Endüstri Mühendisliği Bölümü / Department of Industrial Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11413/6819

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Now showing 1 - 20 of 161

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Determining a New Warehouse Location for an Electrical Home Appliances Company
(Springer Science and Business Media Deutschland GmbH, 2024) KIZILKAYA, İLAYDA; KEVSER, TOLGAHAN; OFLUOĞLU, HANDE; ÖLÇÜCÜER, FEYZA; DEMİREL, DUYGUN FATİH
In today’s businesses, supply chain management is a critical factor in terms of efficiency, profitability and cost savings. The success of the supply chain is possible with the right management of the rings such as warehousing and logistics activities. Deficiencies in warehouse and logistics management can lead to inefficiencies and errors in the supply chain, which can have negative effects on business profitability and customer satisfaction. Strategic decisions regarding warehouse locations are vital for cost policies. In this study, a warehouse location selection procedure is proposed for an electrical home appliances company considering the distances to the customers, their transaction volumes, and various other costs. The approach is basically a two-stage facility layout problem that first solves a weighted Euclidean minisum model defined on a continuous plane. Then, four alternative locations that are close to the result obtained in the first step are determined. In addition, two lands owned by the firm are added to the set of alternatives. Next, a p-median (1-median) model is solved and the most suitable warehouse location is determined. Through sensitivity analysis, the changes in the solution are searched for various rent values. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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Improving Quality Control Applications by Increasing Inspection Efficiency and Decreasing Nonconformance Percentage
(Springer Science and Business Media Deutschland GmbH, 2024) YILMAZ, BAŞAK; FIRAT, SENA; CABA, CİHAN; BEŞİR, BERNA; ÜLKÜ, İLAYDA
Quality controls are activities to evaluate the level of conformity of product attributes and optimal quality objectives. When 100% inspection is applied in quality control processes, sampling is used because it causes high costs, long control times and product damage. Acceptance sampling, which is a statistical method, determines whether the lot can be accepted or rejected in line with the tests performed on the samples taken from the lot. The acceptance sampling plan depends on multiple factors such as the level used, the degree of control applied, the lot size, and the acceptable quality level. For this reason, the use of standard sampling plans that increase the validity of quality control operations can be expressed. In this paper, acceptance process applications were studied for a the company that demonstrates textile industry studies. In this the company, the control processes entered the products in the batch of different sizes coming from the regulations used for the contract are applied. To determine the acceptance listening, the execution of the lot, the control measurement dimensions entered first, the reasons for the return of the the company’s four product groups and the AQL reports are reviewed, and the statistical evaluations of the quality controls come to an end. Next steps, using ANSI/ASQ Z-1.4, observations suitable for lot sizes and appropriate acceptance-rejection details were determined and compared with the size and decision points of the the company. Cause-effect diagrams do not take into account the reasons that cause the returns to be made so that the possible reasons for the returns can be examined. Finally, according to the results of the sampling, solutions were found to make the dimensions for these reasons. Cause-effect diagrams do not take into account the reasons that cause the returns, so that possible causes of the returns can be examined. Finally, according to the sampling results, solutions were found for sizing for these reasons. It is recommended to taken 50 samples from lot sizes between 281–500, 80 samples from 501–1200 lot sizes, and 125 samples for lot sizes between 1201 and 3200. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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Cloud-Based AI Role in Intelligent Pharmaceutical Manufacturing Facilities
(Springer Science and Business Media Deutschland GmbH, 2024) DARABSEH, ESRAA; TARHAN, İBRAHİM ETHEM
Cloud-based Artificial Intelligence (AI) brings advanced computing capabilities into manufacturing facilities without capital expenditures. Cloud AI is capable of assisting turn traditional factories into intelligent factories at low cost. The disruptive innovation of cloud and artificial intelligence equipment in smart factory management leads to increased economic growth and the development of a production pipeline [1]. This article investigates how adopting Cloud-based AI services in intelligent pharmaceutical manufacturing facilities affects the factory’s internal process management. The article uses SWOT/PESTEL analysis to evaluate internal and external factors affecting such facilities based on a case study. In addition, the article uses Minitab to perform linear regression analysis on the case study to determine the outcomes of adopting Cloud-based AI in such factories. The article finds a positive effect of adopting modern technologies, such as Cloud-based AI, on creating a highly efficient production environment, reducing costs, and increasing revenues. However, further investigation is needed to conduct similar research on other pharmaceutical manufacturing facilities of different sizes to understand improved how such implementation affects these facilities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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A Quality Value Stream Mapping Study in a Knitwear Manufacturer
(Springer Science and Business Media Deutschland GmbH, 2024) GERGİN, ZEYNEP; KILINÇ, ARDA SEDEN; AKSU, OZAN İBRAHİM; AKALIN, ARDA BURAK; ALBAYRAK, ABDÜLBAKİ; GÜNEŞ, SALİH
The ready-made clothing industry is one of the sectors that has a high share in export and has a direct impact on our country's economy. Today, the increase in production diversity provides consumers with the chance to choose between alternatives and creates competitive environment for businesses that strive to meet consumer needs at the highest level. In other words, being able to quickly meet the customer's desired quality product at the desired price is as important as producing the product. In this case, businesses are faced with a production process that requires low cost, in which the variety of models and the quality of goods increased, by using the existing resources of the enterprises in the most efficient and flexible way. With this motivation, a case study is implemented for Narin Triko which has an important export market share. Great emphasis is placed on quality control procedures in the company as the customers are global brands, and this leads to more handling of a product and additional number of quality controls. While this approach ensures a higher degree of quality, it also slows down production, requires extra labour, increases lead times and generates more waste. Consequently, this study aims to identify the 7 waste items of lean production and make suggestions to reduce as appropriate. A newly proposed method called Quality Value Stream Mapping (QVSM) that integrates quality focus on Value Stream Mapping (VSM) method is applied. QVSM is a model created to address, analyse, visualize, and evaluate specific quality-related problems. It is expected to suggest some changes in the way the processes work and to increase the product quality by determining the process steps that can be improved regarding the reduction of the wastes like, over processing, overproduction, waiting times, work in process, transportations, scrap, rework and inspection costs. The study started by observing and analysing the production process to collect data on flow of information, process and material, and lean wastes. Then the data are processed for drawing the Current State QVSM that integrates quality-related processes such as quality inspections, rework processes and scrapping processes to the VSM showing the lean wastes. Finally, analysing the QVSM and identifying improvements led to drawing the Future State QVSM and proposing the improvement opportunities. Proposed improvements reduced the Non-Value Adding time 42%. Thus, the new lead time would be 13% less than the previous lead time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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The Impact of Value Engineering on Material Selection: An Example from the Construction Industry
(Springer Science and Business Media Deutschland GmbH, 2024) TARHAN, İBRAHİM ETHEM; QUFFA, BARAA
The urgent need for Value Engineering has arisen due to the enormous expenditure in the construction industry, which could be reduced by up to 25%. This substantial spending is often accompanied by poor quality, leading to a constant need for reconstruction and maintenance. The methods and concepts of Value Engineering can be applied to address this issue. By using Value Engineering, solutions can be created that fulfil the same functional purpose at a lower cost while maintaining high quality. This can be achieved through an analytical study using a specific approach conducted by a multidisciplinary team to identify and classify the functions that the project performs. Profound methods can then be utilized to find innovative alternatives without compromising the basic requirements and quality. This research is dedicated to demonstrating the methodology of Value Engineering while highlighting its impact on construction projects through a case study: Magrabi Offices in Saudi Arabia. This paper used an organized multidisciplinary methodology to identify the project’s main and secondary functions, then utilized Pareto’s law to identify higher-cost materials. It was proven that finding low-cost equivalent materials could reduce the total price by 23.13%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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An Excel-Based Stock Management System for a Leather Label Manufacturer
(Springer Science and Business Media Deutschland GmbH, 2024) UÇUCU, EMİNE; ERASLAN, FATMA BEYZA; KAYMAKLI, ZEYNEB NUR; EMİR, OĞUZ; AKTİN, AYŞE TÜLİN
This paper presents a proposal for an Excel-based digital inventory tracking system to address the operational challenges faced by a leather label manufacturer located in Istanbul, Turkey. The company is currently reliant on manual stock keeping and tracking methods for its leather labels and raw materials, resulting in significant functional difficulties due to the absence of a systematic and efficient inventory tracking system. The proposed system aims to enhance overall productivity and decision-making processes within the company. By implementing the new tracking system, the company can overcome the limitations of manual stock management, leading to improved efficiency and organization in inventory control. Furthermore, the installation of a barcode system is suggested to augment the tracking system’s capabilities, and the profitability of the proposed system is evaluated using three different financial analysis methods. This research contributes to the advancement of inventory management practices and provides valuable insights into the potential benefits of adopting digital solutions for stock control in the leather label industry. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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Understanding Coopetition Dynamics in Manufacturing Value Networks: A System Dynamics Based Causal Loop Diagram (CLD) Modelling Approach
(Springer Science and Business Media Deutschland GmbH, 2024) Konyalioglu, Aziz Kemal; Ates, Aylin; Paton, Steve; APAYDIN, TUĞÇE
The concept of “coopetition” in manufacturing value networks involves firms engaging in both collaboration and competition simultaneously This approach, while aiming to leverage the benefits of both, inherently introduces a paradox concerning value creation and capture. Within a value network, coopetition involves various entities such as suppliers, distributors, subcontractors, and even competitors working together to enhance overall value. Despite a surge in research on coopetition, there remains a disjointed understanding, with limited exploration of its dynamics within manufacturing contexts. To address this gap, our study constructs a system dynamics model using causal loop diagrams (CLD) derived from an in-depth literature review within the manufacturing sector. Our aim is to comprehensively elucidate the factors influencing co-opetitive relationships and dynamics in manufacturing value networks and business ecosystems. Furthermore, existing literature emphasizes the need for a multifaceted perspective on coopetition in manufacturing. Our model, developed through consultation of extensive manufacturing and business literature and CLD application, identifies key factors driving coopetition dynamics in manufacturing and business ecosystem contexts. It represents the first comprehensive content analysis of coopetition dynamics within manufacturing and business ecosystems, serving as a valuable resource for scholars and professionals in the manufacturing and management field. By examining interconnected elements in a causal loop framework specific to manufacturing and business ecosystems, our study reveals how dynamic factors influence co-opetitive outcomes in these ecosystems. We explore various manufacturing-related aspects, such as supply chain dynamics in coopetition, technological innovations, and market dynamics, all impacting co-opetitive interactions. This comprehensive approach fills a literature gap, offering insights into critical factors affecting the co-opetitive process within manufacturing and business value networks. Our study’s methodology, employing causal loop diagrams tailored to the manufacturing domain, stands out in the literature, providing a unique perspective on coopetition dynamics within manufacturing and management contexts. © IFIP International Federation for Information Processing 2024.
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Examining the Effects of Forest Fires: A Framework for Integrating System Dynamics and Remote Sensing Approaches
(IGI Global, 2024) Eriş, Müjgan Bilge; DEMİREL, DUYGUN FATİH; Sezer, Eylül Damla Gönül
Forest fires have been a major concern for many countries over an extended period of time due to natural and human induced factors. In recent years, detection of forest fires has progressively shifted toward advanced technologies where the remote sensing approaches are fully operational. To enhance fire management strategies, it is crucial to gain a comprehensive understanding of the fire dynamics and its consequences on the environment, operational sources, and economic sectors. Therefore, this chapter develops an integrated framework to predict and analyze the effects of forest fires by using system dynamics approach and remote sensing technology, ultimately leading to the establishment of a conceptual model and conclusive insights. © 2024, IGI Global. All rights reserved.
Open Access
Marmara Denizi'nde Görülen Müsilajın Ortadan Kaldırılmasına Yönelik Politikaların Sistem Dinamiği İle İncelenmesi
(Kahramanmaraş Sütçü İmam Üniversitesi, 2024) DEMİREL, DUYGUN FATİH; Sezer, Eylül Damla Gönül
Jeopolitik, ekonomik ve ekolojik açıdan önemli bir yeri olan Marmara Denizi’nde yaşanan kirlilikteki artış son yıllarda farklı çevrelerin dikkatini çekmekle birlikte özellikle 2020-2021 yıllarında yaşanan müsilaj problemi sorunun ciddiyetini ortaya koymuştur. Literatürde iklim değişikliği, topografik yapı, artan nüfus, sanayileşme, tarım aktiviteleri, atıksu arıtma sistemlerinde kullanılan teknolojinin yetersizliği, vb. etmenlerin müsilaj oluşumunu tetiklediği öne sürülmektedir. Müsilaj sorununun çözümüne yönelik çeşitli stratejiler öne sunulmakla birlikte bu stratejilerin ne gibi sonuçlar doğuracağına ilişkin sayısal bir çalışma bulunmamaktadır. Bu amaçla bu makalede Marmara Denizi’nde görülen müsilaj olgusunu modellemek ve sorunu çözmeye yönelik politikaların etkilerini incelemek üzere sistem dinamiği yaklaşımına dayalı bir benzetim modeli sunulmaktadır. Önerilen model müsilaja neden olan temel mekanizmalar ile müsilajın ekonomik etkilerini temsil etmekte olup müsilaj problemini ortadan kaldırmaya yönelik çeşitli stratejilerin etkinlik seviyelerini farklı senaryolarla ortaya koymaktadır. Elde edilen bulgulara göre ileri biyolojik arıtma seviyelerinin arttırılması, tarım ve hayvancılık aktiviteleri için alınacak önlemler ve bölge nüfus artışına karşı alınacak önlemlerin bir arada uygulanmasının Marmara Denizindeki müsilaj riskini sınırlandıracağı sonucuna varılmaktadır.
Open Access
Sürdürülebilirlik ve Yenilikçi Teknolojiler Sempozyumu Bildiriler Kitabı, (Özet / Tam Metin)
(İstanbul Kültür Üniversitesi, 2024) Kolektif; ed., Ceren Aycan Gürel Hoşhanlı; ed., Oğuz Emir
Open Access
Triggering Corporate Sustainable Performance in Construction Sector through Green Training: Moderating Effect of Barrier in Construction Management
(Yıldız Teknik Üniversitesi Rektörlüğü, 2023) WARIS, IMRAN; ÜLKÜ, İLAYDA
Construction barrier plays a significant but negative role-play between green training and corporate sustainability performance due to limited resources. The research question in this study is to explore the relationship between green training and sustainable performance in the construction industry, while also considering the moderating role of construction barriers. This study gives extensive knowledge of green training and corporate sustainability performance. Data is obtained from 225 employees using a convenience sampling technique from the construction sector. The research employed SPSS/PROCESS and follows a cross-sectional research design. Study findings show green training is an antecedent of the sustainable performance of the construction sector. The result shows that Green training significantly and positive role-play in sustainable performance. Person-organization fit theory covers the whole phenomenon. That focuses on productivity, performance, and personal well-being. Under P-O fit theory results are showing the compatibility between a person and an organization where they are doing work. This study's results highlight the green training that transforms the em- employee’s mindset towards corporate sustainable performance. In the future, need longitudinal studies that will be more acceptable. This study provides insights to the managers, policymakers, and practitioners of sustainable environment and performance. The current study will help economies in the developing world, such as Pakistan.
Open Access
The Impact of Perceived COVID-19 Threat and Death Anxiety on Buying Behavior Among Academics: A Comparison Between Türkiye and Northern European Countries
(Türk Kooperatifçilik Kurumu, 2023) Turna, Gülçin Bilgin; Pekmezci, Halil; IŞIK, OKAY
Academics, one of the occupational groups exposed to isolation in the COVID-19 epidemic, tried to adapt to the remote working regulations by not being able to maintain the social environment they were accustomed to in universities. This study aimed to examine the impact of perceived COVID-19 threat and death anxiety on revenge buying behavior by comparing academics who work in Türkiye and Northern Europe (the United Kingdom, the Netherlands, and Norway). “Revenge buying” is a term popularized in the marketing field during the global COVID-19 quarantines. It refers to the surge in shopping desire observed after the lifting of pandemic-related lockdown measures. Data was collected online by using three scales: the “Perceived COVID-19 Threat Scale”, “Templer’s Death Anxiety Scale” and “Revenge Buying Behavior Scale”. The sample consisted of total 327 academics: 163 from Türkiye (TR) and 164 from Northern Europe (NE). Structural Equation Modelling (SEM) was adopted for the analyses. The results showed that academics in NE were more prone to revenge buying behavior than TR. As the perceived threat of COVID-19 and death anxiety increased, it was determined that academics working in both TR and NE have tendencies for revenge buying. However, there was insufficient evidence to support the mediating role of death anxiety in the relationship between perceived COVID-19 threat and revenge buying behavior. In this interdisciplinary study, statistically significant differences identified based on the demographic characteristics of academics working in TR and NE have also been indicated.
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Examining the Impacts of Military Expenditures on Economic Productivity: A System Dynamics Approach
(SAGE Publications Ltd., 2023) Damla Gönül-Sezer, Eylül; DEMİREL, DUYGUN FATİH
The relationship between military expenditures and economic productivity has taken the attention of many researchers and there exist an important number of studies approaching the topic through several techniques. However, there is no consensus among the scholars whether military expenditures trigger economic growth, productivity, and other macroeconomic indicators. Such arguments are mainly due to unclear results obtained from the existing studies, in which the complex relationships between military expenditures and macroeconomics are not fully incorporated. Considering the bidirectional and nonlinear relationships among macroeconomic indicators and complex feedback mechanisms, a system dynamics (SD) model for examining the impacts of military expenditures on economic productivity in Turkey is proposed. The proposed SD model aims to reflect the complex environment surrounding the military spending–economic productivity nexus and to analyze the feedback structures that lead to miscellaneous consequences with delays. A stock–flow model is developed to represent the complex nonlinear relationships and causalities between the variables. Data from SIPRI, the World Bank, and several local statistical sources covering the years 2009–2018 are utilized to simulate the existing case, warfare in neighbors, economic shrinkage scenarios, and the combination of the latter two. The results obtained from the scenarios suggest that short fixes such as importing military products instead of national investments give rise to chronic issues like continual dependence on foreign supply, hence, leading to decrease in overall economic growth. To the best of our knowledge, this is the first attempt to integrate SD methodology with military expenditure and economic productivity analysis.
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An Integrated Assessment of Food Waste Model Through Intuitionistic Fuzzy Cognitive Maps
(Elsevier, 2023) EMİR, OĞUZ; Ekici, Şule Önsel
In recent years, the waste management field has received substantial attention from policymakers, organizations, academics, and researchers due to increased focus on sustainability and carbon footprint reduction as well as concerns around rapid depletion of natural resources, public health, and environmental impact. Studies on food waste management have become especially important given the dramatic growth of the world's population and global hunger and malnutrition crisis. Considering the fact that one-third of the world's food supply is wasted or lost annually while hundreds of millions of people are living with food insecurity, it is easy to understand the importance of research studying appropriate food waste management actions for sustainability. Since the subject of food waste involves complicated linkages, the determination of a suitable model is pivotal. Integrated assessment models (IAMs) have been commonly used to uncover hidden patterns and present insights to policymakers. Furthermore, these models are well-designed to integrate data, information, and multidisciplinary knowledge into a single framework. This project presents a Fuzzy Cognitive Map (FCM) extended with intuitionistic fuzzy sets using the documentary coding method. This intuitionistic FCM (iFCM) is used to analyze the primary factors, explore the interactions between food waste factors, and prioritize some policies to reduce food waste by incorporating hesitancy weight factors representing the lack of information. Then several what-if scenario analyses are generated to review the interrelationships between factors in the developed model and facilitate a decision-making process for researchers. Eventually, it is concluded that food waste reduction is achievable with the implementation of the right policies, and this also improves the other concepts such as the intention not to food waste, shopping routines, and planning routines.
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Forecasting of Turkey's Total Electricity Consumption in Sectoral Bases Using Machine Learning Algorithms
(Institute of Electrical and Electronics Engineers Inc., 2022) HAJJAR, MHD KHAIR; ÜLKÜ, İLAYDA
Electrical energy is a milestone in the economic growth of each country. This study forecasts the sectoral and total electricity consumption in Turkey until the year 2050. This study, utilize two distinct time series forecasting methods namely Multilayer Perceptron (MLP) and Sequential Minimal Optimization (SMO) as a model to generate the forecasting formulas. The sectoral and total electricity consumption for Turkey from the year 1970 to 2020 was obtained from the Turkish Statistical Institute and fed to the models to forecast the upcoming years. The two models were evaluated and compared using determination coefficient R2 and mean absolute percentage error MAPE. It is found that MLP performed better in forecasting the commercial, governmental, illumination and other sectors and SMO performed better in forecasting the industrial and household sectors alongside the total electricity consumption. © 2022 IEEE.
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Global Impact of the Pandemic on Education: A Study of Natural Language Processing
(Institute of Electrical and Electronics Engineers Inc., 2022) AYAZ, TEOMAN BERKAY; USLU, MUHAMMED SAFA; AĞCABAY, İBRAHİM; AHMED, FARUK; KORKMAZ, ÖMER FARUK; KÜREKSİZ, MESUT; ULUÇAM, EMRE; YILDIRIM, ELİF; KOCAÇINAR, BÜŞRA; AKBULUT, FATMA PATLAR
School closures due to the Covid-19 pandemic have changed education forever and we have witnessed the rise of online learning platforms. The education units of the countries made great efforts to adapt to this new order. The expanding, quick spread of the virus and careful steps have prompted the quest for reasonable choices for continuing education to guarantee students get appropriate education and are not impacted logically or mentally. Different methods were attempted to understand how students were affected by this big change. In addition to the significance of traditional surveys and consulting services, the utilization of social media analysis is used as a supportive approach. This paper analyzes the feedback of students on social media via tweets. Deep sentiment analysis is employed to identify embedded emotions such as negative, neutral, and positive. We also aimed to classify irrelevant tweets as the fourth category. Our experiments showed that the tweets are mostly biased toward negative emotions. © 2022 IEEE.
Open Access
Prediction of University Students' Subjective Well-Being with Sleep and Physical Activity Data using Classification Algorithms
(Elsevier B.V., 2022) KILIÇ, AKİF CAN; Karakuş, Ahmet; Alptekin, Emre
Daily activities affect mental health. One of the most used scales is "subjective well-being (SWB)", which is a self-reported questionnaire. This study aimed to predict SWBs using step count, heart rate and sleep duration data from sensors instead of questionnaires. NetHealth data from the University of Notre Dame1 has been used. Attributes included average daily steps, average heart rate, heartbeat standard deviation, average sleep duration, and sleep duration deviation. Preprocessing, processing, classification, and evaluation followed. Naive Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Ensemble classifiers were used. Performance metrics include accuracy, precision, recall, F1-Score, and ROC (Receiver Operating Characteristic) curves. Model accuracy was 62%. This indicates that machine learning could be beneficial in detecting SWB levels using sensor data. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022).
Open Access
A New Organizational Agility Assessment Approach Applied in the Logistics Industry
(Melih Topaloğlu, 2022) GERGİN, ZEYNEP; AK, MEHMET MİRAÇ; ÇOLAK, EREN; KAYALAR, MUSTAFA; YAVAŞOĞLU, CAN DENİZ
Purpose – Today, the variable and numerous demands from customers, changing market conditions and the depletion of resources have made agile working methods more necessary than in the past. In this study, it is aimed to increase the awareness of the concept of agility in companies and to accelerate the agile transformation processes. Design/Methodology/Approach – In this research study, a new measurement scale is developed to assess the current agility levels of the companies operating in logistics sector. The new instrument measures the agility levels of seven business processes for eight components of agility and an aggregated level for company agility score is identified. The detailed questionnaire, which is composed of 51 questions, is applied to 4 companies operating in the logistics sector, differing in size and structure, and their current agility level is evaluated. The weights for business processes and agility component are also defined sector based via Analytic Hierarchy Process (AHP) during the calculation of the final agility score. Due to the detailed structure of the tool, the results gave opportunity for a detailed analysis of the strengths and weaknesses of the business processes. Hence, custom recommendations could be made in order to improve the agility level of the company. Findings – It is seen that there are common elements like technology and innovation, that are highly effective on agility for every company studied, as well as there are prior elements to be focused that differ with the size and structure of the company. It is also concluded that companies need to be more agile as their operation size increases and they can meet these needs with managers who have an innovative perspective. Discussion – This study has developed its own methodology, its own research tool and recommendations, unlike previous studies in the field of agility. Aiming to bring a new link to the academic chain with these features, this project can shed light on more diverse studies in the field of agility.
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Analyzing the Wastewater Treatment Facility Location/Network Design Problem via System Dynamics: Antalya, Turkey Case
(Academic Press Ltd. - Elsevier Science Ltd., 2022) DEMİREL, DUYGUN FATİH; Gönül-Sezer, Eylül Damla; Pehlivan, Seyda Alperen
Wastewater treatment facility location selection and network design issues have become attractive topics in the field of wastewater management due to increasing human population, resource scarcity, environmental concerns, and rise of necessity for sustainable solutions for future policy designs. Especially in areas where the demand for wastewater treatment increases dramatically over the years because of reasons such as high migration levels, rapid industrialization, and tourism activities, the problem turns out to be more critical and dynamic. The existing studies try to deal with the issue through mathematical modeling approaches based on optimization perspectives, which require significant computational effort. In this study, an alternative approach based on system dynamics (SD) method is proposed to examine the complex dynamic and nonlinear structure of waste-water treatment facility location selection and network design problems. The proposed SD simulation model is designed for a densely populated industrial and tourism spot, the city of Antalya, located on the Mediterranean coast of Turkey. The model is capable of determining where and when to build a new wastewater treatment facility as well as generating the generic wastewater network structure to be built for the five districts situated in the city center based on cost issues for 2015-2040 period. In addition, the impacts of demand level changes for wastewater treatment due to population variations are analyzed via several scenarios to help decision makers to develop sustainable and cost-efficient management policies. Although SD is a frequently utilized approach in the water/wastewater management arena, to the best of our knowledge, this study is the first attempt to examine the complex and dynamic nature of wastewater treatment facility location selection and network design problems through SD approach.
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Forecasting Greenhouse Gas Emissions Based on Different Machine Learning Algorithms
(Springer International Publishing, 2022) ÜLKÜ, İLAYDA; Ülkü, Eyüp Emre
With the increase in greenhouse gas emissions, climate change is occurring in the atmosphere. Although the energy production for Turkey is increased at a high rate, the greenhouse gas emissions are still high currently. Problems that seem to be very complex can be predicted with different algorithms without difficulty. Due to fact that artificial intelligence is often included in the studies to evaluate the solution performance and make comparisons with the obtained solutions. In this study, machine learning algorithms are used to compare and predict greenhouse gas emissions. Carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), and fluorinated gases (F-gases) are considered direct greenhouse gases originating from the agriculture and waste sectors, energy, industrial processes, and product use, within the scope of greenhouse gas emission statistics. Compared to different machine learning methods, support vector machines can be considered an advantageous estimation method since they can generalize more details. On the other hand, the artificial neural network algorithm is one of the most commonly used machine learning algorithms in terms of classification, optimization, estimation, regression, and pattern tracking. From this point of view, this study aims to predict greenhouse gas emissions using artificial neural network algorithms and support vector machines by estimating CO2, CH4, N2O, and F-gases from greenhouse gases. The data set was obtained from the Turkish Statistical Institute and the years are included between 1990 and 2019. All analyzes were performed using MATLAB version 2019b software.

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