Academic literature on the topic 'Process monitoring (PM)'
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Journal articles on the topic "Process monitoring (PM)"
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Burr, Tom, Michael S. Hamada, John Howell, Misha Skurikhin, Larry Ticknor, and Brian Weaver. "Estimating Alarm Thresholds for Process Monitoring Data under Different Assumptions about the Data Generating Mechanism." Science and Technology of Nuclear Installations 2013 (2013): 1–18. http://dx.doi.org/10.1155/2013/705878.
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Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation dates to the 1920s with the Shewhart control chart; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of threshold estimation. One of the possible new PM roles involves PM residuals, where a residual is defined as residual = data − prediction. This paper reviews alarm threshold estimation, introduces model selection options, and considers a range of assumptions regarding the data-generating mechanism for PM residuals. Two PM examples from nuclear safeguards are included to motivate the need for alarm threshold estimation. The first example involves mixtures of probability distributions that arise in solution monitoring, which is a common type of PM. The second example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals.
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Agbenyo, Fauster, Wisdom N-Yil-Yari, and Bernard Affiik Akanpabadai Akanbang. "Stakeholder Perspectives on Participatory Monitoring and Evaluation in Educational Projects in Upper West Region, Ghana." Journal of Planning and Land Management 2, no. 1 (September 11, 2021): 50–64. http://dx.doi.org/10.36005/jplm.v2i1.34.
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The paper set out to outline the differences between conventional M&E and PM&E from the perspectives of stakeholders and assess their involvement as well as the benefits associated with PM&E in two districts: Nadowli-Kaleo and Daffiama-Bussie-Issa in the Upper West Region, Ghana. The paper employed multi-stage, simple random and purposive sampling methods in identifying respondents for interviews. Key informant interviews were used to collect data. Thematic and qualitative content analysis of participants’ voices were used in analysing the data. Findings reveal that PM&E gives primary stakeholders power and control over project execution and taking actions on monitoring results. However, it emerged that the youth and women were not fully involved in the process, some beneficiaries have limited capacity and understanding of their roles in the PM&E process and their involvement is limited to ad hoc approaches due to resource constraints. The study concludes that despite its implementation challenges, PM&E has an edge over orthodox M&E in enhancing effective implementation of educational projects. The paper recommends education of and capacity building for beneficiaries on their roles in the PM&E process to enable them more actively and meaningfully participate in it. Policy decision-makers should make conscious efforts to timely free more resources to the monitoring teams to facilitate their work. The monitoring team should also make frantic efforts to engage the youth and women to achieve the right level of participation in the process.
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Morita, Maiko, Ikuo Arizono, Ippei Nakase, and Yasuhiko Takemoto. "Economical operation of the C pm control chart for monitoring process capability index." International Journal of Advanced Manufacturing Technology 43, no. 3-4 (September 16, 2008): 304–11. http://dx.doi.org/10.1007/s00170-008-1703-2.
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Benabbas, Aboubakr, Martin Geißelbrecht, Gabriel Martin Nikol, Lukas Mahr, Daniel Nähr, Simon Steuer, Gabriele Wiesemann, Thomas Müller, Daniela Nicklas, and Thomas Wieland. "Measure particulate matter by yourself: data-quality monitoring in a citizen science project." Journal of Sensors and Sensor Systems 8, no. 2 (November 5, 2019): 317–28. http://dx.doi.org/10.5194/jsss-8-317-2019.
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Abstract. The concern about air quality in urban areas and the impact of particulate matter (PM) on public health is turning into a big debate. A good solution to sensitize people to this issue is to involve them in the process of air quality monitoring. This paper presents contributions in the field of PM measurements using low-cost sensors. We show how a low-cost PM sensor can be extended to transfer data not only over Wi-Fi but also over the LoRa protocol. Then, we identify some of the correlations existing in the data through data analysis. Afterwards, we show how semantic technologies can help model and control sensor data quality in an increasing PM sensor network. We finally wrap up with a conclusion and plans for future work.
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Lou, Mengqi, Liguo Zhang, Feng Xie, Jianzhu Cao, Jiejuan Tong, Weirong Liu, and Yong Wang. "Design of the Online Gross γ Monitoring Instrument at the Exit of the Helium Purification System in HTR-PM." Science and Technology of Nuclear Installations 2018 (November 1, 2018): 1–12. http://dx.doi.org/10.1155/2018/5808352.
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After the successful construction and operation experience of the 10 MW high-temperature gas-cooled reactor (HTR-10), a high-temperature gas-cooled pebble-bed modular (HTR-PM) demonstration plant is under construction in Shidao Bay, Rongcheng City, Shandong province, China. An online gross γ monitoring instrument has been designed and placed at the exit of the helium purification system (HPS) of HTR-PM and is used to detect the activity concentration in the primary circuit after purification. The source terms in the primary loop of HTR-PM and the helium purification process were described. The detailed configuration of the gross γ monitoring instrument was presented in detail. The Monte Carlo method was used to simulate the detection efficiency of the monitoring system. Since the actual source terms in the primary loop of HTR-PM may be different than the current design values, a sensitivity analysis of the detection efficiency was implemented based on different relative proportions of the nuclides. The accuracy and resolution of the NaI(Tl) detector were discussed as well.
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Seo, SungChul, Choongki Min, Madeline Preston, Sanghoon Han, Sung-Hyuk Choi, So Young Kang, and Dohyeong Kim. "Ambient PM Concentrations as a Precursor of Emergency Visits for Respiratory Complaints: Roles of Deep Learning and Multi-Point Real-Time Monitoring." Sustainability 14, no. 5 (February 25, 2022): 2703. http://dx.doi.org/10.3390/su14052703.
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Despite ample evidence that high levels of particulate matter (PM) are associated with increased emergency visits related to respiratory diseases, little has been understood about how prediction processes could be improved by incorporating real-time data from multipoint monitoring stations. While previous studies use traditional statistical models, this study explored the feasibility of deep learning algorithms to improve the accuracy of predicting daily emergency hospital visits by tracking their spatiotemporal association with PM concentrations. We compared the predictive accuracy of the models based on PM datasets collected between 1 December 2019 and 31 December 2021 from a single but more accurate air monitoring station in each district (Air Korea) and multiple but less accurate monitoring sites (Korea Testing & Research Institute; KTR) within Guro District in Seoul, South Korea. We used MLP (multilayer perceptron) to integrate PM data from multiple locations and then LSTM (long short-term memory) models to incorporate the intrinsic temporal PM trends into the learning process. The results reveal evidence that predictive accuracy is improved from 1.67 to 0.79 in RMSE when spatial variations of air pollutants from multi-point stations are incorporated in the algorithm as a 9-day time window. The findings suggest guidelines on how environmental and health policymakers can arrange limited resources for emergency care and design ambient air monitoring and prevention strategies.
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Stefanovic, Nenad, and Dusan Stefanovic. "Supply chain performance measurement system based on scorecards and web portals." Computer Science and Information Systems 8, no. 1 (2011): 167–92. http://dx.doi.org/10.2298/csis090608018s.
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Successful supply chain management becomes essential for the ultimate success of corporations. Companies today seek an effective performance measurement (PM) system to maximize the bottom line. Unfortunately, performance measurement in the supply-chain field has not kept pace with today?s world of interdependent business relationships. What companies need is a new PM system that unifies different business elements, concepts, technologies and tools. In this paper, the architecture of such a pervasive PM system is introduced. The main system elements such as process model, metrics and data warehouse are described. Finally, a specialized PM web portal which enables proactive performance monitoring and fosters the improvement and optimization is presented.
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Elkhawaga, Ghada, Mervat Abuelkheir, Sherif I. Barakat, Alaa M. Riad, and Manfred Reichert. "CONDA-PM—A Systematic Review and Framework for Concept Drift Analysis in Process Mining." Algorithms 13, no. 7 (July 3, 2020): 161. http://dx.doi.org/10.3390/a13070161.
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Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business process changes while being analysed is denoted as Concept Drift. Its analysis is concerned with studying how a business process changes, in terms of detecting and localising changes and studying the effects of the latter. Concept drift analysis is crucial to enable early detection and management of changes, that is, whether to promote a change to become part of an improved process, or to reject the change and make decisions to mitigate its effects. Despite its importance, there exists no comprehensive framework for analysing concept drift types, affected process perspectives, and granularity levels of a business process. This article proposes the CONcept Drift Analysis in Process Mining (CONDA-PM) framework describing phases and requirements of a concept drift analysis approach. CONDA-PM was derived from a Systematic Literature Review (SLR) of current approaches analysing concept drift. We apply the CONDA-PM framework on current approaches to concept drift analysis and evaluate their maturity. Applying CONDA-PM framework highlights areas where research is needed to complement existing efforts.
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Mei, Jiangyuan, Jian Hou, Hamid Reza Karimi, and Jiarao Huang. "A Novel Data-Driven Fault Diagnosis Algorithm Using Multivariate Dynamic Time Warping Measure." Abstract and Applied Analysis 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/625814.
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Process monitoring and fault diagnosis (PM-FD) has been an active research field since it plays important roles in many industrial applications. In this paper, we present a novel data-driven fault diagnosis algorithm which is based on the multivariate dynamic time warping measure. First of all, we propose a Mahalanobis distance based dynamic time warping measure which can compute the similarity of multivariate time series (MTS) efficiently and accurately. Then, a PM-FD framework which consists of data preprocessing, metric learning, MTS pieces building, and MTS classification is presented. After that, we conduct experiments on industrial benchmark of Tennessee Eastman (TE) process. The experimental results demonstrate the improved performance of the proposed algorithm when compared with other classical PM-FD classical methods.
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Carrari, Elisa, Alessandra De Marco, Andrea Laschi, Ovidiu Badea, Laurence Dalstein-Richier, Silvano Fares, Stefan Leca, et al. "Economic and Life Cycle Analysis of Passive and Active Monitoring of Ozone for Forest Protection." Environments 8, no. 10 (October 9, 2021): 104. http://dx.doi.org/10.3390/environments8100104.
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At forest sites, phytotoxic tropospheric ozone (O3) can be monitored with continuously operating, active monitors (AM) or passive, cumulative samplers (PM). For the first time, we present evidence that the sustainability of active monitoring is better than that of passive sensors, as the environmental, economic, and social costs are usually lower in the former than in the latter. By using data collected in the field, environmental, social, and economic costs were analyzed. The study considered monitoring sites at three distances from a control station in Italy (30, 400, and 750 km), two forest types (deciduous and Mediterranean evergreen), and three time windows (5, 10, and 20 years of monitoring). AM resulted in more convenience than PM, even after 5 years, in terms of O3 depletion, global warming, and photochemical O3 creation potential, suggesting that passive monitoring of ozone is not environmentally sustainable, especially for long time periods. AM led to savings ranging from a minimum of EUR 9650 in 5 years up to EUR 94,796 in 20 years in evergreen forests. The resulting social cost of PM was always higher than that of AM. The present evaluation will help in the decision process for the set-up of long-term forest monitoring sites dedicated to the protection of forests from O3.
Dissertations / Theses on the topic "Process monitoring (PM)"
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Tuloup, Corentin. "Process and structural health monitoring of Polymer-Matrix Composites (PMC) using embedded piezoelectric transducers." Thesis, Compiègne, 2020. https://bibliotheque.utc.fr/Default/doc/SYRACUSE/2020COMP2593.
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Ce travail novateur étudie l'intérêt d'intégrer des transducteurs piézoélectriques (à base céramique et/ou polymère) au sein de matériaux composites à matrice organique (CMO) pour effectuer une surveillance en temps réel et in-situ de leur processus de fabrication (Process Monitoring PM) ainsi que de leur vie en service (Structural Health Monitoring SHM). Pour ce faire, les transducteurs piézoélectriques ont été intégrés au cœur des empilements fibreux suivant une méthodologie innovante développée au sein de l’équipe de recherche « Matériaux et Surfaces » du laboratoire Roberval. Le système de fabrication par infusion de résine liquide (LRI) utilisé (campagne en PM) ainsi que les échantillons résultants testés mécaniquement (campagne en SHM) ont été multi-instrumentés à l'aide de plusieurs dispositifs de Contrôle Non Destructif (CND : Emission Acoustique (EA), Thermographie Infrarouge (TIR), Corrélation d’Images Numériques (CIN), etc.) afin d’établir des couplages multi-physiques entre les signaux des techniques CND externes et la signature interne (capacité électrique) provenant des transducteurs intégrés au cœur de la matière. En PM, la sensibilité des transducteurs piézocéramiques (PZT) aux diverses étapes clés du processus LRI (passage du front, imprégnation, arrêt de l’injection, transitions physico-chimiques de réticulation et taux de consolidation) réalisé à divers taux de durcisseur ainsi que leur aptitude à la détection de défauts de fabrication ont montré un fort potentiel digne d’une future utilisation à l’échelle industrielle. En SHM, après une vérification de la non-intrusivité des transducteurs à base céramique et polymère intégrés au cœur des échantillons de tests mécaniques, les transducteurs polymères ont permis une évaluation en temps réel de l’état triaxial de déformation et de la perte de rigidité subis par le CMO hôte durant son chargement mécanique. En revanche, malgré un seuil de non fonctionnement (NWT) lié à la fragilité de leur matériau constitutif, les transducteurs piézocéramiques ont montré une forte sensibilité à la détection et au suivi de l’endommagement en temps réel dès lors qu’ils sont positionnésintelligemment vis-à-vis de la sollicitation mécanique. Ces travaux de thèse se sont achevés sur une première tentative visant à transposer les connaissances acquises en PM et SHM des transducteurs piézoélectriques in-situ d'une échelle 2D « laboratoire » à une échelle structurelle 3D plus proche des réalités industrielles. La fabrication multi-instrumentée d’une structure CMO de type raidisseur « Omega » intégrant 14 transducteurs piézoélectriques (PZT ou copolymère P(VDF-TrFE)) et renforcée en épaisseur par un fil en carbone a permis de confirmer les aptitudes PM du PZT précédemment mises en évidence, et a montré une différence entre la manière dont les signaux de capacité électrique du PZT et des copolymères réagissent à l'ensemble du processus de fabricationThis innovative work studies the interest of integrating piezoelectric transducers (ceramic and/or polymer-based) within Polymer- Matrix Composite materials (PMC) to perform real-time and in-situ monitoring of their manufacturing process (Process Monitoring PM) as well as their lifespan (Structural Health Monitoring SHM). To do this, the piezoelectric transducers were integrated into the heart of the fibrous stacks using an innovative methodology developed within the "Materials and Surfaces" research team at the Roberval laboratory. The Liquid Resin Infusion (LRI) manufacturing system used (PM campaign), as well as the resulting samples tested mechanically (SHM campaign), were multi-instrumented using several Non-Destructive Testing devices (NDT: Acoustic Emission (AE), Infrared Thermography (IRT), Digital Image Correlation (DIC), etc.) in order to establish multi-physical couplings between the signals of external NDT techniques and the internal signature (electrical capacitance) coming from the transducers integrated into the heart of the material. In PM, the piezoceramic (PZT) transducers were found to be sensitive to the various key steps of the LRI process (flow front passing, impregnation, end of injection, chemo-physical transitions during curing and associated consolidation rates) achieved at different hardener rates, and able to detect manufacturing defects. These results showed great potential, worthy of future use on an industrial scale. In SHM, after verification of the non-intrusiveness of the ceramic and polymer-based transducers integrated into the heart of the mechanical test specimens, the polymer transducers allowed a real-time evaluation of the triaxial strain state and the rigidity loss experienced by the host PMC during its mechanical loading. However, despite a Non-Working Threshold (NWT) linked to the brittleness of their constitutive material, the piezoceramic transducers have shown a high sensitivity to the detection and monitoring of damage in real-time when they are positioned intelligently with respect to the mechanical stress. These thesis works ended with a first attempt aimed at transposing the knowledge acquired on PM and SHM of in-situ piezoelectric transducers from a 2D “laboratory” scale to a 3D structural one closer to industrial realities. The multi-instrumented manufacturing of an “Omega” stiffener PMC structure integrating 14 piezoelectric transducers (PZT and P(VDF-TrFE) copolymer) and reinforced through-the-thickness by a carbon tuft thread allowed confirming the previously evidenced PM abilities of the PZT, and showed a difference between how the electrical capacitance signals of PZT and copolymers react to the whole manufacturing process
Book chapters on the topic "Process monitoring (PM)"
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Zhang, Kai. "KPI-based PM-FD methods for static processes." In Performance Assessment for Process Monitoring and Fault Detection Methods, 61–89. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-15971-9_4.
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Zhang, Kai. "KPI-based PM-FD methods for dynamic processes." In Performance Assessment for Process Monitoring and Fault Detection Methods, 109–19. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-15971-9_6.
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Zhang, Kai. "KPI-based PM-FD methods for steady-state dynamic processes: Two DPLS-based methods." In Performance Assessment for Process Monitoring and Fault Detection Methods, 91–107. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-15971-9_5.
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Holopainen, Riikka Maarit, Mervi Niskanen, and Sari Rissanen. "Management Accounting and Profitability in Private Healthcare SMEs." In Research Anthology on Small Business Strategies for Success and Survival, 631–47. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-9155-0.ch032.
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The purpose of this article is to examine the management control practices in small and medium-sized health care enterprises (SMEs). Previous studies suggest that there are often few, if any, comprehensive management control systems (MCS) or there is lack of systematic management accounting or performance management (PM) monitoring in even fairly large SMEs. The first contribution of this article is to present nine years of financial data of micro companies. The data itself is quite unique and not open data for everyone. On one hand, it gives further information about diverse and complex combinations of the profitability process in the small companies and how the MA systems affect it. Based on the contingency theory conception, this article finds that the management accounting practices such as a budgeting system or increased cost knowledge of the company influence the company's performance. Further, some of the contextual factors such as size and age of the company affected the company's performance in this study.
Conference papers on the topic "Process monitoring (PM)"
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Xie, Feng, Wenqian Li, Zhihui Li, Jianzhu Cao, Hong Li, Jiejuan Tong, and Haitao Wang. "Design of the Process and Effluent Radiation Monitoring System of HTR-PM." In 2016 24th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/icone24-61008.
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The process and effluent radiation monitoring system can provide information about kinds of the radionuclide and activity concentrations, which is indispensable, important, and peculiar for a nuclear power station compared to a regular thermal power station. On the basis of knowledge about pressurized water reactors (PWRs) and high temperature gas-cooled reactors (HTGRs), the process and effluent radiation monitoring system of HTR-PM has been designed. It mainly contains several monitoring channels for concerned process systems, certain important areas, and gaseous and liquid effluents. For the coolant is helium and spherical fuel elements containing tristructural isotropic (TRISO) coated particles are adopted in HTR-PM, the source terms are different from those of PWRs. Not only fission or activation products in the gaseous or liquid form are monitored, but also the radioactive dust in the primary loop is sampled for analysis. The tritium (H-3) and carbon-14 (C-14) are taken a key consideration, which will be sampled in the primary loop, in certain important areas, in the secondary loop, and in the gaseous effluent in the stack. Design features of the process and effluent radiation monitoring system of HTR-PM are introduced and discussed compared to those of PWRs.
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Li, Wenqian, Chuan Li, Jianzhu Cao, and Feng Xie. "Design of the Important Area Airborne Radioactivity Monitoring System and Calculation of the Alarm Threshold of HTR-PM." In 2018 26th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icone26-81232.
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Unlike the conventional pressurized water reactor (PWR), helium is adopted as the coolant in the high-temperature gas-cooled reactor pebble-bed module (HTR-PM). Due to the leakage of the primary coolant, in certain process rooms and some important areas, the airborne radioactivity should be monitored for the purpose of personnel radiation protection and emergency control. The system executing above function in HTR-PM is called important area airborne radioactivity monitoring system. This system consists of five separate monitoring channels, in which online and/or sampling monitoring devices will be included. For radiation monitoring system of a reactor, the calculation and setting of alarm thresholds for online devices is an important issue. The set of alarm thresholds requires not only accurate calculation but also feedback from actual operational experience. The design of the high-temperature reactor is different from the PWR, so the set of the alarm thresholds need special considerations. Based on the calculation of source terms and production-removal model, the theoretical radioactive levels of the sampled gases of all the online monitors were calculated and the alarm thresholds adopted in the current design are presented in this paper. The set of the alarm thresholds takes the influences of the background and other factors into account. This paper provides a method for calculating and determining the alarm thresholds of the radiation monitoring system, which can provide references for other nuclear power plants.
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Faure, S. P., L. Mercier, P. Didier, R. Roux, J. F. Coulon, S. Garel, J. Trenit, H. Buard, and F. Razan. "Laser Sintering Process Analysis: Application to Chromium-Cobalt Alloys for Dental Prosthesis Production." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82108.
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Rapid prototyping is an effective way to build prototypes. This process, now called AM (Additive Manufacturing), is suited to realize functional single part or for small batch production. Evolution of AM is now in the way of serial production. In the field of medical applications and more precisely dentistry, AM is a way of increasing numbers of elements produced compared to classic production by lost wax casting. To increase production quality, it is necessary to have a high monitoring and control of process and properties of production. In the case of AM using (DMLS: Direct Metal Laser Sintering), a lot of parameters can have an influence on the elements production quality such as powders quality, laser behavior or sintering time… The goal of this work is to study the serial production quality using a DMLS system (Phenix System PM100). This system is used in production of cobalt-chromium elements for dental applications. The study was done on a period of 6 months with recording results of almost 120 productions and was focused on a quantity of around 7000 dental elements produced. In a first part, number of elements per production, room temperature and hygrometry, powder reloading, maintenance, production stops and new operators are recorded. Material properties of some elements produced such as dimensional properties, density, porosity and crystallographic phases are monitored. Materials analysis has led to ensure the elements quality produced by the Phenix system and results are discussed in this work. In a second part, we focused on the production analysis with the recorded data. Analysis leads to define 2 ratios: production ratio RP defined as [Elements Number]/ [Productions Number] and the efficiency production PE defined as the ratio RP/[Stopped production number]. By calculating RP and PE values with collected data on the Phenix system, a PM 100 efficiency production modeling has been established. The PM 100 production modeling can help to understand that increasing the production ratio RP value leads to have efficiency production PE high variation. On another hand, collecting production parameters leads to increase production efficiency.
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Cluever, Joseph, Thomas Esselman, and Sam Harvey. "Value-Based Bayesian Optimization of Preventive Maintenance Programs." In ASME 2018 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/pvp2018-84832.
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The EPRI Preventive Maintenance Basis Database (PMBD) has become a standard in the industry to develop, validate, or examine the impact of custom changes to maintenance strategies for common power plant equipment. The PMBD provides failure modes and an indication of frequency of occurrence. Recent feedback from PMBD users has made it clear that including a “Cost Module” to work with PMBD data would be a useful addition to the PMBD program and allow users to view the cost impacts associated with alternate custom maintenance strategies. This paper presents a methodology for the merging of maintenance information extracted from PMBD with cost estimates and additional expert-provided reliability data to estimate a maintenance cost distribution. Additional expert information includes missing data and PM type: monitoring, wear-rate reducing (e.g. oil change), or life-restoring (e.g. refurbishment). The cost distribution is calculated via Monte Carlo simulation and is dependent on the PM plan currently considered. Value-based optimization of the PM plan is performed through Bayesian optimization of the mean PM cost by varying the various PM frequencies. Bayesian optimization iteratively uses Gaussian Process Regression (GPR) to fit a non-parametric meta-model to a noisy objective function. As a part of GPR it is necessary to fit a covariance function that describes the spatial correlation or smoothness of the objective cost function. The meta-model with the covariance function effectively produces a built-in sensitivity analysis for the optimization as well.
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Lou, Mengqi, Wenqian Li, Feng Xie, Jianzhu Cao, Liqiang Wei, Jiejuan Tong, and Jiaji Kong. "Design of the Sampling Measurement and Radiochemistry Lab in the Nuclear Island of HTR-PM." In 2018 26th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icone26-81701.
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Radiation monitoring system is very important to the safe operation of the nuclear power plant. The radiation monitor, including the on-line type and the off-line type, can provide the radioactive level for a given system, certain areas, or unique substance promptly. However, as a supplementary method, the sampling measurement can supply more accurate information about the source term. In this paper, we present the design of the sampling measurement in the nuclear island of HTR-PM. The sampling measurement contains the helium sampling from the primary coolant, the radioactive dust sampling from the primary loop, the liquid sampling from the tritiated water and some process systems, the gas sampling from certain areas, etc. The frequency of the sampling measurement depends on regulatory requirements and actual operational demands. The control values of the samples are settled on the basis of the source term analysis and regulatory requirements. The radiochemistry lab has been designed to meet the requirement of the sampling measurement, in which the main instruments include a NaI γ spectrometer, two high-purity germanium γ spectrometers, a four-channel ultralow background α/β analyzer, and a low background liquid scintillation counter. The characteristics of these instruments will be described in details in the paper.
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Reid, Michael, and Bernie Cook. "The Application of Smart, Connected Power Plant Assets for Enhanced Condition Monitoring and Improving Equipment Reliability." In ASME 2016 Power Conference collocated with the ASME 2016 10th International Conference on Energy Sustainability and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/power2016-59189.
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The U.S. electric utility industry continues to undergo dramatic change due to a number of key trends and also prolonged uncertainty. These trends include: • Increasing environmental regulations uncertainty • Natural gas supply uncertainty and price • Economic / decoupling of electricity demand growth from GDP • Aging coal and nuclear generation fleet / coal retirements • Aging workforce • Increasing distributed energy resources • Increasing customer expectations The transformation ultimately demands significant increases in power plant generation operating capabilities (e.g. flexibility, operating envelop, ramp rates, turn-down etc.) and higher levels of equipment reliability, while reducing O&M and capital budgets. Achieving higher levels of equipment reliability and flexibility, with such tightening budget and resource constraints, requires a very disciplined approach to maintenance and an optimized mix of the following maintenance practices: • Reactive (run-to-failure) • Preventive (time-based) • Predictive (condition-based) • Proactive (combination of 1, 2 and 3 + root cause failure analysis) Many U.S. electric utilities with fossil generation have adopted and implemented elements of an equipment reliability process consistent with Institute of Nuclear Power Operations (INPO) AP-913. The Electric Power Research Institute has created a guideline modeled from the learnings of AP-913, that consists of six key sub-processes [1]: 1. Scoping and identification of critical components (identifying system and component criticality) 2. Continuing equipment reliability improvement (establishing and continuously improving system and component maintenance bases) 3. Preventive Maintenance (PM) implementation (implementing the PM program effectively) 4. Performance monitoring (monitoring system and component performance) 5. Corrective action 6. Life cycle management (long-term asset management) A significant proportion of Duke Energy’s coal fleet is of an age where individual components have reached their design intent end-of-life thereby creating an increased need for performance monitoring. Until recent times this was largely performed by maintenance technicians with handheld devices. This approach does not allow regular data collection for trending and optimization of maintenance practices across the fleet. Significant and recent advances in sensor technology, microprocessors, data acquisition, data storage, communication technology, and software have enabled the transformation of critical power plant assets such as steam turbines, combustion turbines, generators, transformers, and large balance-of-plant equipment into smart, connected power plant assets. These enhanced assets, in conjunction with visualization software, provide a comprehensive conditioning monitoring solution that continuously acquires sensory data and performs real time analysis to provide information and insight. This advanced condition monitoring capability has been successfully applied to obtain earlier detection of equipment issues and failures and is key to improving overall equipment reliability. This paper describes an approach by Duke Energy to create and apply smart, connected power plant assets to greatly enhance its fossil generation continuous condition monitoring capabilities. It will discuss the value that is currently being realized and also look at future possibilities to apply big data and analytics to enhance information, insight, and actionable intelligence.
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Alexander, Chris, and Joe Frey. "Use of Analytical and Experimental Monitoring Techniques in Assessing the Performance of a Cold Reheat Steam Line." In ASME 2007 Pressure Vessels and Piping Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/pvp2007-26079.
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After a catastrophic failure that occurred in a 30-inch diameter cold reheat (CRH) steam line at the W. A. Parish Plant, Texas Genco requested that Stress Engineering Services, Inc. (SES) assist in determining the cause of the failure. The incident occurred at approximately 12:10 PM on July 15, 2003 and resulted in a catastrophic failure that scattered components around the plant in a radius of 1,200 feet. Reliant Resources and Texas Genco conducted their own failure investigation that involved metallographic examinations, inspection of the fracture surfaces, review of operating conditions at the time of failure, and studies related to the weld profile of the CRH line. Stress Engineering Services’ efforts included studies using computational fluid dynamics (CFD) to address how droplet sizes from the attemperator might impact downstream behavior of the piping system. Follow-on work involved conducting a mock-up testing as well as field monitoring using high temperature strain gages, accelerometers, and thermocouples. The data obtained from the field monitoring efforts, along with process data provided by Texas Genco, were used to perform finite element analyses. The finite element work involved the calculation of static stresses as well as transient stresses generated by cycling of the attemperator (thermal stresses) and vibration of the line (mechanical stresses). Fracture mechanics was used to determine the times required for crack initiation and propagation to failure. The analysis and monitoring efforts clearly demonstrated the operating conditions that were required to produce the failure. Additionally, the failure reinforced the importance of regular inspection of piping systems; even those high energy piping systems such as the cold reheat lines not normally associated with catastrophic failures.
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Ismail, D. "Integrated Process Safety Tools for Managing Risk of Abnormal Operations Condition in Medco E&P." In Digital Technical Conference. Indonesian Petroleum Association, 2020. http://dx.doi.org/10.29118/ipa20-f-233.
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Process safety is paramount for the oil and gas industry including Medco E&P. Process Safety is essential to prevent major incidents that may have significant impacts in terms of economic loses, environmental damage, and even human loss. Having a strong Asset and Operating integrity programs is a key to carrying out a strong process safety in day-to-day operations. One element in asset and operations integrity that contributes to delivering a safe operations is managing abnormal operation conditions. Abnormal operation condition is defined as operations with process/system/equipment anomaly because they are outside the safe operating limit (SOL), safety critical equipment (SCE) performance degradation, SCE integrity failure, and disable safety protected function. In Medco E&P, abnormal operations risk have been assessed and managed by several tools or systems such as Safety Critical Element Abnormal Risk Assessment (SCEARA), Integrated Anomaly Alert Notification (IAAN) and SCE Preventive and Corrective Maintenance (SCE PM & CM) deferment process. These tools are made as an effort in case of continuous operations under abnormal conditions is intended by minimizing residual risk to a tolerable level. These tools are implemented by online system in Medco E&P’s enterprise resource planning, known as Business Process Management (BPM). The findings reported from the audit and self-assessment showed that it is perplexing to monitor and track between the correlated systems. This later encouraged the integration of the above tools for better abnormal operation risk management. The integration of the system then introduced as Integrated Process Safety Tools. The Integrated Process Safety Tools adds values to the management of abnormal conditions by reducing overlapping processes in the business process flow, facilitating monitoring and mitigation control, and aligning the SCE deviation mitigation periods based on risks; ranging from report initiation, work order planning until deferment processes and also clear commitment to complete abnormality. Integrated Process Safety Tools are designed to be one of the foundations in building awareness and culture of Process Safety within the Company. This paper shares the experience in managing abnormal operation condition in Medco E&P offshore operations assets both surface facility and subsurface facility that associated with Safety Critical Equipment (SCE) and its enhancement through The Integrated Process Safety Tools. The Integrated Process Safety Tools adds values to the management of abnormal conditions by reducing overlapping processes in the business process flow, simplify monitoring and mitigation control, and aligning the SCE deviation mitigation periods based on risks; ranging from report initiation, work order planning until deferment processes, also clear commitment to complete abnormality.
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Sun, Lijian, Steven Lei, Hsuan-Tsung Hsieh, Yitung Chen, and Darrell W. Pepper. "An Integrated, Near Real-Time, Web-Based Data Acquisition and Management System for Air Quality Prediction for Las Vegas Valley, Nevada." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-42041.
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Clark County, Nevada has been criticized by US Environmental Protection Agency (US EPA) for its un-attainment air quality problem for particulate matters (PM 10 and PM 2.5) and ozone (O3) and carbon monoxide (CO). The Department of Air Quality Management (DAQM), Clark County, the regulatory and enforcement agency, is required by the US EPA to measure and report to the public the impact of aeroallergens as well as visibility and haze issues. From the long-term observation, air quality in the Las Vegas Valley is also influenced by those pollution from the neighboring states, currently around 30 monitoring stations through out the county have been in service for years to continuously monitor meteorological condition and provide valuable air quality information to the public in a timely fashion. Since the existing monitoring system was not designed to collect and process large amount of data set at a short time period, the agency cannot flexibly acquire higher resolution data sets as well as any non-scheduled data collection. Meanwhile, the much-needed data presentation and reporting features were not considered for the past. To ensure that Clark County will reach and maintain attainment of all federal air quality standards, the Nevada Center for Advanced Computational Methods (NCACM) at University of Nevada, Las Vegas (UNLV) is required by the DAQM to design a new system that can provide a multi-function data acquisition and management system. By characterized the deficiencies in the existing system, the NCACM redesign the current system that will provide a web-based work environment with new communication, model simulation and database management modules. More remote control capabilities are also included in the new system. The application will be more scalable, flexible and maintainable. The system is defined into four distinct tiers, data acquisition, data repository, data analysis and forecasting and data presentation tiers. After the 9–11 terrorist attacks, emergency response for any major cities around the country becomes a vital issue for homeland security. Through the timely data acquisition support, the system can return high-resolution data from monitoring stations for efficient model simulation. While continuously meteorological data feeding through the network, the NCACM’s newly configured Beowulf PC-clustering system calculates the possible transportation scenario around the valley and returns the best emergency scenario analysis.
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Zar Soe, Thin, Anucha Leelaratsameephanit, Phanuwat Jitputti, Sayan Charoensook, Alongkorn Rodthip, Sathit Chitkla, Apichai On-Dam, and Perapon Sirijitt. "The Achievement of Resource Optimisation on Lean Remote Wellhead Platform Visit with Collaborative 52 Weeks Plan." In Offshore Technology Conference Asia. OTC, 2022. http://dx.doi.org/10.4043/31426-ms.
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Abstract To survive in oil and gas industry, Operating Expenditure (OPEX) must be well controlled for profit maximization. One of the most resource-utilizing activities in Zawtika offshore field is remote wellhead platform (WHP) visit which was previously bi-weekly for operations activities, maintenance activities such as preventive maintenance (PM), etc., inspection activities like flowline erosion monitoring and wells annulus pressure monitoring, thereby high Marine Gas Oil (MGO) consumption due to vessel trips/routes and increased in manpower utilization. Currently, Zawtika Offshore field has a main platform called Zawtika Processing and Living Quarter Platform (ZPQ) and 10 remote wellhead platforms (WHPs). When it is considered for future, there will be more remote wellhead platforms (WHPs) which will increase more OPEX for new phases. To tackle this, this paper describes that Myanmar Asset Zawtika launched a LEAN (Lean Six Sigma) initiative based on safely and cost-effectively reducing the frequency of remote wellhead platforms (WHP) visits, using collaborative 52 week planning to lessen OPEX cost from MGO consumption and manpower requirements as well as maintaining Zawtika Reliability and Asset Integrity (RAI) with the view of achieving resource optimization. This paper also illustrates the effective planning process across multiple functions/disciplines within different sessions/departments and at various locations called 52 weeks plan incorporating with "Integrated Operation Plan (IOP)" guideline established for the first time for Zawtika offshore field to help optimize the resources and activities plan of individual field or asset by ensuring the safety while sustaining the integrity. This paper also outlines the reduction in Greenhouse Gas (GHG) calculated back from MGO reduction which is one of PTTEP strategies for Sustainable Development (SD).