Digital Manufacturing and Process Management, 2023
This paper explores the application of digital twin technology in the CAD/CAM domain, focusing on... 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.
Industrial Engineering and Innovation Management, 2023
This study delves into the critical aspect of supply chain management-optimal inventory allocatio... 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.
Recently, health management systems have some troubles such as insufficient sharing of medical da... 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.
Enhancing Trust in Supply Chain Management with a Blockchain Approach, 2023
Blockchain technology has the potential to significantly enhance trust in supply chain management... 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.
International journal of intelligent systems and applications, Oct 8, 2022
Recently, health management systems have some troubles such as insufficient sharing of medical da... 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.
Digital Manufacturing and Process Management, 2023
This paper explores the application of digital twin technology in the CAD/CAM domain, focusing on... 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.
Industrial Engineering and Innovation Management, 2023
This study delves into the critical aspect of supply chain management-optimal inventory allocatio... 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.
Recently, health management systems have some troubles such as insufficient sharing of medical da... 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.
Enhancing Trust in Supply Chain Management with a Blockchain Approach, 2023
Blockchain technology has the potential to significantly enhance trust in supply chain management... 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.
International journal of intelligent systems and applications, Oct 8, 2022
Recently, health management systems have some troubles such as insufficient sharing of medical da... 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.
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