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检索条件"任意字段=Conference on Data Analysis and Modeling for Process Control II"

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Intelligent Operational Optimization Method for Salt Lake Chemical Industrial processes Based on data-Driven modeling 18

Intelligent Operational Optimization Method for Salt Lake Ch...

引用

18th IEEE conference on Industrial Electronics and Applications, ICIEA 2023

作者： Liu, Diju Wang, Yalin Liu, Chenliang Wang, Kai Yuan, Xiaofeng Central South University School of Automation Changsha410083 China

ISBN: (纸本)9798350312201

The process control performance of the washing process heavily influences the quality of products in the Salt Lake Chemical industrial process, which is mainly determined by two subtasks: process modeling and operation optimization. For these two tasks, this paper first demarcates the modeling and optimization objectives of the washing process by profoundly analyzing the process mechanism and operating rules. To fully consider the working condition type and sampling time, a novel global multi-condition-aware transformer (GMCA-Former) network is proposed for the process modeling task. After that, the relatively accurate GMCA-Former is used to simulate the process state. Next, a hybrid operational optimization strategy based on case matching and NSGA-ii is applied to find the optimal operational parameter settings efficiently and stably. Notably, an event-triggered process model update mechanism is also designed to ensure the accuracy of the process model. Finally, the effectiveness of the proposed methods is verified in the actual industrial dataset. © 2023 IEEE.

关键词： Washing

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Intellectualized Operator Information Support System for NPP: Expert Systems and Dynamic Models

Intellectualized Operator Information Support System for NPP...

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2024 International conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Jharko, Elena Chernyshov, Kirill Abdulova, Ekaterina Laboratory Of Distributed Information Analytical And Control Systems V.A. Trapeznikov Institute Of Control Sciences Of The Russian Academy Of Sciences Moscow Russia Laboratory Of Identification Of Control Systems V.A. Trapeznikov Institute Of Control Sciences Of The Russian Academy Of Sciences Moscow Russia Laboratory Of Security Of Complex Systems V.A. Trapeznikov Institute Of Control Sciences Of The Russian Academy Of Sciences Moscow Russia

ISBN: (纸本)9798350395013

The article discusses an approach that combines expert systems and dynamic models in an intellectualized operator information support system (IOISS) for nuclear power plant units. The main goal of this approach is to provide operators with the most complete and accurate information for the efficient management of power units (PU). The main functions of the IOISS of NPP PUs are highlighted, and a path is proposed for their full-scale implementation based on the use of predictive dynamic modeling of PU parameters and expert systems (ES). The use of predictive dynamic modeling makes it possible to predict the behavior of a power unit based on available data and calculate optimal control parameters. ES, in turn, provides expert knowledge and specialist experience, allowing operators to make informed decisions and respond to possible emergencies. The structure of the ES, which is part of the IOISS and includes modules for data analysis, decision-making, and information visualization, is considered. All these components work together to ensure the efficient and reliable operation of NPPs. This approach to IOISS is the basis for developing upper-level systems for instrumentation and control systems of NPPs. It can significantly improve the safety and efficiency of power units and simplify operators' decision-making process. © 2024 IEEE.

关键词： Nuclear fuels

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Integrating Design Intelligence into Configuration Item Space for Robust Change Integrity 24

Integrating Design Intelligence into Configuration Item Spac...

引用

2024 7th International conference on Computer Information Science and Artificial Intelligence, CISAI 2024

作者： Zhan, Hongfei Meng, Xu Zhang, Xinyuan Shanghai Aircraft Design and Research Institute Shanghai China

ISBN: (纸本)9798400707254

The development process of complex products is typically characterized by high integration across multiple domains and disciplines. Design changes are an integral part of this process, and effective management of frequent design changes is fundamental to ensuring product quality and safety. Ensuring the integrity of design changes is critical and has become a pressing issue in the development of complex products. Leveraging design intelligence, this paper proposes a method for modeling change integrity integrated with the Configuration Item (CI) space. Using the CI space dataset model, we establish rules for checking the integrity of design changes, providing a procedural paradigm for determining change integrity. By integrating design intelligence techniques such as predictive analytics and machine learning, our model enhances the accuracy and efficiency of identifying impacted documents and CIs. This approach improves configuration control capabilities for complex products and ensures quality and safety throughout the development process. Finally, through specific change examples, data analysis, and comparisons, we validate the effectiveness of the proposed model in maintaining design integrity and supporting informed decision-making. © 2024 Copyright held by the owner/author(s).

关键词： data integrity

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data-based modeling and control of nonlinear process systems using sparse identification: An overview of recent results

Data-based modeling and control of nonlinear process systems...

引用

2023 AIChE Annual Meeting

作者： Abdullah, Fahim Christofides, Panagiotis D. Department of Chemical and Biomolecular Engineering University of California Los AngelesCA90095-1592 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095-1592 United States

This paper discusses recent developments in the data-based modeling and control of nonlinear chemical process systems using sparse identification of nonlinear dynamics (SINDy). SINDy is a recent nonlinear system identification technique that uses only measurement data to identify model dynamical systems in the form of first-order nonlinear differential equations. In this work, the challenges of handling time-scale multiplicities and noisy sensor data when using SINDy are addressed. Specifically, a brief overview of novel methods devised to overcome these challenges are described, along with modeling guidelines for using the proposed techniques for process systems. When applied to two-time-scale systems, to overcome model stiffness, which leads to ill-conditioned controllers, a reduced-order modeling approach is proposed where SINDy is used to model the slow dynamics, and nonlinear principal component analysis is used to algebraically ''slave'' the fast states to the slow states. The resulting model can then be used in a Lyapunov-based model predictive controller with guaranteed closed-loop stability provided the separation of fast and slow dynamics is sufficiently large. To handle high levels of sensor noise, SINDy is combined with subsampling and co-teaching to improve modeling accuracy. The challenges of modeling and controlling large-scale systems using noisy industrial data are then addressed by using ensemble learning with SINDy. After summarizing the advances, a nonlinear chemical process is used to provide an end-to-end demonstration of process modeling using sparse identification with guidelines for chemical engineering practitioners. Finally, several future research directions for the incorporation of SINDy into process systems engineering are proposed. © 2023 Elsevier Ltd. All rights reserved.

关键词： Dynamics

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DIGITAL TWIN DEVELOPMENT FOR ADDITIVE MANUFACTURING

DIGITAL TWIN DEVELOPMENT FOR ADDITIVE MANUFACTURING

引用

2024 Pressure Vessels and Piping conference

作者： Park, Y. H. Love, A. Behseresht, S. Pastrana, O. Valdez Sakai, J. Univ New Mexico State Univ Mech & Aerosp Engn Dept Las Cruces NM 88003 USA

ISBN: (纸本)9780791888476

Additive manufacturing (AM) is considered as a transformative manufacturing technology due to its ability to create complex structures and reduce material waste. However, the AM technology also introduces many challenges such as poor surface quality and structural integrity. To address these issues, a novel approach known as a digital twin (DT) has emerged. A digital twin is a digital representation of a physical object or system that enables real-time monitoring and control of their behavior. This study introduces a hybrid physicalvirtual digital twin environment that combines a sensing-driven DT with a process simulation-driven DT. Specifically, we propose a hybrid digital twin environment (HDTE) customized for a fused deposition modeling (FDM) 3D printer. The HDTE is implemented into a 3D development platform. The present DT environment integrates external sensors to collect real-time data on temperature and location of the extruder on a 3D printer. It also includes a virtual AM process simulation using a commercial finite element software to predict temperature distribution and mechanical behavior during 3D printing. Position and temperature assessment experiments confirm the DT's ability to replicate component positions under static and dynamic conditions as well as temperature variation within the 3D printer. Comparative analysis between the simulation and experimental data shows excellent agreement and further validate the DT's capabilities. The present DT holds the potential for a significant advancement in 3D printing technology by offering real-time insights, predictive capabilities, and improved process control.

关键词： Additive manufacturing Thermo-mechanical analysis Damage FEA Johnson-Cook

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7th International conference on Aerospace System Science and Engineering, ICASSE 2023

7th International Conference on Aerospace System Science and...

引用

7th International conference on Aerospace System Science and Engineering, ICASSE 2023

ISBN: (纸本)9789819705498

The proceedings contain 22 papers. The special focus in this conference is on Aerospace System Science and Engineering. The topics include: A Review of Some Key Issues in CFD-Based Throughflow Simulation;influence of Multiple Parameters on the Efficiency of a Single Nozzle in a Heavy Gas Turbine Combustor;analysis of the Influence of Total Pressure Error on Air data Calibration;analysis of Impact Properties of Nanocomposites at Micron Scale;simulation Research on Air Distribution Optimization of Civil Aircraft Cabin Ventilation System;investigation of the 2-D Distribution Form of Bearing Stress in a Single-Bolt Single-Shear Metal-Composite Hybrid Joint;the Impact of Bleeding Slot Angles on the Performance of a Compressor;investigation into Provisions and Validation for Cockpit Smoke Evacuation on Civil Aircraft;numerical Investigation of Diffuser Curvilinear Meridional Shape on Centrifugal Compressor Stage Performance;modeling Method of Specimen Repair Techniques from Polymer Composite Material;process Approach as a Tool of the Knowledge-Intensive Industry Organization Management System;SysML-Based Approach for Functional Quantitative modeling of Civil Aircraft Systems;research on MagicGrid-Based Requirements Development process of Flight control System;airport Collaborative Decision-Making in Single Pilot Operations of Commercial Aircraft;Research on Capability Catalog Generation of UAV Intelligent System Based on DoDAF;research on the Contribution Rate of Shipboard Manned/Unmanned Aerial Vehicle Cooperative Operation Based on Wargame data Mining;cooperative Organization and Application Mechanism Based on Intention Environment Target for Maritime Ship-Aircraft Cooperation;LPV Robust Filter Based Fault Diagnosis Method for Aeroengine control System.

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The Use of Simulation modeling in Hospital Pharmacy Inventory Management 6

The Use of Simulation Modeling in Hospital Pharmacy Inventor...

引用

6th International conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Kritchanchai, Duangpun Supeekit, Tuangyot Chanpuypetch, Wirachchaya Department of Industrial Engineering Faculty of Engineering Mahidol University Nakhonpathom Salaya Thailand Faculty of Agro-Industry Chiang Mai University Samut Sakhon Thailand

Hospitals currently face numerous challenges in managing their pharmacy operations efficiently. While Business process Reengineering (BPR) has been proposed as a solution, its implementation in healthcare is more complex than in other industries. Healthcare professionals often struggle to identify problems and resist change. Simulation modeling is a technique that can visually present issues and facilitate user acceptance of changes. This paper systematically explores the application of discrete event simulation (DES) modeling in hospital pharmacy management. The specific problem of inefficient inventory control policies was analyzed and simulated using primary and secondary data from a tertiary care hospital case study in Thailand, focusing on a fast-moving drug called "Tear Natural Free (TNF)". The simulation revealed the current inefficient performance, highlighting various phenomena such as demand characteristics, inventory levels, and stock-outs in each pharmacy room. The simulation outputs were utilized to identify alternative scenarios for further analysis of the effects of changing the business process. The most suitable forecasting technique and inventory replenishment policy for this type of item were determined to be Croston's method and continuous review order-point, order-up-to-level (s, S) or min-max policy, respectively. Simulation modeling can serve as a valuable tool in identifying problems and improving business processes in hospital pharmacy management. © 2025 Elsevier B.V.. All rights reserved.

关键词： Inventory control

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modeling and Simulation of Engine Starting process 42

Modeling and Simulation of Engine Starting Process

引用

42nd Chinese control conference, CCC 2023

作者： Zhao, Zhen Yao, Min Ma, Mengqi College of Electrical Information and Automation Civil Aviation University of China Tianjin300300 China

ISBN: (纸本)9789887581543

On the basis of a component-level approach, mathematical and simulation models are created for various modules to examine the operation of the APU (Auxiliary Power Unit) and the ATS (Air Turbine Starter) in civil aircraft. For the static analysis, simulation is done at the design point and steady-state point, respectively. For the dynamic analysis, additional output power and output torque of ATS at various temperatures are derived. The error is allowable in comparison to the provided test data, demonstrating the viability and efficacy of the model. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Auxiliary power systems

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FedMSPC: A Federated Multivariate Statistical process control Framework For Privacy-Preserving process modeling Across Company Borders 1

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11th International conference on Mechatronics and control Engineering, ICMCE 2023

作者： Nguyen Duy, Du Gabauer, David Nikzad-Langerodi, Ramin Software Competence Center Hagenberg Hagenberg Austria

ISBN: (数字)9789819965236

ISBN: (纸本)9789819965229

The ongoing transition from a linear (produce-use-dispose) to a circular economy poses significant challenges to current state-of-the-art information and communication technologies. In particular, the derivation of integrated, high-level views on material, process, and product streams from (real-time) data produced along value chains is challenging for several reasons. Most importantly, sufficiently rich data is often available yet not shared across company borders because of privacy concerns which make it impossible to build integrated process models that capture the interrelations between input materials, process parameters, and key performance indicators along value chains. In the current contribution, we propose a privacy-preserving, federated multivariate statistical process control (FedMSPC) framework based on Federated Principal Component analysis (PCA) and Secure Aggregation to foster the incentive for closer collaboration of stakeholders along value chains. We tested our approach on two industrial benchmark data sets - SECOM and ST-AWFD. Our empirical results demonstrate the superior fault detection capability of the proposed approach compared to standard, single-party (Multiway) PCA. Furthermore, we showcase the possibility of our framework to provide privacy-preserving fault diagnosis to each data holder in the value chain to underpin the benefits of secure data sharing and federated process modeling. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Fault detection

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Design of Transportation Information Resource Systems Based on data Mining 2

Design of Transportation Information Resource Systems Based ...

引用

2nd IEEE International conference on Image processing and Computer Applications, ICIPCA 2024

作者： He, Kaini Shaanxi Railway Institute Railway Transportation Department Weinan714000 China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350360240

This study details data mining techniques in the design of transportation information system (TIS) database, which are widely used by transport companies in China. The objective is to examined how the information system is designed and operates. Association rules, which may identify common combinations of features that occur most often within a particular data set, are used with descriptive statistical approaches to evaluate data. The association rules were created using two different quantifier types: 'above average' and 'founded implication.' The analysis is shown with graphs and hypotheses as the outcomes. © 2024 IEEE.

关键词： Support vector machines Information resources System performance Optimization models Predictive models Planning Association rule learning Public transportation Load modeling Information systems

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