The Experts below are selected from a list of 53037 Experts worldwide ranked by ideXlab platform
Chunhua Yang - One of the best experts on this subject based on the ideXlab platform.
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Temperature Measurement Method for Blast Furnace Molten Iron Based on Infrared Thermography and Temperature Reduction Model.
Sensors (Basel Switzerland), 2018Co-Authors: Dong Pan, Zhaohui Jiang, Zhipeng Chen, Weihua Gui, Yongfang Xie, Chunhua YangAbstract:The temperature measurement of blast furnace (BF) molten iron is a mandatory requirement in the ironmaking process, and the molten iron temperature is significant in estimating the molten iron quality and control blast furnace condition. However, it is not easy to realize real-time measurement of molten iron temperature because of the harsh environment in the blast furnace casthouse and the high-temperature characteristics of molten iron. To achieve continuous detection of the molten iron temperature of the blast furnace, this paper proposes a temperature measurement method based on infrared thermography and a temperature reduction model. Firstly, an infrared thermal imager is applied to capture the infrared thermal image of the molten iron flow after the skimmer. Then, based on the temperature distribution of the molten iron flow region, a temperature mapping model is established to measure the molten iron temperature after the skimmer. Finally, a temperature reduction model is developed to describe the relationship between the molten iron temperature at the taphole and skimmer, and the molten iron temperature at the taphole is calculated according to the temperature reduction model and the molten iron temperature after the skimmer. Industrial Experiment results illustrate that the proposed method can achieve simultaneous measurement of molten iron temperature at the skimmer and taphole and provide reliable temperature data for regulating the blast furnace.
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coordinated optimization setting of reagent dosages in roughing scavenging process of antimony flotation
Journal of Central South University, 2018Co-Authors: Chunhua Yang, Jianqi LiAbstract:Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model, a coordinated optimization method for dosage reagent based on key characteristics variation tendency and case-based reasoning is proposed. On the basis of the expert reagent regulation method in antimony flotation process, the reagent dosage pre-setting model of the roughing–scavenging bank is constructed based on case-based reasoning. Then, the sensitivity index is used to calculate the key features of reagent dosage. The reagent dosage compensation model is constructed based on the variation tendency of the key features in the roughing and scavenging process. At last, the prediction model is used to finish the classification and discriminant analysis. The simulation results and Industrial Experiment in antimony flotation process show that the proposed method reduces fluctuation of the tailings indicators and the cost of reagent dosage. It can lay a foundation for optimizing the whole process of flotation.
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Modeling, optimization, and control of solution purification process in zinc hydrometallurgy
IEEE CAA Journal of Automatica Sinica, 2018Co-Authors: Chunhua Yang, Yonggang LiAbstract:The solution purification process is an essential step in zinc hydrometallurgy. The performance of solution purification directly affects the normal functioning and economical benefits of zinc hydrometallurgy. This paper summarizes the authors' recent work on the modeling, optimization, and control of solution purification process. The online measurable property of the oxidation reduction potential U+0028 ORP U+0029 and the multiple reactors, multiple running statuses characteristic of the solution purification process are extensively utilized in this research. The absence of reliable online equipment for detecting the impurity ion concentration is circumvented by introducing the oxidationreduction potential into the kinetic model. A steady-state multiple reactors gradient optimization, unsteady-state operationalpattern adjustment strategy, and a process evaluation strategy based on the oxidation-reduction potential are proposed. The effectiveness of the proposed research is demonstrated by its Industrial Experiment.
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A Novel Device for Optical Imaging of Blast Furnace Burden Surface: Parallel Low-Light-Loss Backlight High-Temperature Industrial Endoscope
IEEE Sensors Journal, 2016Co-Authors: Zhipeng Chen, Zhaohui Jiang, Chunhua YangAbstract:Accurate real-time optical imaging of the burden surface shape plays an important role in improving the gas flow distribution, reducing the coke ration, and reducing the emissions of a blast furnace. To overcome the high-temperature, high-dust, and lightless environment and obtain clear images of the burden surface, a parallel low-light-loss backlight high-temperature Industrial endoscope is developed. The design of a parallel low-light-loss backlight path and a high-light-efficiency, low-light, color backlight source overcomes the lightlessness issue. Combined with the endoscopic optical imaging method, a high-temperature resistant image-capturing lens and a high-temperature non-resistant photosensitive chip are separated at two ends of the instrument. This separation design method together with the water cooling and Industrial nitrogen cooling system enables the equipment to overcome the high temperature issue. Moreover, a new installation strategy, which avoids the material flow and high-dust region, is proposed to overcome the high dust issue. The strategy includes establishing a trajectory model of dust particles to determine the low-dust area and conducting a landing points Experiment and a trajectory model of the material flow to determine the no-material-flow region. The Industrial Experiment results indicate that the developed device obtains real-time images of the burden surface and exhibits clear details of the coke and iron ore particles. The application also demonstrates the validity and better imaging performance of the proposed method compared with conventional detection methods.
Benoit Montreuil - One of the best experts on this subject based on the ideXlab platform.
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Strategic Supply Chain Planning and Risk Management: Experiment of a Decision Support System Gathering Business Departments Around a Common Vision
2019 International Conference on Industrial Engineering and Systems Management (IESM), 2019Co-Authors: Raphaёl Oger, Matthieu Lauras, Frédérick Benaben, Benoit MontreuilAbstract:Strategic supply chain planning and supply chain risk management are two fields of supply chain management that are inseparable nowadays. The ability to consider risks is essential to maintain business performance. In addition, integrating the different business departments' visions in a common business vision is necessary to properly plan the future of a company. However, it is still a challenge for companies to design and maintain a decision-making process supporting strategic supply chain decisions that integrates risk management and unify business vision across departments. This paper relates an Industrial Experiment as an attempt to meet this challenge. This Experiment was asked by a pharmaceutical company with the aim of supporting strategic decisions regarding its network of suppliers. It led to a decision-making process including the use of a computerized information system composed of a software for computations and a business intelligence software to easily make decisions. This process was put in practice on a pilot use case with two years old data. It resulted in the identification of several decisions that could have been made if the process was in operation two years ago, which is considered as a first validation of the approach. Finally, limitations have been identified regarding the data collection, opening avenues for future research on an innovative approach combining supply chain hyperconnectivity and event-driven principles.
Montreuil Benoit - One of the best experts on this subject based on the ideXlab platform.
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Strategic Supply Chain Planning and Risk Management: Experiment of a Decision Support System Gathering Business Departments Around a Common Vision
HAL CCSD, 2019Co-Authors: Oger Raphaël, Lauras Matthieu, Benaben Frederick, Montreuil BenoitAbstract:“© © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”International audienceStrategic supply chain planning and supply chain risk management are two fields of supply chain management that are inseparable nowadays. The ability to consider risks is essential to maintain business performance. In addition, integrating the different business departments’ visions in a common business vision is necessary to properly plan the future of a company. However, it is still a challenge for companies to design and maintain a decision-making process supporting strategic supply chain decisions that integrates risk management and unify business vision across departments. This paper relates an Industrial Experiment as an attempt to meet this challenge. This Experiment was asked by a pharmaceutical company with the aim of supporting strategic decisions regarding its network of suppliers. It led to a decision-making process including the use of a computerized information system composed of a software for computations and a business intelligence software to easily make decisions. This process was put in practice on a pilot use case with two years old data. It resulted in the identification of several decisions that could have been made if the process was in operation two years ago, which is considered as a first validation of the approach. Finally, limitations have been identified regarding the data collection, opening avenues for future research on an innovative approach combining supply chain hyperconnectivity and event-driven principles
Raphaёl Oger - One of the best experts on this subject based on the ideXlab platform.
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Strategic Supply Chain Planning and Risk Management: Experiment of a Decision Support System Gathering Business Departments Around a Common Vision
2019 International Conference on Industrial Engineering and Systems Management (IESM), 2019Co-Authors: Raphaёl Oger, Matthieu Lauras, Frédérick Benaben, Benoit MontreuilAbstract:Strategic supply chain planning and supply chain risk management are two fields of supply chain management that are inseparable nowadays. The ability to consider risks is essential to maintain business performance. In addition, integrating the different business departments' visions in a common business vision is necessary to properly plan the future of a company. However, it is still a challenge for companies to design and maintain a decision-making process supporting strategic supply chain decisions that integrates risk management and unify business vision across departments. This paper relates an Industrial Experiment as an attempt to meet this challenge. This Experiment was asked by a pharmaceutical company with the aim of supporting strategic decisions regarding its network of suppliers. It led to a decision-making process including the use of a computerized information system composed of a software for computations and a business intelligence software to easily make decisions. This process was put in practice on a pilot use case with two years old data. It resulted in the identification of several decisions that could have been made if the process was in operation two years ago, which is considered as a first validation of the approach. Finally, limitations have been identified regarding the data collection, opening avenues for future research on an innovative approach combining supply chain hyperconnectivity and event-driven principles.
Oger Raphaël - One of the best experts on this subject based on the ideXlab platform.
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Strategic Supply Chain Planning and Risk Management: Experiment of a Decision Support System Gathering Business Departments Around a Common Vision
HAL CCSD, 2019Co-Authors: Oger Raphaël, Lauras Matthieu, Benaben Frederick, Montreuil BenoitAbstract:“© © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”International audienceStrategic supply chain planning and supply chain risk management are two fields of supply chain management that are inseparable nowadays. The ability to consider risks is essential to maintain business performance. In addition, integrating the different business departments’ visions in a common business vision is necessary to properly plan the future of a company. However, it is still a challenge for companies to design and maintain a decision-making process supporting strategic supply chain decisions that integrates risk management and unify business vision across departments. This paper relates an Industrial Experiment as an attempt to meet this challenge. This Experiment was asked by a pharmaceutical company with the aim of supporting strategic decisions regarding its network of suppliers. It led to a decision-making process including the use of a computerized information system composed of a software for computations and a business intelligence software to easily make decisions. This process was put in practice on a pilot use case with two years old data. It resulted in the identification of several decisions that could have been made if the process was in operation two years ago, which is considered as a first validation of the approach. Finally, limitations have been identified regarding the data collection, opening avenues for future research on an innovative approach combining supply chain hyperconnectivity and event-driven principles