Relevant bibliographies by topics / Integration SPC and EPC

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Integration SPC and EPC'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Integration SPC and EPC"

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Shao, Yuehjen E. "Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches." Abstract and Applied Analysis 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/519705.

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Because of the excellent performance on monitoring and controlling an autocorrelated process, the integration of statistical process control (SPC) and engineering process control (EPC) has drawn considerable attention in recent years. Both theoretical and empirical findings have suggested that the integration of SPC and EPC can be an effective way to improve the quality of a process, especially when the underlying process is autocorrelated. However, because EPC compensates for the effects of underlying disturbances, the disturbance patterns are embedded and hard to be recognized. Effective recognition of disturbance patterns is a very important issue for process improvement since disturbance patterns would be associated with certain assignable causes which affect the process. In practical situations, after compensating by EPC, the underlying disturbance patterns could be of any mixture types which are totally different from the original patterns. This study proposes the integration of support vector machine (SVM) and artificial neural network (ANN) approaches to recognize the disturbance patterns of the underlying disturbances. Experimental results revealed that the proposed schemes are able to effectively recognize various disturbance patterns of an SPC/EPC system.
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Wang, Xiu Hong. "Research on Process Monitoring and Adjusting Methods." Applied Mechanics and Materials 130-134 (October 2011): 2513–16. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.2513.

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Special reason and common reason bring on the process disturbance. Statistical process control (SPC) is commonly used to monitor the process disturbance which arises from assignable reason. Engineering process control (EPC) compensates the deviation of output for common reason based on the feedback adjustment principle. Therefore, integrated SPC/EPC approach has better performance than that merely using SPC or EPC. However, in practice, it is very hard to search the appropriate method to apply for integration of SPC/EPC. The main reason is that EPC’s compensation has depressed probability which assignable reason is monitored by control chart. In this paper, a joint-monitoring method is designed to account for the above problems through detecting process output as well as monitoring process input. An example is given to prove that joint-monitoring can detect the process disturbance more quickly and more accurately.
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Shao, Yuehjen E., Po-Yu Chang, and Chi-Jie Lu. "Applying Two-Stage Neural Network Based Classifiers to the Identification of Mixture Control Chart Patterns for an SPC-EPC Process." Complexity 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/2323082.

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The effective controlling and monitoring of an industrial process through the integration of statistical process control (SPC) and engineering process control (EPC) has been widely addressed in recent years. However, because the mixture types of disturbances are often embedded in underlying processes, mixture control chart patterns (MCCPs) are very difficult for an SPC-EPC process to identify. This can result in problems when attempting to determine the underlying root causes of process faults. Additionally, a large number of categories of disturbances may be present in a process, but typical single-stage classifiers have difficulty in identifying large numbers of categories of disturbances in an SPC-EPC process. Therefore, we propose a two-stage neural network (NN) based scheme to enhance the accurate identification rate (AIR) for MCCPs by performing dimension reduction on disturbance categories. The two-stage scheme includes a combination of a NN, support vector machine (SVM), and multivariate adaptive regression splines (MARS). Experimental results reveal that the proposed scheme achieves a satisfactory AIR for identifying MCCPs in an SPC-EPC system.
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KEATS, J. BERT, DOUGLAS C. MONTGOMERY, GEORGE C. RUNGER, and WILLIAM S. MESSINA. "FEEDBACK CONTROL AND STATISTICAL PROCESS MONITORING." International Journal of Reliability, Quality and Safety Engineering 03, no. 03 (September 1996): 231–41. http://dx.doi.org/10.1142/s0218539396000168.

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In the industrial world, different methodologies have been applied to reduce variability. Engineers whose training is in the quality assurance sciences have frequently used statistical process control (SPC) whereas engineers whose background includes control theory have employed engineering process control (EPC), often in the form of feedback control. SPC is usually applied to processes that vary about a fixed mean, with successive observations viewed as statistically independent. EPC is usually applied to processes in which successive observations are related over time, and where the mean drifts dynamically. The objective of SPC is to reduce variability by the elimination of assignable causes that shift the mean off-target, while EPC continuously adjusts manipulatable variables in the process to keep the mean on target. This study demonstrates the effectiveness of integrating SPC with feedback control for three commonly encountered schemes: Integral Control, Proportional-Integral Control, and Proportional-Integral-Differential Control. A simulation study demonstrates that the combined EPC/SPC scheme significantly reduces overall variability in comparison to feedback control alone when assignable causes are present.
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Huang, Chung-Hsing, and Yi-Ni Lin. "Decision rule of assignable causes removal under an SPC-EPC integration system." International Journal of Systems Science 33, no. 10 (January 2002): 855–67. http://dx.doi.org/10.1080/00207720210167005.

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Jiang, Wei, and John V. Farr. "Integrating SPC and EPC Methods for Quality Improvement." Quality Technology & Quantitative Management 4, no. 3 (January 2007): 345–63. http://dx.doi.org/10.1080/16843703.2007.11673156.

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Jiang, Zhong Qiu. "The Intelligent Quality Control Technology System Based on the Integration Methods of SPC and EPC." Applied Mechanics and Materials 263-266 (December 2012): 839–42. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.839.

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SPC (statistical process control) and EPC (engineering process control) is the scientific methods of quality quality control and quality improvement. It is the difficult problems of quality control process for network manufacturing enterprise how to effectively solve the dynamic quality fluctuation monitoring and the fluctuation abnormal diagnostic analysis and timely process adjustments, this paper designs the intelligent quality control mode and function system architecture, the modes expatiates quality management network based on quality control network of the workshop level and enterprise class network, and researches the integration applications of statistical process control and enterprise ERP quality system, and applies J2EE technology to achieve the system organic combination of design and development.
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Hu, Yaoguang, and Xi Cheng. "A Quality Control Approach of PVC Gloves Based on the Integration of SPC and EPC." Communications in Statistics - Theory and Methods 41, no. 24 (December 15, 2012): 4470–83. http://dx.doi.org/10.1080/03610926.2012.728276.

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Göb, Rainer, Enrique Del Castillo, and Klaus Dräger. "Run length analysis of Shewhart charts applied to drifting processes under an integrative SPC/EPC model." Metrika 50, no. 2 (December 1999): 0137–61. http://dx.doi.org/10.1007/s001840050041.

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Levine, Oren Hannun, Daryl Bainbridge, Gregory Russell Pond, Marissa Slaven, Sukhbinder K. Dhesy-Thind, Jonathan Sussman, and Ralph M. Meyer. "The ESCAPADE Study: Early supportive care for advanced cancer patients, assessing care delivery and provider engagement." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): e23142-e23142. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e23142.

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e23142 Background: Advanced cancer patients benefit from early integration of palliative care (EIPC) with usual care. A proposed model of EIPC reserves specialized palliative care (SPC) for complex patients, while primary care providers (PCP) and oncologists oversee basic palliative care (PC). We studied the attitudes among patients and their healthcare providers regarding delivery of EIPC. Methods: A cross-sectional study at a tertiary cancer centre in Ontario. Patients with newly diagnosed incurable gastrointestinal (GI) cancer were surveyed using a study specific instrument for the outcomes of interest: importance of and preferences for accessing support across 8 domains of PC (disease management, physical, psychological, social, spiritual, practical, end of life care, loss and grief). Healthcare providers within the circle of care completed a parallel survey for each recruited patient. Primary analysis involved use of descriptive statistics to summarize survey results and concordance between patient and provider responses. Results: From Oct 2017 - Nov 2018, 67 patients were surveyed (median age 69, 34% female). 90% had an identified medical oncologist, and 19% had SPC. 97% had a PCP, but only 42% listed a PCP as part of the care team. Median time from first oncology assessment for advanced cancer to patient survey completion was 52.5 days. 85 providers responded (oncologist = 59, PCP = 20, SPC = 6; response rate 92%; 1-3 physician responses per patient). Disease management and physical concerns were most important to patients. In these domains, 67% and 81% of patients endorsed receiving care from the preferred provider, but concordance between patient and physician responses regarding most responsible provider was only 58% and 38%. For all other domains, 87 – 100% of patients attributed primary responsibility to self or family rather than any healthcare provider. Conclusions: Respondents did not assign responsibility to physicians early in the disease trajectory for many domains of PC. Our findings suggest that incorporating patient activation and empowerment into EIPC requires further study. PCPs appeared to have limited involvement in PC for newly diagnosed advanced GI cancer patients.
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Dissertations / Theses on the topic "Integration SPC and EPC"

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Trentin, Marcelo Gonçalves. "Monitoramento e controle estatístico integrado ao controle de engenharia de processo." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2010. http://hdl.handle.net/10183/28819.

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Com o aumento da produção mundial em proporções cada vez maiores, os processos industriais têm se tornando um desafio pela complexidade do seu gerenciamento. A identificação rápida e precisa de não conformidades é cada vez mais necessária e mais difícil de ser realizada. Este estudo propõe a integração do Controle de Engenharia com o Controle Estatístico de Processo, no monitoramento e controle de processos industriais, almejando a percepção mais rápida de anormalidades, visando à redução de problemas de especificação de produtos. Uma forma de autoajuste do controlador Proporcional-Integral e Derivativo (PID) é proposta, aumentando a robustez do sistema, empregando-se técnicas comumente utilizadas nos processos. O modelo matemático do processo, equacionando as relações das variáveis envolvidas, é estabelecido para determinação e especificação do controlador e de forma conjunta as cartas de controle são configuradas. O controlador projetado para a situação normal de operação atua no sentido de manter as variáveis de saída (controladas) dentro de especificações através do conhecimento de sua relação com as de entrada e de processo. As cartas de controle baseadas em modelos, monitorando os resíduos provenientes de ajustes de modelos ARIMA, acompanham as variações do processo, evitando variabilidade excessiva e possibilitando a detecção de comportamentos anormais, inclusive monitorando o desempenho do próprio controlador. Com a sinalização das cartas de controle, é realizada uma interferência na equação de ajuste do controlador. Empregando-se a simulação numérica, analisam-se os comportamentos do controlador e este, combinado com as cartas de controle. Falhas inseridas propositalmente, em cada variável controlada, foram devidamente sinalizadas. Estas sinalizações ocorreram mesmo em situações em que as variáveis estiveram mantidas dentro da especificação pelo controlador. Para o sistema de autoajuste, o aumento dos ganhos de contribuição das cartas de controle proporcionou maior acurácia das variáveis controladas (monitoradas). A integração proposta apresentou melhores resultados, quanto à manutenção das variáveis de saída próximas aos seus alvos, quando comparada com o controlador operando isoladamente.
With the increase of world production at bigger and bigger proportions, the industrial processes have become a challenge by the complexity of their management. The fast and precise identification of non-conformities is increasingly necessary and more difficult to be performed, preferably even before problems with product specification or waste can be considered. This study proposes the integration of Engineering Process Control with the Statistical Process Control, in monitoring and controlling of industrial processes, aiming the quicker perception of abnormalities, looking for the reduction of products specification problems. A form of self-adjustment of the Proportional-Integral and Derivative Controller (PID) is proposed, increasing the system robustness applying techniques commonly used in the processes. The mathematical model of the process, equating the relationship of the variables involved, is established to the determination and specification of the controller, and the control charts are configure in an integrated way. The controller projected to the normal operation situation, acts in the sense of keeping the exit variables (controlled) within the specifications through the knowledge of its relationship with that of the entrance and that of the process. The control charts based in models, monitoring the residues coming from the models adjustment ARIMA, follow up the process variations avoiding excessive variability and making it possible the detection of abnormal behaviors, even monitoring the performance of the controller itself. With the signalling of the control charts, an interference in the equation of adjustment of the controller is performed. Applying the numerical simulation, the controller behaviors are analyzed and this combined with the control charts. Intentionally inserted failures, in each controlled variable, were properly signalized. These signallings have happened even in situations where the variables were kept by the controller within the specification.. To the self-adjustment system, the increase of contribution gains of the control charts has provided greater accuracy of the controlled variables. The integration proposed has presented better results, in relation to maintain of the exit variables next to their targets, when compared to the controller operating in isolation.
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Chang, Hsuan-Kai. "An integrated SPC/EPC system for fault diagnosis." Diss., Online access via UMI:, 2009.

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Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Systems Science and Industrial Engineering, 2009.
Includes bibliographical references.
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Ramalho, Octávio Ferreira. "Implementação integrada de SPC e EPC na melhoria contínua do processo." Master's thesis, Faculdade de Ciências e Tecnologia, 2008. http://hdl.handle.net/10362/3937.

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Dissertação apresentada na faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Industrial
Durante os últimos anos tem havido nos meios académicos, por parte de um sector da engenharia industrial um esforço no sentido de integrar duas metodologias de controlo que, em muitas situações reais, estão implementadas de forma autónoma. A primeira, mais ligada à engenharia da qualidade, consiste na monitorização dos processos com recurso a cartas de controlo, ou controlo estatístico do processo (SPC - Statistical Process Control). A segunda abordagem está baseada no ajustamento dos processos recorrendo à informação sobre os níveis actuais das respostas ou desvios em relação aos valores de referência e constitui a engenharia de controlo do processo (EPC). Ambas as metodologias têm por base a identificação e modelação do processo. O presente trabalho apresenta metodologias abrangentes para a identificação e modelação dos processos, baseadas em estimativas dos mínimos quadrados e de máxima verosimilhança, com o objectivo de se captar as dinâmicas internas dos processos e assim obter os modelos necessários à implementação integrada, ou não, do controlo estatístico (SPC) e engenharia de controlo (EPC - Engineering Process Control). Pretendendo-se ser o mais abrangente possível, toda a abordagem foi feita para lidar com sistemas de múltiplas entradas e múltiplas saídas (MIMO Multi-Input/Multi-Output), considerando-se os outros modelos (SISO ou MISO) como casos particulares deste. A metodologia de identificação implementada foi posteriormente utilizada com dados reais provenientes de um processo MISO, obtendo-se assim o modelo que serviu de base para simular o sistema de integrado SPC/EPC. Com base nos resultados obtidos por simulação, pode-se concluir que o sistema integrado permite simultaneamente um melhor ajustamento do processo em relação aos valores de referência, reduzir a sua variabilidade, detectar alterações verificadas no processo e, caso seja possível, alterar o algoritmo de controlo de forma a responder às alterações verificadas.
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Tezic, Kerem. "Essays on immigrants' economic integration /." Göteborg : Dept. of Economics [Nationalekonomiska institutionen], Univ, 2004. http://www.handels.gu.se/epc/archive/00003616/01/Kerem_full.pdf.

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Erlandsson, Mattias. "On monetary integration and macroeconomic policy." Göteborg : Dept. of Economics, School of Economics and Commercial Law, [Nationalekonomiska institutionen, Handelshögsk.], Univ, 2003. http://www.handels.gu.se/epc/archive/00002715/01/Erlandsson.avhandl.pdf.

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Rohani, Jafri Mohd. "The development and analysis of quality control adjustment schemes for process regulation." Ohio : Ohio University, 1995. http://www.ohiolink.edu/etd/view.cgi?ohiou1179951651.

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Bouterse, Rosita B. "Competition and integration - what goals count? : EEC competition law and goals of industrial, monetary, and cultural policy /." Deventer [u.a.] : Kluwer Law and Taxation Publ, 1994. http://www.gbv.de/dms/spk/sbb/recht/toc/276164091.pdf.

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沈瑞蓉 and Ray-Long Shen. "應用多品質特性之SPC-EPC 系統於隧道窯爐溫控制之製程管制探討–以陶瓷電容之介電瓷粉製程為例." 碩士, 朝陽科技大學, 1991. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22091CYUT5031044%22.&searchmode=basic.

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Chung, Lin-Cheng, and 鍾姈君. "A Study on the Integration of SPC And EPC." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/62729054866886291185.

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碩士
國立清華大學
統計學研究所
86
Statistical process control (SPC) and engineering process control (EPC) are twostrategies for quality improvement.In general, both strategies have reduction of variablity as their objective,although they seek to accomplish this objective in different ways.This article addresses the $EPC$ rules ($MV$ controller) of the process withmore general stochastic disturbances. We also examine the advantage of usingthe $Cuscore$ control as an interface between $EPC$ and $SPC$ techniques.
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Lu, Shu-Lan, and 盧淑蘭. "A Study of Dealing With theAutocorrelated Data by Integrating EPC and SPC." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/92426406850012769091.

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碩士
國立雲林科技大學
工業工程與管理研究所碩士班
91
Autocorrelation commonly exists in the process industry. With reduced ARL, autocorrelation leads to increase the false alarm rate of control charts. It is required to deal with autocorrelation, because it can cause significant deterioration of control charting performance. Time series approach is generally used to describe the structure of autocorrelation. AR(1) and AR(2) models are investigated, and disturbances considered are stepped or linear types. Recent researches on process control find that integration of EPC and SPC has good performance. Purpose of this research is to study integrated EPC and SPC method in dealing with autocorrelated data. Three control charts are considered: Shwhart、CUSUM and EWMA chart. From this study,results show that when the level of autocorrelation is low, the result of integrated EPC and SPC is similar to time series model approach. However, when data with high autocorrelation, integrated EPC and SPC is better than time series model approach. CUSUM and EWMA charts are better than Shewhart chart in these situations:(1) in stepped disturbance, low level of autocorrelation and range of process shifts is 0.5 to 2 time standard deviation; (2) in stepped disturbance, high level of autocorrelation and range of process shifts is 1 to 3 time standard deviation; (3)in linear disturbance, the slope of process shifts is between 0.05 and 0.5. Therefore, it is a good choice using CUSUM or EWMA charts for process monitoring under these situations.
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Book chapters on the topic "Integration SPC and EPC"

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Tsang, Julia Y., Ping Tang, and Gary M. Tse. "Papillary Lesions of the Breast (IDP, IDPC, EPC, SPC)." In Practical Breast Pathology, 145–57. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16518-5_5.

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Nishina, Ken, Masanobu Higashide, Hironobu Kawamura, and Naru Ishii. "On the Integration of SPC and APC: APC Can Be a Convenient Support for SPC." In Frontiers in Statistical Quality Control 10, 109–19. Heidelberg: Physica-Verlag HD, 2012. http://dx.doi.org/10.1007/978-3-7908-2846-7_8.

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Nüttgens, M., T. Feld, and V. Zimmermann. "Business Process Modeling with EPC and UML: Transformation or Integration?" In The Unified Modeling Language, 250–61. Heidelberg: Physica-Verlag HD, 1998. http://dx.doi.org/10.1007/978-3-642-48673-9_17.

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Chang, Yao-Chung. "Integration of EPC and Wireless Sensor Networks for Heterogeneous Networking in a U-Life Environment." In Advances in Intelligent Systems and Applications - Volume 1, 551–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35452-6_56.

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"A Methodological Approach for the Integration of SPC and EPC in Discrete Manufacturing Processes." In Statistical Process Monitoring and Optimization, 97–126. CRC Press, 1999. http://dx.doi.org/10.1201/9781482276763-7.

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Smew, Walid, Bader Al-Mutawa, and Ali Issawy. "Implementation of SPC-EPC Scheme to Lessen and Control Production Disruptions in Chlor-Alkali Industry." In Lean Manufacturing and Six Sigma - Behind the Mask. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.86514.

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Segers, Mathieu. "A Europe of conspiracies (1957-1968)." In The Netherlands and European Integration, 1950 to Present. Nieuwe Prinsengracht 89 1018 VR Amsterdam Nederland: Amsterdam University Press, 2020. http://dx.doi.org/10.5117/9789463728133_ch05.

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The Europe of the Six never became The Hague’s Europe, just as it never became London’s or Ludwig Erhard’s. The revisionism this induced in Dutch government circles remained a priority regardless of what government was in office during the 1950s, ‘60s and early ‘70s. Successive Dutch governments of all political colours actively engaged in attempts to sabotage French initiatives and Franco-German plans for a European Political Community (EPC) in the mid-1950s. And when French President de Gaulle made new attempts to create a European Political Union in the early 1960s, Dutch diplomacy helped unveil what were seen as Gaullist conspiracies aimed at steering European integration in an anti-Anglo-Saxon direction, which the Dutch saw as also undermining NATO.
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Stein, Sebastian, Christian Stamber, Marwane El Kharbili, and Pawel Rubach. "Semantic Business Process Management." In Information Resources Management, 1144–66. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-965-1.ch412.

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The application of semantic technologies promises boosting business process management because semantic integration of business and IT is achieved. To enable the vision of semantic business process management, semantic technologies like ontologies, reasoners, and semantic Web services must be integrated in BPM tools. We extended a professional BPM tool to allow semantic business process modelling using the EPC notation. In addition, we adapted the tool’s EPC to BPEL transformation to preserve the semantic annotations. By introducing a proxy service, we are able to perform Semantic Web service discovery on a standard BPEL engine. We evaluated our approach in an empirical case study, which was replicated 13 times by 17 participants from 8 different organisations. We received valuable feedback, which is interesting for researchers and practitioners trying to bring semantic technologies to end-users with no or only limited background knowledge about semantics.
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Solanki, Monika, and Christopher Brewster. "Enhancing Visibility in EPCIS Governing Agri-Food Supply Chains via Linked Pedigrees." In Information Retrieval and Management, 839–70. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5191-1.ch036.

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Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services (EPCIS) is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code (EPC). In this paper, the authors propose a framework that utilises events and EPCs in the generation of “linked pedigrees” - linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.
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Bulmer, Simon, Owen Parker, Ian Bache, Stephen George, and Charlotte Burns. "25. Common Foreign and Security Policy." In Politics in the European Union, 476–94. Oxford University Press, 2020. http://dx.doi.org/10.1093/hepl/9780198820635.003.0025.

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This chapter examines the European Union’s (EU’s) Common Foreign and Security Policy (CFSP). It tells the story of increasing co-operation between member states on foreign policy matters, first with European Political Co-operation (EPC) and, since the 1990s, with CFSP and a Common Security and Defence Policy (CSDP). The chapter highlights the internal dynamics and external events that drove the member states towards such co-operation and considers the most recent example of such efforts: the 2017 attempt to create a system of permanent structured co-operation (PESCO). However, it is noted that the EU remains far from having a truly supranational foreign policy and there remains a reluctance from member states to push much further integration, given states’ keen desire to remain sovereign in this area. Finally, the chapter considers the EU’s status as a ‘power’ in international relations, noting that it has diminished in important respects since 2003, but remains an important economic power.
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Conference papers on the topic "Integration SPC and EPC"

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Jiang, Jui-Chin, Feng-Yuan Hsiao, and Chun-An Chen. "Applying SPC/EPC to Establish a MIMO Process Control System." In 2008 ISECS International Colloquium on Computing, Communication, Control, and Management. IEEE, 2008. http://dx.doi.org/10.1109/cccm.2008.12.

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Kim, Jung-Goon. "Improved EPC Integration Management for FPSOs." In Offshore Technology Conference. Offshore Technology Conference, 2008. http://dx.doi.org/10.4043/19695-ms.

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Yang Musheng and Zhang Yu. "Intelligent Integrated Method of EPC and SPC in Manufacturing Process Quality Control." In 2007 IEEE International Conference on Control and Automation. IEEE, 2007. http://dx.doi.org/10.1109/icca.2007.4376674.

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Savolainen, Jari T., Harri Hirvola, and Sassan Iraji. "EPC UHF RFID Reader: Mobile Phone Integration and Services." In 2009 6th IEEE Consumer Communications and Networking Conference (CCNC). IEEE, 2009. http://dx.doi.org/10.1109/ccnc.2009.4784900.

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Zhang, Cheng Cheng, Kim Khoa Nguyen, Chuan Pham, and Mohamed Cheriet. "Routing and Packet Scheduling in LORAWANs-EPC Integration Network." In GLOBECOM 2020 - 2020 IEEE Global Communications Conference. IEEE, 2020. http://dx.doi.org/10.1109/globecom42002.2020.9322231.

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Wang, Xiuhong. "Optimize transition stages of the integrated SPC/EPC process using improved ant colony algorithm." In 2010 Sixth International Conference on Natural Computation (ICNC). IEEE, 2010. http://dx.doi.org/10.1109/icnc.2010.5583724.

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Shao, Yuehjen E. "A Fault Detection for a Correlated Process with the Use of SPC/EPC/NN Scheme." In 2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC). IEEE, 2009. http://dx.doi.org/10.1109/icicic.2009.13.

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Sung, Jongwoo, Tomas Sanchez Lopez, and Daeyoung Kim. "The EPC Sensor Network for RFID and WSN Integration Infrastructure." In Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07). IEEE, 2007. http://dx.doi.org/10.1109/percomw.2007.113.

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Zhijun Wang, Dehua Chen, Ming Du, and Jiajin Le. "A novel RFID event data integration approach via EPC network." In 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icicisys.2010.5658702.

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Mawatari, Takashi, Yasushi Yamamoto, Osamu Shibasaki, Takahiro Hara, Yusuke Horayama, and Junichi Takagi. "Evaluations of TiO2 Deposition on Structure Surfaces and Water Radiolysis for the Corrosive Environment in a Reactor Pressure Vessel." In 2020 International Conference on Nuclear Engineering collocated with the ASME 2020 Power Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/icone2020-16405.

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Abstract:
Abstract It is important to avoid a risk of stress corrosion cracking (SCC) of structure materials in nuclear power plants. One of the methods for preventing SCC is titanium-dioxide (TiO2) injection. TiO2 is a photo-catalyst, and injected TiO2 deposits on the surfaces of structure materials, and the deposited TiO2 can decrease the electrochemical corrosion potential (ECP) by irradiation of Cherenkov-light in the reactor. Generally, the ECP is an important indicator about susceptibility to SCC, and ECP-lowering makes a risk of SCC lower. Therefore, initiation and propagation of SCC will be mitigated by the TiO2 injection. The evaluation model for corrosive environment had been already developed. That “conventional” model was consisted of some analysis such as water radiolysis, ECP and others. However, the model did not consider an effect of TiO2 deposition and was one-dimensional simple model. Therefore, to evaluate ECP distribution in a reactor after TiO2 injection, the “newly developed” model was build: analyses integration, high-resolution and three-dimensional model. In this paper, the TiO2 deposition and water radiolysis analyses integrated into flow analysis were contained. Both the deposition and the radiolysis depend on flow in the RPV, so that these analyses were built into the computational fluid dynamics (CFD) analysis model for CFD code. The target plant type for the model was 1100 MWe-class BWR-5. The flow analysis was carried out at steady-state, assuming the TiO2 injection during the rated operation of the plant. Then the TiO2 deposition and the radiolysis analyses were conducted by transient calculations using the result of flow, and the three-dimensional and high resolution results were obtained.
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