Relevant bibliographies by topics / Cloud Storage in Manufacturing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cloud Storage in Manufacturing'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Cloud Storage in Manufacturing"

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Su, Kai Kai, Wen Sheng Xu, and Jian Yong Li. "Research on Mass Manufacturing Resource Sensory Data Management Based on Hadoop." Key Engineering Materials 693 (May 2016): 1880–85. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1880.

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Aiming at the management issue of mass sensory data from the manufacturing resources in cloud manufacturing, a management method for mass sensory data based on Hadoop is proposed. Firstly, characteristics of sensory data in cloud manufacturing are analyzed, meanings and advantages of Internet of Things and cloud computing are elaborated. Then the structure of the cloud manufacturing service platform is proposed based on Hadoop, the information model of manufacturing resources in cloud manufacturing is defined, and the data cloud in the cloud manufacturing service platform is designed. The dist
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Syed Omer Farooq Ahmed, Et al. "Machine Learning Algorithms in Cloud Manufacturing - A Review." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2024): 3213–26. http://dx.doi.org/10.17762/ijritcc.v11i9.9512.

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Cloud computing has advanced significantly in terms of storage, QoS, online service availability, and integration with conventional business models and procedures. The traditional manufacturing firm becomes Cloud Manufacturing when Cloud Services are integrated into the present production process. The capabilities of Cloud Manufacturing are enhanced by Machine Learning. A lot of machine learning algorithms provide the user with the desired outcomes. The main objectives are to learn more about the architecture and analysis of Cloud Manufacturing frameworks and the role that machine learning alg
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Zhao, Guang-Yuan, Wei Zong, and Guang-Jie An. "Effect of Storage on Cloud Stability of Cloudy Apple Juice." Food Science and Technology International 14, no. 1 (2008): 105–13. http://dx.doi.org/10.1177/1082013208090176.

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Cloud stability of particles in cloudy apple juice during its storage for 120 days at 4, 22 and 40 °C is conducted. The juices are added with or without ascorbic acid. The cloud stability of juices during storage is studied by optical microscopy, electron microscopy and size distribution analysis of suspending particles combined with a polyphenols component analysis by high performance liquid chromatography. At the beginning of storage, the turbidity of juice added with or without ascorbic acid decreased quickly because particles of larger size in juices aggregated and deposited, and since the
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Ren, Lei, and Lin Zhang. "An Efficient IT Energy-Saving Approach Based on Cloud Computing for Networked Green Manufacturing." Advanced Materials Research 139-141 (October 2010): 1374–77. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1374.

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Networked manufacturing technology has provided an effective approach to integrating manufacturing resources over Internet. However, a vast number of resources involving networks, computing, and storage resulted in ever increasing energy consumption. This paper proposed an IT energy-saving approach based on Cloud Computing for networked green manufacturing. The paper first presented the architecture of networked green manufacturing on Cloud Computing to support service-oriented IT resources outsourcing. Then the paper discussed the dynamically-scalable resource utilization mechanism for networ
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Researcher. "AI-DRIVEN CLOUD STORAGE SYSTEMS FOR PREDICTIVE MAINTENANCE IN MANUFACTURING." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 280–89. https://doi.org/10.5281/zenodo.13970658.

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This article examines the implementation and impact of AI-driven cloud storage systems for predictive maintenance in the manufacturing sector, focusing on case studies from industry leaders Siemens and General Electric (GE). The research explores the architecture of these systems, including IoT sensor deployment, data collection mechanisms, and AI algorithms for analysis. Through a comprehensive literature review and mixed-methods data collection approach, the study reveals significant benefits of these technologies, including a 30% reduction in unplanned downtime and substantial equipment lif
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Zhou, Guo Hong. "Study of Cloud Computing and Advanced Manufacturing Technology under Information Technology Development." Applied Mechanics and Materials 484-485 (January 2014): 227–30. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.227.

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Cloud computing can be regarded as the integration of grid computing and virtualization technology: namely the use of grid distributed computing processing power of IT resources and build into a resource pool, plus on a mature server virtualization, storage virtualization technology make users can real-time monitoring and deployment of resources. Cloud computing and advanced manufacturing technology is facing many challenges during the process of development in the future, including security and privacy will become a primary issue. This study focused on relations with the important areas of em
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Abdulshaheed, Haider Rasheed, Israa Al Barazanchi, and Madya Safiah Binti Sidek. "Survey: Benefits of integrating both wireless sensors networks and cloud computing infrastructure." Sustainable Engineering and Innovation 1, no. 2 (2019): 67–83. http://dx.doi.org/10.37868/sei.v1i2.29.

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Cloud computing has the capabilities of powerful processing and scalable storage with the ability of offline and online data analysis and mining of the collected sensed data from body areas networks. Cloud computing can be considered as main enabler for modern manufacturing industries. Cloud computing can efficiently serve key areas of manufacturing by aspects of pay-as-you-go business model, scaling up and down production according to certain demands, more customized solutions and flexible deployments. In cloud manufacturing, the distributed sensors and resources can be managed in centralized
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V.Mary, Rajam Vandana*1 Dr.K.Thamodaran 2. "IMPROVING THE PERFORMANCE OF CLOUD STORAGE THROUGH ELIMINATION OF DUPLICATE ENCRYPTED BIG DATA." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 10 (2017): 314–28. https://doi.org/10.5281/zenodo.1012533.

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Big data means a situation where the logistics of storing, processing, or analyzing data have surpassed traditional operational abilities of organizations. Cloud computing is purported to be the future of the IT industry. In cloud computing environment, as the infrastructure not owned by users, it is desirable that its security and integrity must be protected and verified time to time. Cloud computing marks a true paradigm shift in how the computing would happen in the future and cloud computing is likely to have the same impact on IT industry that foundries have had on the manufacturing indus
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Li, Jie. "Applied Research on the Impact of Big Data, Cloud Computing and Cloud Storage on Smart Manufacturing Supply Chain." Journal of Computing and Electronic Information Management 15, no. 1 (2024): 28–32. http://dx.doi.org/10.54097/sdszfk83.

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The rapid advancements in big data, cloud computing, and cloud storage technologies are profoundly reshaping the operational models of smart manufacturing supply chains. The integration and application of these technologies not only drive the enhanced data collection and analysis capabilities across various supply chain segments but also significantly improve the accuracy of demand forecasting, the rationality of resource allocation, and the scientific nature of decision support. Consequently, the collaborative efficiency and dynamic response capabilities of supply chains have been substantial
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Renjith, E. Jeslin. "Revolutionizing Cloud Security: Innovative Approaches for Safeguarding Data Integrity." FMDB Transactions on Sustainable Computer Letters 2, no. 2 (2024): 111–19. http://dx.doi.org/10.69888/ftscl.2024.000185.

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Cloud computing uses third-party servers or private clouds to provide online services and on-demand enterprise resource access. Microsoft Azure, Amazon, IBM, and Google Apps allow customers to design and run cloud-based apps from anywhere. These cloud services store and retrieve data from faraway servers, highlighting the importance of security due to internet data transfer. Before using cloud computing, firms must handle security issues. Pay-per-use, self-service, and scalability make the model popular in banking, healthcare, retail, education, manufacturing, and business. Pay-per-use models
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Dissertations / Theses on the topic "Cloud Storage in Manufacturing"

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Haver, Eirik, Eivind Melvold, and Pål Ruud. "Cloud Storage Vault." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for telematikk, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-13812.

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Today, major IT-companies, such as Microsoft, Amazon and Google, are offering online storage services to their customers. This is a favourable solution -- as opposed to regular storage -- in terms of low costs, reliability, scalability and capacity. However, important security features such as data privacy and integrity are often absent.To address these issues, a cryptographic architecture is proposed that ensures the confidentiality and integrity of the data stored by users, independent of the trust of the provider. This includes secure sharing of private data among users of the same service.
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Avlasovych, V. V. "Cloud data Storage." Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/46877.

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Today, the Internet gives us a lot of opportunities. One of them is a cloud data storage. Cloud Storage is a model of the data warehouse, which is located in the network on a large number of servers and provides non-stop customer access to their data from anywhere and any device with Internet access.
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Cappelli, Gino. "Data cloud through google cloud storage." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3032/.

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Il Cloud Storage è un modello di conservazione dati su computer in rete, dove i dati stessi sono memorizzati su molteplici server, reali e/o virtuali, generalmente ospitati presso strutture di terze parti o su server dedicati. Tramite questo modello è possibile accedere alle informazioni personali o aziendali, siano essi video, fotografie, musica, database o file in maniera “smaterializzata”, senza conoscere l’ubicazione fisica dei dati, da qualsiasi parte del mondo, con un qualsiasi dispositivo adeguato. I vantaggi di questa metodologia sono molteplici: infinita capacita’ di spazio di m
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Zapolskas, Vytautas. "Securing Cloud Storage Service." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for telematikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18626.

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Cloud computing brought flexibility, scalability, and capital cost savings to the IT industry. As more companies turn to cloud solutions, securing cloud based services becomes increasingly important, because for many organizations, the final barrier to adopting cloud computing is whether it is sufficiently secure.More users rely on cloud storage as it is mainly because cloud storage is available to be used by multiple devices (e.g. smart phones, tablets, notebooks, etc.) at the same time. These services often offer adequate protection to user's private data. However, there were cases wher
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Wang, Xing. "Benchmarking Cloud Storage Systems." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for telematikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-26716.

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With the rise of cloud computing, many cloud storage systems like Dropbox, Google Drive and Mega have been built to provide decentralized and reliable file storage. It is thus of prime importance to know their features, performance, and the best way to make use of them. In this context, we introduce BenchCloud, a tool designed as part of this thesis to conveniently and efficiently benchmark any cloud storage system.First, we provide a study of six commonly-used cloud storage systems to identify different types of their features. Then existing benchmarking tools for cloud systems are presented,
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Falk, Matthew D. "Cryptographic cloud storage framework." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85417.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 59).<br>The cloud prevents cheap and convenient ways to create shared remote repositories. One concern when creating systems that provide security is if the system will be able to remain secure when new attacks are developed. As tools and techniques for breaking security systems advance, new ideas are required to provide the security guarantees that may have been exploited. This project pre
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Parsa, Ramin. "Cloud Manufacturing and Sustainability." Thesis, Jönköping University, JTH, Produktionsutveckling, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53947.

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Collaboration is a pervasive element in an organization's departments, various suppliers, and business associates in an advanced manufacturing industry. Cloud Manufacturing (CMfg) is a new service-oriented business paradigm capable of generating this sought-after collaboration. Companies are expected to accomplish cost reductions, maintain quality, satisfy the market, and reduce environmental impacts while growing in sophistication and integration. Implementing the idea of sharing resources and capabilities will ultimately result in cost reduction, boost productivity,and more efficient consump
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Ali, Mazhar. "Towards Secure Cloud Storage Services." Diss., North Dakota State University, 2015. http://hdl.handle.net/10365/24802.

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Cloud computing is anticipated to revolutionize the Information and Communication Technology sector and has been a mainstream of research over the last decade. The cloud computing, upsurges the capabilities of the hardware resources by optimal and shared utilization. The above mentioned features encourage the organizations and individual users to shift their data, applications and services to the cloud. However, the services provided by third-party cloud service providers entail additional security threats. Data being one of the prime assets of the organizations must be protected from all sort
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Mourad, Mohamed. "Interoperability assessment in cloud manufacturing." Thesis, University of Bath, 2018. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761016.

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Cloud manufacturing is defined as a resource sharing paradigm that provides on- demand access to a pool of manufacturing resources and capabilities aimed at utilising geographically dispersed manufacturing resources in a service-oriented manner. These services are deployed via the Industrial Internet of Things (IIoT) and its underlying IT infrastructure, architecture models, as well as data and information exchange protocols and standards. In this context, interoperability has been identified to be a key enabler for implementing such vertically or horizontally integrated cyber-physical systems
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Graf, Sebastian [Verfasser]. "Flexible Secure Cloud Storage / Sebastian Graf." Konstanz : Bibliothek der Universität Konstanz, 2014. http://d-nb.info/1049393635/34.

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Books on the topic "Cloud Storage in Manufacturing"

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Li, Weidong, and Jörn Mehnen, eds. Cloud Manufacturing. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4935-4.

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Hua, Yu, and Xue Liu. Searchable Storage in Cloud Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2721-6.

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Galibus, Tatiana, Viktor V. Krasnoproshin, Robson de Oliveira Albuquerque, and Edison Pignaton de Freitas. Elements of Cloud Storage Security. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44962-3.

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Yang, Kan, and Xiaohua Jia. Security for Cloud Storage Systems. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-7873-7.

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Zhang, Yuan, Chunxiang Xu, and Xuemin Sherman Shen. Data Security in Cloud Storage. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4374-6.

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Schaefer, Dirk, ed. Cloud-Based Design and Manufacturing (CBDM). Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07398-9.

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Li, Weidong. Cloud Manufacturing: Distributed Computing Technologies for Global and Sustainable Manufacturing. Springer London, 2013.

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Wang, Lihui, and Xi Vincent Wang. Cloud-Based Cyber-Physical Systems in Manufacturing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-67693-7.

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Sokolov, Boris, Dmitry Ivanov, and Alexandre Dolgui, eds. Scheduling in Industry 4.0 and Cloud Manufacturing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43177-8.

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Walter, Gerry. Optical storage of engineering and manufacturing documents. Rothchild Consultants, 1988.

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Book chapters on the topic "Cloud Storage in Manufacturing"

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Krishnan, S. P. T., and Jose L. Ugia Gonzalez. "Cloud Storage." In Building Your Next Big Thing with Google Cloud Platform. Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1004-8_8.

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Frampton, Michael. "Cloud Storage." In Complete Guide to Open Source Big Data Stack. Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-2149-5_2.

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Saygili, Okcan Yasin. "Storage Cloud." In Oracle IaaS. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2832-6_3.

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Mathai, Manju K., and Juby Mathew. "Cloud storage." In Research Advances in Network Technologies. CRC Press, 2024. http://dx.doi.org/10.1201/9781003433958-6.

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Waschke, Marvin. "Storage Standards." In Cloud Standards. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4111-9_8.

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Sadiku, Matthew N. O., Abayomi J. Ajayi-Majebi, and Philip O. Adebo. "Cloud Manufacturing." In Emerging Technologies in Manufacturing. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-23156-8_13.

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Li, Feifei, Xuan Zhou, Peng Cai, Rong Zhang, Gui Huang, and XiangWen Liu. "Storage Engine." In Cloud Native Database. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-4057-4_4.

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Surianarayanan, Chellammal, and Pethuru Raj Chelliah. "Storage Fundamentals and Cloud Storage." In Texts in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13134-0_5.

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Surianarayanan, Chellammal, and Pethuru Raj Chelliah. "Storage Fundamentals and Cloud Storage." In Texts in Computer Science. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32044-6_5.

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Waschke, Marvin. "Cloud Storage and Cloud Network." In Cloud Standards. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4111-9_6.

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Conference papers on the topic "Cloud Storage in Manufacturing"

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Sairam, V. Sri, and M. Sathish Kumar. "Blockchain Based Cloud Storage System." In 2025 8th International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2025. https://doi.org/10.1109/icoei65986.2025.11012931.

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Reddy, T. Sudeep, V. Baladitya, N. Rohit, and G. Sreeraag. "Cloud Storage Security Audit System." In 2025 International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE). IEEE, 2025. https://doi.org/10.1109/amathe65477.2025.11080830.

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Wang, Yazhe, Shunan Ma, and Lei Ren. "A Security Framework for Cloud Manufacturing." In ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/msec2014-4082.

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Cloud manufacturing has been considered as a promising new service-oriented manufacturing paradigm that can transform traditional industry. However security is one of the major issues which hamper the growth of cloud manufacturing industry. In this paper, we analyze the cloud manufacturing security issues and challenges, and propose a security framework for cloud manufacturing, which includes four levels: infrastructure security, identity and access management, data protection and security, and cloud security as a service. The Infrastructure security level can ensure an organization’s core IT
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Zhao, Qiuyun, Wenli Liao, Le Wei, and Hongping Shu. "An Equipment Cloud Service Storage Scheme Based on Domain Division in Cloud Manufacturing Environment." In 2020 International Conference on Information Science, Parallel and Distributed Systems (ISPDS). IEEE, 2020. http://dx.doi.org/10.1109/ispds51347.2020.00031.

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Jeong, Hwa-Young, Jong Hyuk Park, and Jae Dong Lee. "The Cloud Storage Model for Manufacturing System in Global Factory Automation." In 2014 28th International Conference on Advanced Information Networking and Applications Workshops (WAINA). IEEE, 2014. http://dx.doi.org/10.1109/waina.2014.138.

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Wang, Xi Vincent, and Lihui Wang. "Function Block-Based Integration Mechanisms for Adaptive and Flexible Cloud Manufacturing." In ASME 2015 International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/msec2015-9303.

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Cloud Computing is the new enabling technology that offers centralised computing, flexible data storage, and scalable services. In the manufacturing context, it is possible to extend the Cloud technology for integrating and provisioning manufacturing facilities and capabilities in terms of Cloud services. In this paper, a function block-based integration mechanism is developed to integrate various types of manufacturing facilities. A Cloud-based architecture is also deployed to provide a service pool which maintains these facilities in terms of manufacturing services. The proposed framework an
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Zhao, Pu, Xin Sun, Jingtao Shang, Jianjun Lin, Mingming Dong, and Bo Li. "A Dynamic Convergent Replica Selection Strategy Based on Cloud Storage." In 2019 International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM). IEEE, 2019. http://dx.doi.org/10.1109/aiam48774.2019.00100.

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Wang, Yunpeng, Xiao Sun, Fangdong Zhu, Fan Zhang, Min Zhang, and Haisheng Cao. "ChainFileSynch: An Innovate File Synchronization for Cloud Storage with Blockchain." In 2019 International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM). IEEE, 2019. http://dx.doi.org/10.1109/aiam48774.2019.00115.

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Anderson, Patrick, Erika Aranas, Richard Black, et al. "Multi-dimensional optical data writing techniques for cloud-scale archival storage." In Laser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVIII, edited by Laura Gemini, Aiko Narazaki, and Jan Kleinert. SPIE, 2023. http://dx.doi.org/10.1117/12.2649177.

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Mei, Han, and Feng Ke. "GIS Application based on Cloud Storage for Atmospheric Environmental Monitoring." In 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015). Atlantis Press, 2015. http://dx.doi.org/10.2991/ic3me-15.2015.188.

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Reports on the topic "Cloud Storage in Manufacturing"

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Ivezic, Nenad, Boonserm Kulvatunyou, Yan Lu, et al. OAGi/NIST Workshop on Open Cloud Architecture for Smart Manufacturing. National Institute of Standards and Technology, 2016. http://dx.doi.org/10.6028/nist.ir.8124.

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McVay, Aaron. Point Cloud Storage and Access on a Global Scale. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada619005.

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Ho, Clifford, Prakash Rao, Nwike Iloeje, et al. Energy Storage for Manufacturing and Industrial Decarbonization (Energy StorM). Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1887337.

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Heifets, Samuel A. Study of Coherent Tune Shift Caused by Electron Cloud in Positron Storage Rings. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/798936.

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Lu, Xuan. CloudChord: A P2P Network of Clients Cloud Storage for Data Access Pattern Privacy. Iowa State University, 2018. http://dx.doi.org/10.31274/cc-20240624-373.

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Leavitt, Mark, and Patrick Lam. Development of advanced manufacturing technologies for low cost hydrogen storage vessels. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1229901.

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Verdu-Andres, Silvia. Electron cloud thresholds at the arcs of the Electron-Ion Collider hadron storage ring. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/1992863.

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Simmons, Kevin L., Kenneth I. Johnson, and Norman L. Newhouse. Low-Cost Efficient Manufacturing of Pressurized Conformable Compressed Natural Gas Storage Tanks. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1163679.

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Leavitt, Mark, Patrick Lam, Karl M. Nelson, et al. V1.6 Development of Advanced Manufacturing Technologies for Low Cost Hydrogen Storage Vessels. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1055412.

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Hendrick, Stephen, Hilary Carter, and Jason Perlow. 2021 Data and Storage Trends. The Linux Foundation, 2021. https://doi.org/10.70828/gqyx2842.

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Enterprise storage trends are all about core IT functions and day-to-day business challenges. 2020, however, was not your typical business year. In the wake of the COVID-19 pandemic, it was clear that the demand for secure and affordable data and storage services was exacerbated, but more insight into the current landscape was needed, especially the role of open source in this equation. The SODA Foundation is an open source project under the Linux Foundation that fosters an ecosystem of open source data management and storage software for data autonomy. SODA offers a neutral forum for cross-pr
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