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Öğe A Fuzzy Analytic Hierarchy Process Model For Supplier Selection And A Case Study(Kırıkkale Üniversitesi, 2011) Aktepe, Adnan; Ersoz, SuleymanIn today’s competitive manufacturing and service industries decision making is a critical process. Supply chain management is a network of businesses and in this network there are several critical decision making problems. One of them is supplier selection decision. Supplier selection is a multi-criteria decision making problem and a fuzzy decision making model is proposed to this problem area in supply chain management. The extent analysis method and integral value calculation is used in the study for computing the priority weights of criteria and alternatives. In addition, a case study is added to the study.Öğe A model proposal for measuring service quality of eduaction with fuzzy rule-based approach and fuzzy ranking and an application(Ios Press, 2023) Altinsoy, Ufuk; Aktepe, Adnan; Ersoz, SuleymanIn today's understanding, the universities are considered as service providers besides their institutional functions. Because the universities shape the future of the country via the services they provide, it is a necessity that their service quality must be assessed by using scientific analyses, and their service quality must be improved based on such scientific findings. The Generation Z, whose members are currently receiving university education carries unique features that distinguish them from the previous generations. When this fact is considered, it is understood that the constant research and monitoring of the learning environment of the Generation Z is important. In this study, as a result of a detailed literature search, a scale consisting of 7 dimensions and 36 indicators was developed in order to measure the higher education service quality of the Z generation. The validity and reliability tests of this scale are completed via the convergent and divergent validity analyses, Exploratory Factor Analysis (EFA), and Confirmatory Factor Analysis (CFA). Because the answers provided to the surveys reflect the personal evaluation of the participants, the Fuzzy Logic is employed, and the study is conducted by using the fuzzy modelling and fuzzy ranking. As a result of this study, the General Satisfaction Index is created, and improving recommendations are carried out based on the scores.Öğe A model proposal for movie theater service performance index (MTSPI) calculation with structural equation modeling and application(Gazi Univ, 2024) Özek, Kübra İpek; Aktepe, Adnan; Ersöz, SüleymanIn this research, the objective is to create a performance index for movie theater services. In order to create the index, firstly the conceptual model for movie theater services was created. Secondly, physical evidence, social benefit, customer satisfaction and ambiance are determined as latent variables and verified with Confirmatory Factor Analysis (CFA). The relationships among latent variables are determined using the Structural Equation Model (SEM). Then Entertainment Performance Index is developed and calculated by using weights and scores of latent variables for movie theater services. Entertainment Performance Index is used for determining the level of performance and for proposing suggestions for decreasing the level of service quality gaps in movie theater services sector. In addition, satisfaction levels for different customer groups are compared according to the frequency of benefiting from revenue management applications. The ambiance dimension, which is about feeling yourself in the script and feeling the emotions more intensely in the movie theater atmosphere, was developed in this study.Öğe A Multi-Agent Reinforcement Learning Approach to the Dynamic Job Shop Scheduling Problem(Mdpi, 2023) Inal, Ali Firat; Sel, Cagri; Aktepe, Adnan; Turker, Ahmet Kursad; Ersoz, SuleymanIn a production environment, scheduling decides job and machine allocations and the operation sequence. In a job shop production system, the wide variety of jobs, complex routes, and real-life events becomes challenging for scheduling activities. New, unexpected events disrupt the production schedule and require dynamic scheduling updates to the production schedule on an event-based basis. To solve the dynamic scheduling problem, we propose a multi-agent system with reinforcement learning aimed at the minimization of tardiness and flow time to improve the dynamic scheduling techniques. The performance of the proposed multi-agent system is compared with the first-in-first-out, shortest processing time, and earliest due date dispatching rules in terms of the minimization of tardy jobs, mean tardiness, maximum tardiness, mean earliness, maximum earliness, mean flow time, maximum flow time, work in process, and makespan. Five scenarios are generated with different arrival intervals of the jobs to the job shop production system. The results of the experiments, performed for the 3 x 3, 5 x 5, and 10 x 10 problem sizes, show that our multi-agent system overperforms compared to the dispatching rules as the workload of the job shop increases. Under a heavy workload, the proposed multi-agent system gives the best results for five performance criteria, which are the proportion of tardy jobs, mean tardiness, maximum tardiness, mean flow time, and maximum flow time.Öğe A Systematic Literature Review of the Predictive Maintenance from Transportation Systems Aspect(Mdpi, 2022) Ersoz, Olcay Ozge; Inal, Ali Firat; Aktepe, Adnan; Turker, Ahmet Kursad; Ersoz, SuleymanWith the rapid progress of network technologies and sensors, monitoring the sensor data such as pressure, temperature, current, vibration and other electrical, mechanical and chemical variables has become much more significant. With the arrival of Big Data and artificial intelligence (AI), sophisticated solutions can be developed to prevent failures and predict the equipment's remaining useful life (RUL). These techniques allow for taking maintenance actions with haste and precision. Accordingly, this study provides a systematic literature review (SLR) of the predictive maintenance (PdM) techniques in transportation systems. The main focus of this study is the literature covering PdM in the motor vehicles' industry in the last 5 years. A total of 52 studies were included in the SLR and examined in detail within the scope of our research questions. We provided a summary on statistical, stochastic and AI approaches for PdM applications and their goals, methods, findings, challenges and opportunities. In addition, this study encourages future research by indicating the areas that have not yet been studied in the PdM literature.Öğe An Application on Analysis of Mask Production Factors with Clustering Approach(Kırıkkale Üniversitesi, 2023) Tebrizcik, Semra; Ersöz, Süleyman; Aktepe, AdnanWith the development of technology, large databases are becoming more accessible. Today, it is possible to use large databases in many fields. By using data kept in databases and data mining approaches, meaningful information and rules are discovered. Thus, information discoveries are made that will be useful for businesses. In this study, the production data of a factory producing surgical (medical) masks was used. Clustering analyzes of the variables that are effective in the production of faulty or error-free masks in the quality control stage were made with the Two Step method and the properties of the resulting clusters were compared. The most effective variables in cluster partitioning are; It has been observed that the amount of speed used in the creation of the mask body, the type of fabric of the middle layer of the mask body consisting of 3 layers, and the amount of ultrasonic heat used to create the pleats on the body. The information obtained to improve the performance of production activities will be used to improve the process.Öğe An Expert System Approach For High School Type Selection(Gazi Univ, 2011) Ersoz, Suleyman; Aktepe, AdnanAn expert system is a computer program that imitates the procedures by which experts solve problems. This paper describes an expert system application which provides advice to primary school students who are seeking assistance in determining high school type. The system gathers information about student grade point average (GPA), centralized exam score, personality type and socio-economic factors. It assesses student qualifications for seven different school types in Turkey. The expert system recommends a school type for the students and produces a short report explaining the reasons of recommendation. Student GPA and centralized exam score are considered as technical criteria. In addition, social and socio-economic factors such as personality type, parental involvement etc.affecting the decision process are also considered and included in the model.Öğe An application of data envelopment analytic network process (DEANP) in quality function deployment (QFD)(Gazi Univ, Fac Engineering Architecture, 2011) Ersoez, Sueleyman; Aktepe, AdnanIn this paper a solution method is proposed for emphasizing the importance of costumer needs at the starting of Quality Function Deployment (QFD) application when there are multi costumer groups. Data Envelopment Analysis (DEA) steps are added to an algorithm in which an Analytic Network Process (ANP) approach is used in QFD. The need for adding DEA steps is determining the efficient customer requirements when there are multi customer groups. This solution approach is called DEANP which aggregates data DEA to ANP. The relative importance values of product technical requirements are calculated with this algorithm and application is performed at a manufacturer of white goods company in Turkey. The fact that using DEANP instead of ANP produced more powerful solutions is also confirmed by marketing specialists.Öğe Application of Fuzzy Quality Function Deployment Model, Group Decision Making and Choquet Integral to Improve Service Quality in Engineering Education(Tempus Publications, 2019) Aktepe, AdnanThis paper considers ways to increase service quality levels at engineering programs and actions to be taken for accomplishing this. The aim of this paper is to develop and implement a Quality Function Deployment (QED) model for engineering programs in Turkey. The research determines the most important technical requirements based on considering Voice of the Student (VOS), which is measured with a Service Quality (SERVQUAL) application-based measurement model. The students' responses to SERVQUAL survey are considered by a group decision-making approach. Group decision-making approach is used to attach importance to the ideas of students. The Choquet integral as an aggregation operator is used firstly for aggregating the weights of each response in order to determine the weight of each dimension of SERVQUAL application and secondly for aggregating the SERVQUAL weights and relationship matrix. Finally key factors for increasing qualified and sustainable education are proposed.Öğe Backpropagation Neural Network Applications for a Welding Process Control Problem(Springer-Verlag Berlin, 2012) Aktepe, Adnan; Ersoz, Suleyman; Luy, MuratThe aim of this study is to develop predictive Artificial Neural Network (ANN) models for welding process control of a strategic product (155 mm. artillery ammunition) in armed forces' inventories. The critical process about the production of product is the welding process. In this process, a rotating band is welded to the body of ammunition. This is a multi-input, multi-output process. In order to tackle problems in the welding process 2 different ANN models have been developed in this study. Model 1 is a Backpropagation Neural Network (BPNN) application used for classification of defective and defect-free products. Model 2 is a reverse BPNN application used for predicting input parameters given output values. In addition, with the help of models developed mean values of best values of some input parameters are found for a defect-free weld operation.Öğe Bulanık çok ölçütlü karar verme yöntemleriyle bir toplam performans ölçüm modeli'nin kurulması ve uygulanması(Kırıkkale Üniversitesi, 2011) Aktepe, Adnan; Ersöz, SüleymanArtan rekabet, küreselleşme ve pazar koşullarının ağırlaşmasıyla performans yönetimi özellikle son yıllarda İnsan Kaynakları Yönetimi'nde ön plana çıkan konulardan biri haline gelmiştir. Etkin bir performans yönetimi bütün işletme faaliyetlerinin hedeflere ulaşma derecesinin doğru bir biçimde ölçülmesi ve değerlendirilmesine bağlıdır. İlk uygulamaları sadece finansal raporlamalardan oluşan toplam performans ölçüm modelleri son yıllarda diğer boyutların da dâhil edilmesiyle çok yönlü olarak ele alınmaya başlanmıştır. Bu çalışmada da finans, üretim, müşteri, süreç geliştirme ve öğrenme-gelişme boyutlarından oluşan çok boyutlu bir toplam performans ölçüm modeli geliştirilmiştir. Her bir boyutta verimlilik, etkenlik ve karlılığı ölçen performans göstergeleri tanımlanmıştır. Performans göstergelerinin yüzde önem dereceleri DEMATEL ve bulanık ANP yöntemlerinin bütünleşik kullanımı ile geliştirilen algoritma ile belirlenmiştir. Performans skorları performans göstergelerinin yüzde önem dereceleri ve performans değerlerinin çarpımıyla elde edilmiştir. Geliştirilen model ile işletmenin toplam performansı ölçülebilmekte ve her bir boyuttaki süreçlerin performans değerlendirmesi yapılabilmektedir. Çalışmada ayrıca İstanbul'da faaliyet gösteren bir üretim işletmesinde uygulama yapılmış ve sonuçlar tartışılmıştır.Öğe Calculation of Efficiency Rate of Lean Manufacturing Techniques in a Casting Factory with Fuzzy Logic Approach(Springer Science and Business Media Deutschland GmbH, 2024) Coskun, Zeynep; Aktepe, Adnan; Ersöz, Süleyman; Mangan, Ayşe Gül; Kuruoğlu, UğurSectoral growth is increasing day by day and the competition market is growing with it. At the same time, customer awareness is also increasing. As customer awareness increases, the quality of service provided should also increase. One of the ways that companies will apply in order to maintain their existence in this competitive environment and to prevent customer loss is to make the lean manufacturing philosophy a corporate culture. It is a production approach that does not contain any unnecessary elements in the lean manufacturing structure, minimizes waste and aims to increase efficiency in production. When moving to the lean manufacturing philosophy, it is of great importance for companies to draw a correct road map. This study was applied to the product/product group produced in a foundry. Value stream mapping (VSM), which is one of the lean manufacturing techniques for the determined product/product group, was made and the current situation value stream map was created. With value stream mapping, bottlenecks and losses in the process were determined and a future situation value stream map was created. Lean manufacturing techniques were applied at these determined points, problems were eliminated and productivity increase was achieved in production. Fuzzy logic was used to clearly determine the productivity increase. Fuzzy logic creates numerical models by imitating the human mind many vague, non-numerically expressed terms that we use daily. With fuzzy logic, the efficiency rate was modeled numerically and the contribution of the lean manufacturing techniques applied to productivity was determined. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Öğe Creating Alternative Layout Plans with Simulated Annealing and Data Mining(Ieee, 2017) Kokoc, Melda; Aktepe, Adnan; Ersoz, SuleymanWhen studies in literature are examined, it is seen that different approaches have been used to solve facility layout problems. The relationship between departments in layout is always important. In this study, data mining technique is used for analyzing relations among departments and then association rules are obtained. Determining closeness relationships between the departments in facility are often ambiguous and require expert opinions. In such cases, a fuzzy component emerges in the facility layout problem. Hence, fuzzy logic is widely used to address ambiguous problems. Association rules is converted by using defuzzification approach to crisp values used facility layout problem solution in this study. Facility layout problems are considered to be NP-Hard (Nondeterministic-Polynomial-Hard) optimization problems. That is, definite solution approaches are limited in solving large-scale problem examples. For heuristic approaches are frequently used to improve the layout, simulated annealing approach is used in this study. To improve facility layout planning, simulated annealing approach is carried out via code written in Visual Basic 2012. In conclusion, 17% improvement is achieved with alternative layout plan obtained.Öğe Customer satisfaction and loyalty analysis with classification algorithms and Structural Equation Modeling(Pergamon-Elsevier Science Ltd, 2015) Aktepe, Adnan; Ersoz, Suleyman; Toklu, BilalBusinesses can maintain their effectiveness as long as they have satisfied and loyal customers. Customer relationship management provides significant advantages for companies especially in gaining competitiveness. In order to reach these objectives primarily companies need to identify and analyze their customers. In this respect, effective communication and commitment to customers and changing market conditions is of great importance to increase the level of satisfaction and loyalty. To evaluate this situation, level of customer satisfaction and loyalty should be measured correctly with a comprehensive approach. In this study, customers are investigated in 4 main groups according to their level of satisfaction and loyalty with a criteria and group based analysis with a new method. We use classification algorithms in WEKA programming software and Structural Equation Modeling (SEM) with LISREL tools together to analyze the effect of each satisfaction and loyalty criteria in a satisfaction-loyalty matrix and extend the customer satisfaction and loyalty post-analysis research bridging the gap in this field of research. To convert developed conceptual thought to experimental study, white goods industry is exemplified. 15 criteria are used for evaluation in 4 customer groups and a satisfaction-loyalty survey developed by experts is applied to 200 customers with face-to-face interviews. As a result of the study, a customer and criteria grouping method is created with high performance classification methods and good fit structural models. In addition, results are evaluated for developing a customer strategy improvement tool considering method outcomes. (C) 2014 Elsevier Ltd. All rights reserved.Öğe Demand forecasting application with regression and artificial intelligence methods in a construction machinery company(Springer, 2021) Aktepe, Adnan; Yanik, Emre; Ersoz, SuleymanDemand forecasts are used as input to planning activities and play an important role in the management of fundamental operations. Accurate demand forecasting is an important information for many organizations. It provides information for each stage of inventory management. In this study, multiple linear regression analysis, multiple nonlinear regression analysis, artificial neural networks and support vector regression were applied in a production facility that produces spare parts of construction machinery. The aim of the study is to forecast the number of spare parts requested in the future period by the customer as close as possible. As the input variables in the developed models, the sales amounts of the past years belonging to the manifold product group, which is one of the important spare parts of the construction machinery, number of construction machines sold in the world, USD exchange rate and monthly impact rate are used as input variables. The inputs of the model are designed according to construction machinery sector. In the model, monthly impact rate enables us to create more robust model. In addition, the estimation results have high accuracy by systematic parameter design of artificial intelligence methods. The data of the 9 years (from 2010 to 2018) were used in the application. Demand forecasts were conducted for 2018 to compare actual values. In forecasts, artificial neural network and support vector regression produced better results than regression methods. In addition, it was found that support vector regression forecasting produced better results in comparison to artificial neural network. __________________________________________________________________________________________Öğe Demand forecasting of spare parts with regression and machine learning methods: Application in a bus fleet(Academic Publication Council, 2023) Ifraz, Metin; Aktepe, Adnan; Ersoz, Suleyman; cetinyokus, TahsinForecasting the demand of spare parts of vehicles in bus fleets is a vital issue. Vehicles must operate effectively and must have a high availability rate in the fleet. In maintenance operations, faulty parts or parts that complete their lifetime must be replaced with a new one. Spare parts needed must be in inventories with the required amount on time. In this sector, there are thousands of spare parts to manage. The maintenance and repair department must operate effectively. In order to accomplish this, accurate forecast of spare parts is required. In this study, demand forecasting was carried out with regression-based methods (multivariate linear regression, multivariate nonlinear regression, Gaussian process regression, additive regression, regression by discretion, support vector regression), rule-based methods (decision table, M5Rule), tree-based methods (random forest, M5P, Random tree, REPTree) and artificial neural networks. The forecasting model developed in this study includes critical variables such as the number of vehicles in the fleet, the number of breakdowns that cause parts to change, the number of periodic maintenance, mean time between failure and demand quantity in previous years. The application was carried out with real data of eight (2013-2020) years. 2013-2019 data was used for training and 2020 data was used for testing. In forecasts, support vector regression among regression-based methods, decision table among rule-based methods, M5P among tree-based methods gave the best results. It has been observed that the artificial neural network produced more accurate forecasts than all other methods. Artificial neural network forecasts give the highest forecast accuracy rate and the least deviation.Öğe Denetimsiz Öğrenme İle E-Ticaret Sektöründe Faaliyet Gösteren Bir İşletmede Müşteri Segment Analizi Ve Uygulaması(Kırıkkale Üniversitesi, 2024) Ganioğlu, Beyza; Aktepe, Adnan; Ersöz, Süleyman; Tebrizcik, SemraElektronik ticaretin yaygınlaşması ile birlikte e-ticaret firma sayısında artış olmuş ve rakipler arasında rekabet başlamıştır. İşletmelerin rakip firmalar karşısında başarılı olması açısından müşteri memnuniyetinin günümüzde önemli bir yeri vardır. Müşteri memnuniyeti, müşterilerin aldığı hizmet veya ürün karşısında olumlu geri bildirim sağlamasıdır. Müşterilerin firma memnuniyetini artırması adına müşterilerin beklentilerini doğru analiz ederek müşteri memnuniyetini ve bağlılığını üst düzeye çıkarmak mümkündür. Müşterileri sadık müşteri, kaybetmek üzere olunan müşteriler ve kaybedilen müşteriler olarak kümelere ayırmak mümkündür. Bu çalışmada müşteri profillerini doğru analiz edip sadık müşterilerin sadakatini artırmak, kaybetmek üzere olunan müşterilerin bağlılığını ve memnuniyetini artırmak, kaybedilen müşterileri ise geri kazanmak adına doğru stratejileri geliştirmek amaçlanmıştır. Makalede 28 soruluk anket çalışması 100 farklı müşteri üzerinde uygulanmış olup, müşteriler e-ticaret sektöründe Kendini Örgütleyen Haritalar (KO?H/SOM) yardımıyla müşteriler 4 kümeye ayrılmıştır. Kümelerin özellikleri belirlenerek her bir kümeye özel satış stratejileri geliştirilmiştir. Müşteri kümeleri özelinde geliştirilen stratejiler ile müşterilerin memnuniyeti ve müşteri bağlılıklarını artırarak e-ticaret sitesinin sadık müşteri sayısını artırmak hedeflenmiştir.Öğe Design of a Tracking Welding Robot Automation System for Manufacturing of Steam and Heating Boilers(2018) Ersöz, Süleyman; Türker, Ahmet Kürşad; Aktepe, Adnan; Atabaş, İrfan; Kokoç, MeldaFor satisfying customers companies want to respond to customer requests on time. At the same time, they expect production process to be completed with low cost and low loss. For this reason, the importance of mechanization and automation in production sector has increased. As a result, companies have begun to give more importance to robotic systems, which are the basic components of automation systems. Despite the likelihood of mistakes caused by physiological and mental states of humans, these systems can perform operations precisely without any variability. In this study, an application was carried out for the automation of welding process of industrial type boilers in different sizes and features. For products of which standard measurements or welding operations are difficult to perform manually, a robotic system was proposed in which measurement and welding operations can be performed automatically. In addition, operators are prevented from exposure to gas and light via the proposed system which enables a safer working condition.Öğe Examining the Effect of Revenue Management on Customer Perceptions and Calculating the Service Performance Index: Food Order Application Example(Mdpi, 2022) Ozek, Kubra Ipek; Ersoz, Suleyman; Aktepe, Adnan; Teslim, SilaIn this research, the target is to create a Service Performance Index for food order mobile applications. In order to create the index, a structural equation model is developed. Then the coefficients which are obtained from the model are used to calculate the index values. There are some revenue management practices carried out in the food sector such as discounts when you order a meal for two or privileges for contracted credit card or mobile line users. In this context, this study tried to measure whether there is a relationship between the revenue management and customer perceptions, which are e-service quality, satisfaction and word of mouth. It was realized that revenue management has a significant, positive and high-level effect on e-service quality, satisfaction and word of mouth. The index scores of participants of the questionnaire were compared according to the frequency of benefiting from revenue management applications and discount campaigns. Thus, it was revealed that the service performance index of those who always use revenue management applications is higher than those who never use them. This result contributes to businesses with an important reference in terms of food marketing strategy.Öğe Export Potential Index for Textile Industry (EPIT) model proposal with structural equation modelling and application(Emerald Group Publishing Ltd, 2024) Kirkin, Metin; Aktepe, Adnan; Toklu, BilalPurposeThe aim of this study is to develop a new multidimensional index to measure export potential of textile firms by using firm-level data.Design/methodology/approachAfter a conceptual model, a structural equation model is developed with five dimensions and 27 observed variables based on resource-based view theory. The measurement model is solved by Linear Structural Relations (LISREL) with maximum likelihood algorithm by using data collected from 454 textile firms in T & uuml;rkiye.FindingsIn this study, a new multidimensional index that measures export potential of textile firms is developed. With the proposed model, the export potential of textile firms can be calculated numerically with the five dimensions: Resources, Dynamism, Knowledge, Innovation and Sustainability. The comparison of the output of the proposed model with the control variable, firm's actual export values, shows a significantly high success ratio of 90.76%.Research limitations/implicationsThe model is applicable for textile firms at different export levels, regions and sub-sectors. The Export Potential Index for Textile Industry model is verified by using Turkish textile industry data. The robustness of the model may be increased by verifying the model by using some other countries data. This model can be implemented to other industrial sectors with some modification of the dimensions and variables.Practical implicationsThe proposed model will contribute to the firms by calculating their export potential in five dimensions with their own variables numerically. The model will help firms to develop strategies to increase their export potential and to the governmental and industrial organizations to develop incentives policies.Originality/valueThis paper fills the gap in the literature by proposing a multidimensional index that determines a firm's export potential numerically by using firm-level data.
