial components, where the challenge lies in making maintenance decisions based on partial information from sensor data, including when to perform maintenance and how many spare parts to carry to the maintenance site. Through simulations of periodic systems with identical components, optimal strategies were derived across various scenarios. Additionally, the study explores how changes in system parameters affect the optimal decision points. The findings suggest that spare part selection costs can constitute up to 20% of the total maintenance costs. Moreover, as machinery technology advances, the accuracy of partial information improves, leading to a higher incidence of predictive maintenance and enhanced system predictability. keywords: condition-based maintenance, preventive-maintenance, spare part selection, corrective maintenance, multi-component systemConference Object Maintenance Decision and Spare Part Selection for Multi-component System(Springer Science and Business Media Deutschland GmbH, 2024) Berk Kaya; Oktay Karabağ; Mehmet Murat Fadiloglu; Kaya, Berk; Karabağ, Oktay; Fadıloğlu, Mehmet Murat; N.M. Durakbasa , M.G. GençyılmazDue to the advancement of technology over time higher technology machines are being used in the production and service sectors. Companies suffer great financial losses if these machines stop working due to a breakdown. To avoid these losses maintenance has become increasingly important for companies over time. Condition based maintenance aims to intervene in a system as close to the point of failure as possible using information received from the system. Sensors are used to obtain information about the wear and tear of the machine. However since sensors are costly they are not installed on every machine component but rather on the system. While this reduces costs it also means that we now obtain partial information from the system rather than from each component. In these systems we need to make two types of decisions. The first decision is when to intervene in the system. The second decision is how many spare parts to carry with us once we decide to intervene. We simulated several different experiments for a periodic system composed of identical components and found optimal policies based on the two decisions we made. Our managerial insights indicate that as the number of components in the machine increases the importance of selecting spare parts for the system also increases leading to a tendency to maintain the system as late as possible before the system fails. Moreover in situations where the penalty for maintenance is lower after a failure occurs in optimal policy we maintain later and carry more spare parts during our interventions. © 2024 Elsevier B.V. All rights reserved.Conference Object Citation - Scopus: 1A Simulation Based Analysis for Sewing Lines of Apparel Industry(Springer Science and Business Media Deutschland GmbH, 2023) Berk Kaya; Zeynep Hazal Soyan; Işılay Aydın; Sanemnaz Yurteri; Zilan Gerilakan; Önder Bulut; Burak Özdeş; Can Elhan; Zeynep Rala; Şafak Birol; Birol, Şafak; Yurteri, Sanemnaz; Kaya, Berk; Aydın, Işılay; Bulut, Önder; Gerilakan, Zilan; Soyan, Zeynep Hazal; N.M. Durakbasa , M.G. GençyılmazOne of the frequently encountered problems in the labour-intensive apparel industry is the deviation from the target deadlines. The biggest observed reason for this problem is that the standard operation times and therefore production targets are being defined as deterministic values in the stochastic environment. The statistical studies carried out in this project show that the standard deviation of the operation times is too significant to be ignored. The natural randomness in the performance of the workers and additional factors such as fatigue and learning effect are some of the most important reasons that increase the variability in the system. The project is carried out in conjunction with one of Turkey’s top companies within the apparel sector TYH Tekstil A.Ş. Different policies are applied by the company to dynamically solve the problems encountered during production. In the literature review different simulation-based policy methods for a sample order were examined. However since the company’s sewing line has its unique characteristics the reviewed policies alone were determined not to be suitable for use. This project aims to determine the mentioned randomness parameters by analyzing the day-hour variability of the operation times statistically and provide the company with a tool that will simulate the sewing lines ahead of production using the order-specific inputs and data analysis dynamically analyze and improve the performance of the sewing lines by Tabu search algorithm and visually/verbally report any problematic operations/occasions that may arise and performance improvements made by the decision policies for minimizing deviations from target deadlines. To increase the flexibility of the system and make it dynamic the Python programming language was used. © 2023 Elsevier B.V. All rights reserved.Article Citation - WoS: 6Citation - Scopus: 7Shuttle-Based Storage and Retrieval Systems Designs from Multi-Objective Perspectives: Total Investment Cost- Throughput Rate and Sustainability(MDPI, 2023) Banu Y. Ekren; Berk Kaya; Melis Kucukyasar; Kaya, Berk; Kucukyasar, Melis; Ekren, Banu Y.This paper studies performance comparison of two shuttle-based storage and retrieval system (SBS/RS) configurations developed on flexible or non-flexible travel policies of shuttles in the system. In the non-flexible SBS/RS a shuttle is dedicated to a tier so that it cannot travel out of its dedicated aisle and tier. A lifting mechanism is installed in each aisle to provide vertical travel for loads. In flexible SBS/RS shuttles can travel between tiers by a separate lifting mechanism installed on the other edge point of each aisle. The advantage of that flexible design is that there might be decreased number of shuttles settling in the system compared to the non-flexible design. We simulate the two system configurations and conduct an experimental design for the comparison purpose. Based on the three-performance metrics: total investment cost throughput rate and energy consumption per transaction the results show that mainly the flexible system provides better results which might be considered as future system investment for SBS/RS.
