- Turkey
Safiye TURGAY
Sakarya University, Industrial Engineering, Faculty Member
- RESEARCHERedit
Research Interests:
Research Interests:
Research Interests:
This paper explores the application of digital twin technology in the CAD/CAM domain, focusing on its potential to enhance the design and manufacturing structure. The paper begins by introducing the concept of digital twins and their role... more
This paper explores the application of digital twin technology in the CAD/CAM domain, focusing on its potential to enhance the design and manufacturing structure. The paper begins by introducing the concept of digital twins and their role in bridging the gap between physical and virtual worlds. It emphasizes the benefits of real-time data synchronization and it enables continuous monitoring, analysis, and decision-making throughout the product lifecycle in detail. Next, the focus shifts to the integration of digital twin modelling into the CAD/CAM processes. The paper outlines the steps involved in creating a digital twin of the design and manufacturing structure, from data acquisition and integration to model calibration and validation. Special attention is given to ensuring the accuracy and fidelity of the digital twin to enable reliable simulation results. The paper then explores the various simulation capabilities offered by the digital twin model. It delves into the use of finite element analysis (FEA), computational fluid dynamics (CFD), and other simulation techniques to analyse product performance, optimize manufacturing processes, and assess structural integrity. Case studies demonstrate the application of digital twin simulations in improving design efficiency, reducing time-to-market, and enhancing overall product quality.
Research Interests:
This study delves into the critical aspect of supply chain management-optimal inventory allocation-for the fast-moving consumer goods (FMCG) industry. FMCG companies face the challenge of meeting dynamic customer demands while minimizing... more
This study delves into the critical aspect of supply chain management-optimal inventory allocation-for the fast-moving consumer goods (FMCG) industry. FMCG companies face the challenge of meeting dynamic customer demands while minimizing excess inventory costs. This abstract highlights key strategies employed by successful FMCG businesses to strike a balance between customer satisfaction and efficient inventory management. Moreover, for seasonal products, a tailored approach to inventory allocation is vital, allowing companies to adjust stock levels to match peak demand and prevent overstocking. The integration of advanced inventory management software facilitates realtime tracking, analysis, and decision-making, streamlining the inventory allocation process. By implementing these strategies and continually refining them based on real-world data, FMCG businesses can achieve optimal inventory allocation, leading to improved customer satisfaction, reduced costs, and an overall boost in supply chain efficiency. This study offers a comprehensive overview of inventory optimization techniques, aiming to assist FMCG companies in navigating the complexities of inventory management and remaining competitive in a fast-paced market.
Research Interests:
Recently, health management systems have some troubles such as insufficient sharing of medical data, security problems of shared information, tampering and leaking of private data with data modeling probes and developing technology. Local... more
Recently, health management systems have some troubles such as insufficient sharing of medical data, security problems of shared information, tampering and leaking of private data with data modeling probes and developing technology. Local learning is performed together with federated learning and differential entropy method to prevent the leakage of medical confidential information, so blockchain-based learning is preferred to completely eliminate the possibility of leakage while in global learning. Qualitative and quantitative analysis of information can be made with information entropy technology for the effective and maximum use of medical data in the local learning process. The blockchain is used the distributed network structure and inherent security features, at the same time information is treated as a whole, not as islands of data. All the way through this work, data sharing between medical systems can be encouraged, access records tampered with, and better support medical research and definitive medical treatment. The M/M/1 queue for the memory pool and M/M/C queue to combine integrated blockchains with a unified learning structure. With the proposed model, the number of transactions per block, mining of each block, learning time, index operations per second, number of memory pools, waiting time in the memory pool, number of unconfirmed transactions in the whole system, total number of transactions were examined. Thanks to this study, the protection of the medical privacy information of the user during the service process and the autonomous management of the patient's own medical data will benefit the protection of privacy within the scope of medical data sharing. Motivated by this, proposed a blockchain and federated learning-based data management system able to develop in next studies.
Research Interests:
Blockchain technology has the potential to significantly enhance trust in supply chain management by providing a secure and transparent system for recording and tracking transactions. A blockchain is essentially a distributed ledger that... more
Blockchain technology has the potential to significantly enhance trust in supply chain management by providing a secure and transparent system for recording and tracking transactions. A blockchain is essentially a distributed ledger that is maintained by a network of nodes, and each node holds a copy of the same ledger. Transactions validated and recorded by the nodes in the network, and once a transaction is recorded, it cannot be altered or deleted. One of the key benefits of using blockchain technology in supply chain management is the ability to provide end-to-end traceability of products. By using a blockchain-based system, every transaction that occurs within the supply chain can be recorded and tracked, allowing for greater transparency and accountability. This can help to reduce the risk of fraud, counterfeiting, and other illegal activities within the supply chain. By using a decentralized system for recording and tracking transactions, there is less need for intermediaries and intermediaries, which can reduce costs and increase the speed of transactions. Overall, blockchain technology has the potential to significantly enhance trust in supply chain management by providing a secure and transparent system for recording and tracking transactions. However, there are still some challenges that need to be addressed, such as interoperability between different blockchain systems, and the need for standardization of data formats and protocols.
Research Interests:
Recently, health management systems have some troubles such as insufficient sharing of medical data, security problems of shared information, tampering and leaking of private data with data modeling probes and developing technology. Local... more
Recently, health management systems have some troubles such as insufficient sharing of medical data, security problems of shared information, tampering and leaking of private data with data modeling probes and developing technology. Local learning is performed together with federated learning and differential entropy method to prevent the leakage of medical confidential information, so blockchain-based learning is preferred to completely eliminate the possibility of leakage while in global learning. Qualitative and quantitative analysis of information can be made with information entropy technology for the effective and maximum use of medical data in the local learning process. The blockchain is used the distributed network structure and inherent security features, at the same time information is treated as a whole, not as islands of data. All the way through this work, data sharing between medical systems can be encouraged, access records tampered with, and better support medical research and definitive medical treatment. The M/M/1 queue for the memory pool and M/M/C queue to combine integrated blockchains with a unified learning structure. With the proposed model, the number of transactions per block, mining of each block, learning time, index operations per second, number of memory pools, waiting time in the memory pool, number of unconfirmed transactions in the whole system, total number of transactions were examined. Thanks to this study, the protection of the medical privacy information of the user during the service process and the autonomous management of the patient's own medical data will benefit the protection of privacy within the scope of medical data sharing. Motivated by this, proposed a blockchain and federated learning-based data management system able to develop in next studies.
Research Interests:
Research Interests:
Research Interests:
Research Interests: Engineering, Computer Science, Artificial Intelligence, Natural Language Processing, Multiobjective Optimization, and 15 moreNamed Entity Recognition, Engineering Optimization, Mathematical Sciences, Case Study, Multi objective optimization, Decision Support, Domain Knowledge, Mathematical Optimization, Conditional Random Field, Classifier Ensemble, Named Entity, Ac Power, Maximum entropy, Boundary Detection, and Electricity Distribution
Research Interests:
Research Interests:
Research Interests: Engineering, Computer Science, Artificial Intelligence, Operations Research, Fuzzy Logic, and 10 moreSystem Management, Numerical Analysis, Intelligent Manufacturing, Production economics, Manufacturing Engineering, Artificial Intelligent, Intelligent, Production Process, Manufacturing System, and Production System
Research Interests: Engineering, Computer Science, Agent Based, Automatic Control, Supervisory Control, and 13 moreControl system, Multi Agent System, Object Oriented Design, Multi Agent Systems, Agile Manufacturing, Control Design, Petri Net, Workstation, Manufacturing System, Fault Tolerant, System performance, Waiting Time, and Flexible Manufacturing System
Research Interests:
Cellular manufacturing is a process that groups similar machines, workstations, and processes in a dedicated area to maximize efficiency and reduce production time. A well-designed cellular manufacturing facility layout can increase... more
Cellular manufacturing is a process that groups similar machines, workstations, and processes in a dedicated area to maximize efficiency and reduce production time. A well-designed cellular manufacturing facility layout can increase productivity and decrease manufacturing costs. To optimize the layout design of a cellular manufacturing facility, digital twin simulation can be used. Digital twin simulation involves creating a virtual replica of a physical system or process to simulate and optimize various scenarios. By utilizing digital twin simulation, manufacturers can identify potential bottlenecks, inefficiencies, and other issues that could impact design and leading to cost savings and increased productivity. This paper will explore the concept of maximizing efficiency and cost savings through digital twin simulation, specifically focusing on optimizing cellular manufacturing processes. The paper will discuss the benefits of digital twin simulation, provide examples of its applications in cellular manufacturing.
Research Interests:
Job evaluation is a critical process in organizations, particularly in the manufacturing industry, where production roles play a vital role in overall operational success. Traditional job evaluation methods often rely on subjective... more
Job evaluation is a critical process in organizations, particularly in the manufacturing industry, where production roles play a vital role in overall operational success. Traditional job evaluation methods often rely on subjective judgments and can be prone to bias. This study considered the application of Fuzzy Cognitive Maps (FCMs) as a novel approach to job evaluation in the manufacturing industry. FCMs provide a framework to capture and represent the complex relationships and interdependencies between various job attributes and their impact on overall job performance. The objective of this empirical study is to demonstrate the effectiveness of FCMs in job evaluation for production roles in the manufacturing industry. The collected data will be used to construct FCMs, where nodes represent job attributes (e.g., technical skills, communication, problemsolving) and edges capture the strength and direction of relationships between attributes. The FCMs will be validated and calibrated using statistical techniques, ensuring their reliability and accuracy. The final evaluation framework will provide a quantitative method for assessing the relative importance of job attributes and determining the overall value of production roles within the organization.
Research Interests:
This research paper explores the application of lean manufacturing techniques for process improvement in the cable company. Lean manufacturing is a philosophy and methodology focused on eliminating waste and maximizing value-added... more
This research paper explores the application of lean manufacturing techniques for process improvement in the cable company. Lean manufacturing is a philosophy and methodology focused on eliminating waste and maximizing value-added activities in production processes. The cable industry faces various challenges, including complex production flows, high demand variability, and increasing customer expectations. Therefore, implementing lean manufacturing principles becomes crucial to enhance operational efficiency, reduce costs, and improve overall customer satisfaction. The paper begins by providing an overview of lean manufacturing principles, including the identification and elimination of various forms of waste such as overproduction, defects, waiting time, excessive inventory, and unnecessary motion. It highlights the importance of creating a culture of continuous improvement and engaging employees at all levels of the organization in the lean transformation process. Overall, this research paper provides a comprehensive approach to implementing lean manufacturing techniques in the cable company for process improvement. It serves as a valuable resource for managers, engineers, and practitioners in the cable industry seeking to enhance operational efficiency and achieve sustainable competitive advantage.
Research Interests:
The success and sustainability of small and medium-sized enterprises (SMEs) significantly influences by their ability to identify, assess, and mitigate risks effectively. However, many SMEs often lack the resources and expertise to... more
The success and sustainability of small and medium-sized enterprises (SMEs) significantly influences by their ability to identify, assess, and mitigate risks effectively. However, many SMEs often lack the resources and expertise to establish a robust risk management framework, leaving them vulnerable to potential threats and uncertainties. This comprehensive guide aims to bridge that gap by providing SMEs with a step-by-step approach to develop and implement an effective risk mitigation framework. The guide begins by highlighting the importance of risk management in the context of SMEs and its direct impact on their long-term growth and survival. A framework for ranking and categorizing risks based on their severity provided to help SMEs allocate resources efficiently. Once risks identified and prioritized, the guide delves into risk mitigation strategies. Various risk treatment options, including risk avoidance, risk reduction, risk transfer, and risk acceptance, explored in detail, enabling SMEs to make informed decisions based on their specific risk appetite and capacity. To ensure successful implementation, the guide outlines a step-by-step plan to integrate risk management into the organization's culture and operations. Key stakeholders' involvement and clear communication channels emphasized to foster risk-awareness throughout the SME. Furthermore, the guide underscores the significance of continuous monitoring and evaluation of the risk management framework. Periodic reviews allow SMEs to adapt their strategies as the business landscape evolves and new risks emerge. Real-world case studies and best practices incorporated throughout the guide to offer practical insights and illustrate the benefits of a well-structured risk management framework. By following this step-bystep guide, SMEs can proactively mitigate risks, enhance their decision-making process, and fortify their business against potential threats, ultimately paving the way for sustainable growth and long-term success.
Today, with the rapidly developing technology, data volume and data sharing are increasing day by day. Data mapping and reducing is very important in the process of analyzing big data which in faster and more effectively. In big data... more
Today, with the rapidly developing technology, data volume and data sharing are increasing day by day. Data mapping and reducing is very important in the process of analyzing big data which in faster and more effectively. In big data analysis, data mapping sequence and mining works by using a specific algorithm the inputs and lists of values as parameters. All values in the system entered for the intermediate results which are converted and created. In the mapping process, the data is subjected to fast sorting processes, taking into account the area that occupied with the number of repetitions. Processing small amounts of data has a cost-reducing effect on issues such as less time, memory, process and disk consumption. In this study, data sorting and data reduction operations were performed more effectively with the proposed algorithm. The data prepared for data analysis with their sortable features and then the process applied. Considering the data size and value structures have be...
Research Interests:
Data-driven approaches to hospital capacity planning and management involve using historical and real-time data to identify patterns and trends in patient demand, resource utilization, and other key metrics. This information provides to... more
Data-driven approaches to hospital capacity planning and management involve using historical and real-time data to identify patterns and trends in patient demand, resource utilization, and other key metrics. This information provides to develop predictive models, forecast patient demand, optimize staffing levels, and improve patient outcomes. Electronic health record systems and Internet of Things devices can also be used to monitor hospital operations in real-time and identify areas of inefficiency. Hospital capacity planning and management are critical to ensuring that healthcare facilities have enough resources to meet the needs of their patients. Data-driven approaches can be helpful in addressing these challenges by providing insights into patient demand, resource utilization, and other key metrics. This article discusses the various data-driven approaches to hospital capacity planning and management and their potential benefits. It also highlights the importance of having the right infrastructure and expertise effectively collect, analyse, and act on this data.
Research Interests:
In the pandemic period, the health sector has vital roles for the people. At the same time, it gets the necessity to study and review of this field. Health services and hospitals consist of different knowledge and qualification... more
In the pandemic period, the health sector has vital roles for the people. At the same time, it gets the necessity to study and review of this field. Health services and hospitals consist of different knowledge and qualification personnel's. In addition, these factors are getting difference among the people. Increasing motivation closely related to positive effect to working performance. Health institutions and hospitals have complex organizational structure consisting of personnel with different knowledge and qualifications. In addition, the effects of these factors on personnel motivation vary from person to person. Our aim is to find out the actors that affect the motivation of the personnel working in a health institution and which factor is more or less effective in the work environment. It is known by everyone that an increasing professionalization in health management will increase the performance and productivity of the personnel who become a whole with the company they work for, are aware of their duties and responsibilities and can give all their motivation to the work they do. In this study, performance criteria and motivation factors searched and examined. Management factors, individual factors and occupational other factors are analyzed in small health business company. Survey and performance applied analysis of 67 personnel belonging to a small health business during the COVID-19 pandemic period.
Research Interests:
Research Interests:
Research Interests:
Preventive maintenance planning management is modelled with stochastic approach. It is aimed to prevent stoppages and quality disorders due to disturbances, carriage and maintenance processes in production. Different maintenance policy... more
Preventive maintenance planning management is modelled with stochastic approach. It is aimed to prevent stoppages and quality disorders due to disturbances, carriage and maintenance processes in production. Different maintenance policy alternatives were considered in order to develop and sustain more effective maintenance policies. The preventive maintenance process includes the cost of inspection and maintenance status, the cost of repair and other losses in the accidents with operator injuries and damage to the possible value of the situation. The stochastic model approach is applied for determine the possible period intervals of the machinery and equipment and the maintenance process analyzed and discussed in detail. The preventive maintenance approach in the maintenance planning process is aimed to develop a sustainable maintenance policy without any disturbance in the quality of production from any disturbance and disruption of the system in the long term. However, it is aimed to take preventive maintenance measures as well as to analyze the current system condition and predict future situations.
Research Interests:
Research Interests:
Research Interests:
Recent and future technology development make intelligent transport systems a reality in contemporary societies leading to a higher quality, performance, and safety in transportation systems. In a big data era, however, efficient... more
Recent and future technology development make intelligent transport systems a reality in contemporary societies leading to a higher quality, performance, and safety in transportation systems. In a big data era, however, efficient information technology infrastructures are necessary to support real-time applications efficiently. In this paper, we review different control structures based on model predictive control and embed them in cloud infrastructures. We especially focus on conceptual ideas for intelligent road transportation and explain how the proposed cloud-based system can be used for parallel and scalable computing supporting real-time decision making based on large volumes and a variety of data from different sources. As such, the paper provides a novel approach for applying data-driven intelligent transport systems that utilize scalable and cost-efficient cloud infrastructures based on model predictive control structures.
Research Interests:
Production activities without interruption, growing the products on time, and producing the desired quality are essential for the sustainability of the enterprises. Today, with the developing technology, sustainability in the production... more
Production activities without interruption, growing the products on time, and producing the desired quality are essential for the sustainability of the enterprises. Today, with the developing technology, sustainability in the production process and analysis of production data has to integrate and the emerge of the big data and Internet of Things (IoT) concept. Continuously obtaining and analyzing the production data related to maintenance planning and revealing the rules to be used in the enterprise to analyze these data also support maintenance planning activities. They will make a significant contribution to the production process. However, most operating and maintenance costs are wasted due to incorrect, unsystematic, and unplanned maintenance methods. Maintenance costs are known to account for between 15% and 60% of the total operating costs. This study aims to standardize the types of breakdowns and faults to estimate them during the operation of the existing system by considering the frequency values of the breakdowns and faults obtained from dynamic structures from big data and encountered. It is one of the most important objectives to carry out the production process without interruption without increasing its performance with preventive measures and without deteriorating the production quality with a decision support system.
Research Interests:
The sustainable supply chain structure reveals the ability of firms to continue their activities in economic, social, and environmental dimensions. In the studies carried out so far that B2B and B2C structures are not considered... more
The sustainable supply chain structure reveals the ability of firms to continue their activities in economic, social, and environmental dimensions. In the studies carried out so far that B2B and B2C structures are not considered comparatively in sustainable supply chain models. As a result of examining the supply chain structure in the buying center, the study of different systems in B2B and B2C sectors revealed the situation. The B2B business-to-business structure acts in a more flexible and complementary design among themselves. In contrast, the responsibility of representing more brands better in the business-to-consumer network has emerged. The B2C structure can work more institutionally. In recent years, in developing economies with the technology revolution, the competitive system of businesses in their markets has been changing formally and dimensionally and has become increasingly sharper. Multi-Criteria Decision Making (MCDM) methods and a rough set approach used to analyze the competitive advantage in such an environment. A well-functioning supply chain provides a competitive advantage in the markets and ensures significant increases in market share. Therefore, businesses should be careful in supplier selection and work with suitable suppliers to achieve their goals by making a difference with their competitors. Therefore, competitive pressure has made supply chain management one of the essential issues businesses consider in achieving their business strategies. Supplier selection is a multi-criteria decision-making problem that includes multiple conflicting, numerical, and non-numerical criteria. The supplier selection problem aimed to determine the most appropriate measures that affect Sustainable Supply Chain Management(SSCM).
Research Interests:
In the pandemic period, the health sector has vital roles for the people. At the same time, it gets the necessity to study and review of this field. Health services and hospitals consist of different knowledge and qualification... more
In the pandemic period, the health sector has vital roles for the people. At the same time, it gets the necessity to study and review of this field. Health services and hospitals consist of different knowledge and qualification personnel's. In addition, these factors are getting difference among the people. Increasing motivation closely related to positive effect to working performance. Health institutions and hospitals have complex organizational structure consisting of personnel with different knowledge and qualifications. In addition, the effects of these factors on personnel motivation vary from person to person. Our aim is to find out the actors that affect the motivation of the personnel working in a health institution and which factor is more or less effective in the work environment. It is known by everyone that an increasing professionalization in health management will increase the performance and productivity of the personnel who become a whole with the company they work for, are aware of their duties and responsibilities and can give all their motivation to the work they do. In this study, performance criteria and motivation factors searched and examined. Management factors, individual factors and occupational other factors are analyzed in small health business company. Survey and performance applied analysis of 67 personnel belonging to a small health business during the COVID-19 pandemic period.
criteria methods are used simultaneously instead of selecting the best method for the situation. To test the proposed methodology, data obtained from a grocery retailer is used. Finally, discussion, implications and some concluding... more
criteria methods are used simultaneously instead of selecting the best method for the situation. To test the proposed methodology, data obtained from a grocery retailer is used. Finally, discussion, implications and some concluding remarks are provided.
The sustainable supply chain structure reveals the ability of firms to continue their activities in economic, social, and environmental dimensions. In the studies carried out so far that B2B and B2C structures are not considered... more
The sustainable supply chain structure reveals the ability of firms to continue their activities in economic, social, and environmental dimensions. In the studies carried out so far that B2B and B2C structures are not considered comparatively in sustainable supply chain models. As a result of examining the supply chain structure in the buying center, the study of different systems in B2B and B2C sectors revealed the situation. The B2B business-to-business structure acts in a more flexible and complementary design among themselves. In contrast, the responsibility of representing more brands better in the business-to-consumer network has emerged. The B2C structure can work more institutionally. In recent years, in developing economies with the technology revolution, the competitive system of businesses in their markets has been changing formally and dimensionally and has become increasingly sharper. Multi-Criteria Decision Making (MCDM) methods and a rough set approach used to analyze the competitive advantage in such an environment. A well-functioning supply chain provides a competitive advantage in the markets and ensures significant increases in market share. Therefore, businesses should be careful in supplier selection and work with suitable suppliers to achieve their goals by making a difference with their competitors. Therefore, competitive pressure has made supply chain management one of the essential issues businesses consider in achieving their business strategies. Supplier selection is a multi-criteria decision-making problem that includes multiple conflicting, numerical, and non-numerical criteria. The supplier selection problem aimed to determine the most appropriate measures that affect Sustainable Supply Chain Management(SSCM).
Production activities without interruption, growing the products on time, and producing the desired quality are essential for the sustainability of the enterprises. Today, with the developing technology, sustainability in the production... more
Production activities without interruption, growing the products on time, and producing the desired quality are essential for the sustainability of the enterprises. Today, with the developing technology, sustainability in the production process and analysis of production data has to integrate and the emerge of the big data and Internet of Things (IoT) concept. Continuously obtaining and analyzing the production data related to maintenance planning and revealing the rules to be used in the enterprise to analyze these data also support maintenance planning activities. They will make a significant contribution to the production process. However, most operating and maintenance costs are wasted due to incorrect, unsystematic, and unplanned maintenance methods. Maintenance costs are known to account for between 15% and 60% of the total operating costs. This study aims to standardize the types of breakdowns and faults to estimate them during the operation of the existing system by considering the frequency values of the breakdowns and faults obtained from dynamic structures from big data and encountered. It is one of the most important objectives to carry out the production process without interruption without increasing its performance with preventive measures and without deteriorating the production quality with a decision support system.
In a developing business, it has a very important to share in terms of competitive advantage by detecting and directing the errors before occur. There are many methods in the literature for the early detection and prioritization of these... more
In a developing business, it has a very important to share in terms of competitive advantage by detecting and directing the errors before occur. There are many methods in the literature for the early detection and prioritization of these failures. Failure modes and effects analysis (FMEA) is also a common method of choice. The uncertainty and flexibility problem arising from error types analysis has been eliminated by integrating fuzzy FMEA. The probability, severity, and discoverability values determined for each error were examined with error types, effects and fuzzy logic methods. Probability, severity, and discoverability values are considered and analyzed. Each method was listed according to the determined risk process network values and expert opinion, and comparisons were made between the methods.
While the development of technology and internet infrastructure facilitates many aspects of daily life, it does so based on the processes and data running in the background. With the development of information and communication... more
While the development of technology and internet infrastructure facilitates many aspects of daily life, it does so based on the processes and data running in the background. With the development of information and communication technology, changes and improvements in people's lives have also had a great impact on Intelligent Transportation Systems. Cloud Computing, which was developed for the storage of data that has been made descriptive of the virtual environment with a reference model setup as the first step. This model is aimed to facilitate the data storage, processing, and transfer process required for Intelligent Transportation Systems. In this study, a reference model on passenger occupancy rate, which is a passenger information system from Cloud Computing-based Intelligent Transportation System components, has been created, and this model has offered suggestions in the form of interface improvement for Sakarya Metropolitan Municipality transportation mobile application SAKUS. It is foreseen that these suggestions will have a great impact on the daily life of the passengers in planning their travels and in turning to alternative modes of transportation.
The digital twin-based fuzzy decision mechanism provides great opportunities for the realization of the optimization process, especially in the flexible production environment, with big data and new business modes beyond expectations.... more
The digital twin-based fuzzy decision mechanism provides great opportunities for the realization of the optimization process, especially in the flexible production environment, with big data and new business modes beyond expectations. Developing technology has brought with it the increasing amount of data and the development of big data analysis techniques. We can give Internet of Things (IoT), 5G, digital twin and cloud computing technologies as examples. Digital twin covers the process of monitoring and directing the production processes in the virtual environment in line with the increasing amount of data and the ability to respond quickly and accurately to customer services. The digital twin provides the internal and external changes in the production environment allow instant analysis of data. In this approach, it is aimed to optimize the production process, reduce costs and increase operational efficiency. It provides continuous learning in the production system environment and self-optimization of the system. It includes a digital twin-based integrated smart production model and the evaluation of the fuzzy approach in decision-making in a flexible production environment
With the development of computer technology, data and database structure and information systems have become widespread. For a distributed and dynamic environment, it is essential to realize the requirements of daily life in a short time.... more
With the development of computer technology, data and database structure and information systems have become widespread. For a distributed and dynamic environment, it is essential to realize the requirements of daily life in a short time. This study proposes the response model of the municipal system based on big data. It enables how significant sources of information, especially those containing uncertain and incomplete data, are evaluated and analyzed for fast and efficient decision-making with a cloud computingbased reference model. In this study, all data types in the municipal activities environment are assessed and analyzed in the reference model, including data management with submodules.
Recently, health management systems have some troubles such as insufficient sharing of medical data, security problems of shared information, tampering and leaking of private data with data modeling probes and developing technology. Local... more
Recently, health management systems have some troubles such as insufficient sharing of medical data, security problems of shared information, tampering and leaking of private data with data modeling probes and developing technology. Local learning is performed together with federated learning and differential entropy method to prevent the leakage of medical confidential information, so blockchain-based learning is preferred to completely eliminate the possibility of leakage while in global learning. Qualitative and quantitative analysis of information can be made with information entropy technology for the effective and maximum use of medical data in the local learning process. The blockchain is used the distributed network structure and inherent security features, at the same time information is treated as a whole, not as islands of data. All the way through this work, data sharing between medical systems can be encouraged, access records tampered with, and better support medical research and definitive medical treatment. The M/M/1 queue for the memory pool and M/M/C queue to combine integrated blockchains with a unified learning structure. With the proposed model, the number of transactions per block, mining of each block, learning time, index operations per second, number of memory pools, waiting time in the memory pool, number of unconfirmed transactions in the whole system, total number of transactions were examined. Thanks to this study, the protection of the medical privacy information of the user during the service process and the autonomous management of the patient's own medical data will benefit the protection of privacy within the scope of medical data sharing. Motivated by this, proposed a blockchain and federated learning-based data management system able to develop in next studies.
Problem definition: Rough set based MCDM method has been developed for rule extraction and classification from inconsistent and incomplete data structures. During the analysis, lower and upper approaches use the incomplete and uncertain... more
Problem definition: Rough set based MCDM method has been developed for rule extraction and classification from inconsistent and incomplete data structures. During the analysis, lower and upper approaches use the incomplete and uncertain data. Incomplete information analysis and knowledge base reduction methods can able to use the minimization of uncertainty also the structure does not contain strict constraints like fuzzy sets. Academic / Practical relevance: The rough set, first proposed by Pawlak [1] in 1982, that enables the discovery of the necessary information using large databases, as well as it can be used in the analysis of missing data structures and uncertain data. Also developed algorithm can be used as a tool in multi-criteria decision making techniques. Methodology: The rough set concept was developed to analyze of imprecise structures in multi-criteria decision making problems, and it was derived from fuzzy logic approach by evaluating the data which covers the lower and upper limits. Results: The results were solved with the developed algorithm, entropy-based approach, fuzzy MCDM, fuzzy AHP, and compared with the rough set-based approach that gave the same results with the fuzzy logic based MCDM, fuzzy logic based AHP, while the entropy-based result gave 75% similar results. It shows that the proposed method is reliable and suitable as other MCDM methods. Managerial implications: In view of the fact that the data are uncertain or incomplete, the existing multi-criteria decision making methods will be insufficient, seeing as the rough set-based multi-criteria decision making algorithm can able to overcome this deficiency.
Facility layout design problem considers the departments' physcial layout design with area requirements in some restrictions such as material handling costs, remoteness and distance requests. Briefly, facility layout problem related to... more
Facility layout design problem considers the departments' physcial layout design with area requirements in some restrictions such as material handling costs, remoteness and distance requests. Briefly, facility layout problem related to optimization of the layout costs and working conditions. This paper proposes a new multi objective simulated annealing algorithm for solving of the unequal area in layout design. Using of the different objective weights are generated with entropy approach and used in the alternative layout design. Multi objective function takes into the objective function and constraints. The suggested heuristic algorithm used the multi-objective parameters for initialization. Then prefered the entropy approach determines the weight of the objective functions. After the suggested improved simulated annealing approach applied to whole developed model. A multi-objective simulated annealing algorithm is implemented to increase the diversity and reduce the chance of getting layout conditions in local optima.
Preventive maintenance planning management is modelled with stochastic approach. It is aimed to prevent stoppages and quality disorders due to disturbances, carriage and maintenance processes in production. Different maintenance policy... more
Preventive maintenance planning management is modelled with stochastic approach. It is aimed to prevent stoppages and quality disorders due to disturbances, carriage and maintenance processes in production. Different maintenance policy alternatives were considered in order to develop and sustain more effective maintenance policies. The preventive maintenance process includes the cost of inspection and maintenance status, the cost of repair and other losses in the accidents with operator injuries and damage to the possible value of the situation. The stochastic model approach is applied for determine the possible period intervals of the machinery and equipment and the maintenance process analyzed and discussed in detail. The preventive maintenance approach in the maintenance planning process is aimed to develop a sustainable maintenance policy without any disturbance in the quality of production from any disturbance and disruption of the system in the long term. However, it is aimed to take preventive maintenance measures as well as to analyze the current system condition and predict future situations.
Fuzzy MCDM approach is developed to select nuclear power plant location in Turkey. The proposed framework employs fuzzy entropy and fuzzy compromise programming. A criterion set was developed using a map by The Turkish Atomic Energy... more
Fuzzy MCDM approach is developed to select nuclear power plant location in Turkey. The proposed framework employs fuzzy entropy and fuzzy compromise programming. A criterion set was developed using a map by The Turkish Atomic Energy Authority. Cilingoz is found to be the best with the index values 0.6584 and 0.0838. The proposed tool can be considered a tool to evaluate the alternative sites.
Project management has an important role in terms of time, cost and flexibility. An agentbased architecture provides additional robustness, scalability, flexibility that is particularly appropriate for problems with a dynamic and... more
Project management has an important role in terms of time, cost and flexibility. An agentbased architecture provides additional robustness, scalability, flexibility that is particularly appropriate for problems with a dynamic and distributed nature. Integrated agent based project management covers design and construction planning. It is combined with plan execution, tolerating both the design and plan, which may be changed as necessary. In this reason, the decision making process requires that the right effects of change need to be propagated through the plan and design in dynamic environment. It is difficult to estimate the operation times and costs exactly. A numerical simulation is presented at the end of this paper to illustrate the procedures of the proposed model.