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Proceedings of the 2023 7th International Conference on Electronic Information Technology and Computer engineering

作者： Yanbo Yin Jianming Zhao Tianyu Wang Weiyan Tong School of Chemical Process Automation Shenyang University of Technology China Key Laboratory of Networked Control Systems Chinese Academy of Sciences China

ISBN: (纸本)9798400708305

This article addresses the challenge of optimizing performance in a fragmentation blockchain system for industrial Internet of things (IIOT) applications. It introduces an enhanced version of the traditional Whale Optimization Algorithm (WOA) known as the Chaotic Whale Optimization Algorithm. This enhanced algorithm is designed to optimize the parameters of the fragmentation blockchain system with the goal of maximizing real-time memory utilization in the fragmentation nodes while minimizing block consensus time. The proposed method identifies optimal blockchain system parameters within diverse network environments, taking into account factors such as node computing power and inter-node transmission rates. To mitigate the issue of local optima inherent in traditional algorithms, the Chaotic Whale Optimization Algorithm transforms the optimization problem in a more intuitive manner. This algorithm strikes a fine balance between diversity and convergence. The effectiveness of this method is assessed through simulation experiments, with results indicating its superior performance compared to alternative approaches. Overall, the approach presented in this article significantly reduces consensus time within the fragmentation blockchain system and enhances real-time memory utilization in the fragmented blocks.

关键词： consensus time industrial Internet of Things real-time utilization of node memory whale optimization algorithm

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Inductive Sintering Module for Improved Multi-Die Attach in the Field of Power Packaging 12

Inductive Sintering Module for Improved Multi-Die Attach in ...

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12th IEEE CPMT Symposium Japan, ICSJ 2023

作者： Hofmann, Christian Rochala, Patrick Kroll, Martin Panhale, Sushant Baum, Mario Kuhn, Harald Oi, Kiyoshi Sanada, Masaki Murayama, Kei Fraunhofer Institute for Electronic Nano Systems Enas Department System Packaging Chemnitz Germany Chemnitz University of Technology Professorship for Forming and Joining Chemnitz Germany Fraunhofer Institute for Electronic Nano Systems Enas Department Systems Engineering Chemnitz Germany Fraunhofer Institute for Electronic Nano Systems Enas Chemnitz Germany Shinko Electric Industries CO. LTD. Process Development Dept. Nagano Japan

This work presents a heating technology for multi-die attach based on inductive silver sintering. Thus, the heat for the sintering reaction is confined locally to the bond region, avoiding heating of the entire power ... 详细信息

ISBN: (纸本)9798350325157

关键词： Sintering

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Application of an electrolysis system model for techno-economic optimization of hydrogen production in industry-based case studies

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International Journal of Hydrogen Energy 2025年 138卷 1144-1162页

作者： Köstlbacher, Jürgen Breuning, Larissa Nigbur, Florian Wienert, Patrick Khatiwada, Dilip Technical University of Munich School of Engineering and Design Department of Energy and Process Engineering Chair of Renewable and Sustainable Energy Systems Lichtenbergstraße 4a Garching bei Muenchen85748 Germany KTH Royal Institute of Technology Department of Energy Technology Division of Energy System Brinellvägen 68 Stockholm100 44 Sweden Accenture Germany Campus Kronberg 1 Kronberg61476 Germany

Even with favorable policy frameworks, green hydrogen has not been cost-competitive in Europe. Optimizing hydrogen production can reduce the Levelized Costs of Hydrogen (LCOH). In this research, an electrolysis system model is developed to optimize hydrogen production in two industrial settings. The model incorporates technical aspects such as part-load behavior, stack degradation, and energy inputs (i.e., electricity price and volume projections). Mid-scale hydrogen production for heavy-duty transport refuelling in Germany has the lowest LCOH at 8 €/kg (with a 16 MWel electrolysis system), whereas large-scale hydrogen production for the refinery industry in Portugal achieves 4 €/kg (with a 128 MWel system). The study reveals that the optimal system configuration depends on energy prices, technology costs, efficiency, load flexibility, and storage options. This study could be helpful in operationalizing hydrogen production systems (e.g., stack operation and replacement strategies) depending on energy supply and hydrogen demand over the lifetime. © 2025 The Authors

关键词： Linear programming

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Wet milling of mefenamic acid for seed generation: model-driven size reduction for maximizing yield

Wet milling of mefenamic acid for seed generation: model-dri...

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2022 AIChE Annual Meeting

作者： Mehta, B.A. Brown, C.J. Mitchell, N.A. Florence, A. Siemens Process Systems Engineering Ltd. London United Kingdom EPSRC Future CMAC Manufacturing Hub University of Strathclyde Glasgow United Kingdom

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Phase transfer-based high-efficiency recycling of precious metal electrocatalysts

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Green Chemical engineering 2024年第1期5卷 68-74页

作者： Qing Zeng Shaonan Tian Yu Zhang Hui Liu Dong Chen Xinlong Tian Chaoquan Hu Jun Yang State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing100190China State Key Laboratory of Marine Resource Utilization in South China Sea Hainan Provincial Key Lab of Fine ChemistrySchool of Chemical Engineering and TechnologyHainan UniversityHaikou570228China Nanjing IPE Institute of Green Manufacturing Industry Nanjing211100China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing100049China

Recycling precious metals with high-efficiency is undoubtedly beneficial to optimize resource utilization for environmental remediation and sustainable ***,we report an efficient route to recycle the palladium(Pd)and platinum(Pt)electrocatalysts using a phase transfer *** strategy involves acidic dissolution of deactivated precious metal(Pd/Pt)electrocatalysts from their loading substrates,mixing with an ethanolic solution of dodecylamine(DDA),subsequent extraction of metal ions into a non-polar organic phase,and final reduction by sodium borohydride to reproduce high-performance electrocatalysts towards typical electrochemical reactions,e.g.,oxygen reduction reaction(ORR)and ethanol oxidation reaction(EOR).In specific,the transfer efficiencies are up to 98%and the final recovery rate is over 85%for Pd and Pt electrocatalysts in each *** approach symbolizes a facile and efficient way to recover precious metals,which might be applied to recycling a wide range of metals in various realms after appropriate modifications.

关键词： Precious metal Phase transfer Extraction Recovery Electrocatalyst

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Research on Comprehensive Assessment Method of Battery Consistency Based on Scaled Energy Storage Power Station 9

Research on Comprehensive Assessment Method of Battery Consi...

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9th Asia Conference on Power and Electrical engineering, ACPEE 2024

作者： Kepaiyitulla, Tursun Li, Ming Zheng, Yunping Zong, Sijia Luo, Xingyan Wang, Shangxing Li, Xiangjun Xinjiang Key Laboratory of Whole Process Simulation for Power System State Grid Xinjiang Electric Power Research Institute Urumqi China State Key Laboratory of Operation Ad Control of Renewable Energy and Storage Systems China Electric Power Research Istitute Beijing100192 China

ISBN: (纸本)9798350309638

In the long-term operation of a megawatt-scale energy storage plant composed of series-parallel connections, the single batteries will have different degrees of inconsistency problems. To solve this problem, this paper proposes a comprehensive assessment method based on the consistency of batteries in scaled energy storage power stations. According to the consistency indexes such as single battery voltage and voltage polarity difference in series connection between modules, the consistency evaluation criterion of battery monomer was established. Based on the historical data of a battery energy storage system, the consistency evaluation criterion of a single battery is used to analyze the consistency of a single battery of an energy storage power station at different charging and discharging stages. The results show that this method can accurately assess cell consistency. It provides data support for the health status assessment of energy storage plants and reduces the systematic operational risk of energy storage plants. © 2024 IEEE.

关键词： Digital storage

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A Typical Skill 4.0 Platform for process Safety Management 8

A Typical Skill 4.0 Platform for Process Safety Management

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8th International Conference on control, Instrumentation and Automation, ICCIA 2022

作者： Mokhtarname, Reyhane Safavi, Ali Akbar Urbas, Leonhard Salimi, Fabienne Taghipour, Hosein Shiraz University Power and Control Eng. Dep. Shiraz Iran Chair of Process Control Systems Technische Universität Dresden Dresden Germany ADEPP Academy London United Kingdom

ISBN: (纸本)9781665495691

In the 20th century, the engineering curriculum aimed to educate the specialist engineers. Observation skills were enforced after learning the fundamental theory of the scientific and engineering topic in face-to-face classrooms where professors taught the subject matter. Students were engaged in the courses upon the available time and with the professor teaching style. Along the fourth industrial revolution, new engineering education platforms based on some new and desired skills are required to cope with the changes in production and quality assurance requirements. This paper proposes an active collaborative learning platform in which the learners can learn by doing and serious engagement. The developed platform provides the digital twin of process safety engineering and management systems for a real complex polymerization plant. This platform can be used for training of engineers at both academia and industry. © 2022 IEEE.

关键词： Industry 4.0

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Fluidized bed combustion of high water content alcohol extracted herb residue and the impacts of blending wasted activated coke

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Carbon Resources Conversion 2023年第1期6卷 11-19页

作者： Xuan Liu Xinyu Zhu Wenyan Wang Bowen Shi Guangyi Zhang Jianling Zhang Jiancheng Yang Yanming Shen School of Chemical Engineering Shenyang University of Chemical TechnologyShenyang 110142LiaoningChina School of Ecology and Environment Beijing Technology and Business UniversityBeijing 100048China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China China Power Engineering Consulting Group Co. LtdBeijing 100120China

Combustion of herb residues(HRs)for heat recovery is a good way for their utilization,but there exists such a problem as high concentration NOx emission in flue *** alcohol extracted herb residue(AEHR),one special type of HRs,was chosen as the object and was subjected to immediate combustion in a fluidized bed reactor to investigate the characteristics of its resulting NOx *** results showed that,most of the NOx in the flue gas was produced from the char nitrogen(C-N);as the fuel water content increased,the NOx emission concentration exhibited a trend of first decreasing and then increasing;and a properly low combustion temperature inhibited the NOx emission upon the premise of ensuring full *** staging combustion was adopted to effectively control NOx:the NOx emission concentration in the flue gas was reduced to 296 mg⋅m􀀀3 and the NOx emission reduction rate reached 46.51%compared to conventional ***-combustion by blending wasted activated coke(WAC)into the AEHR helped both stabilize the combustion state and reduce further the NOx *** the blending ratio of WAC fell within a proper range of 20-30%,the NOx emission concentration in the flue gas was as low as 231.4 mg⋅m􀀀*** addition to the dilution effect of the combustion flue gas of the blended WAC,the local reducing atmosphere caused by its incomplete combustion as well as its strong absorbability and catalytical effect was accountable for the further decrease of the NOx emission concentration.

关键词： Alcohol extracted herb residue Wasted activated coke Fluidized bed combustion NOx Air staging combustion

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ARRTOC: ADVERSARIALLY ROBUST REAL-TIME OPTIMIZATION AND control

arXiv

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arXiv 2023年

作者： Ahmed, Akhil del Rio-Chanona, Ehecatl Antonio Mercangöz, Mehmet Centre for Process Systems Engineering Department of Chemical Engineering Imperial College London London United Kingdom

Real-Time Optimization (RTO) plays a crucial role in the process operation hierarchy by determining optimal set-points for the lower-level controllers. However, at the control layer, these set-points may be difficult to track due to challenges in implementation as a result of disturbances, measurement noise, and actuator performance limitations. To address this, in this paper, we present the Adversarially Robust Real-Time Optimization and control (ARRTOC) algorithm. ARRTOC addresses this issue by finding set-points which are both optimal and inherently robust to implementation errors at the control layers. ARRTOC draws inspiration from adversarial machine learning, offering a novel constrained Adversarially Robust Optimization (ARO) solution applied to the RTO layer. By integrating controller design with RTO, ARRTOC enhances overall system performance and robustness by ensuring the chosen set-points are tailored to the underlying controller designs. To validate our claims, we present three case studies: an illustrative example, a bioreactor case study, and a multi-loop evaporator process. The proposed approach is found to improve RTO objectives, such as profit, by as much as 50% in some case studies compared to RTO formulations which ignore the performance of the control layers. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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The Impact of Predictive Maintenance on the Performance of Industrial Enterprises

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SN Computer Science 2025年第1期6卷 1-34页

作者： Er-Ratby, Mohamed Kobi, Abdessamad Sadraoui, Youssef Kadiri, Moulay Saddik LaSTI Laboratory of Science and Engineering Techniques National School of Applied Sciences of Khouribga Sultan Moulay Slimane University Khouribga Morocco LARIS Angevin Laboratory for Systems Engineering Research Polytech Angers University of Angers Angers France LIPIM Laboratory of Process Engineering Computer Science and Mathematics National School of Applied Sciences of Khouribga Sultan Moulay Slimane University Khouribga Morocco

Optimizing maintenance and enhancing the performance of businesses are significant concerns in the modern industrial world. Predictive maintenance is emerging as an innovative approach to address these challenges, allowing companies to shift from corrective maintenance to preventive maintenance. Predictive maintenance relies on the use of advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) to collect and analyse real-time data from equipment. Through this predictive analysis, it becomes possible to identify early warning signals of failures, enabling the anticipation of potential issues and the proactive planning of maintenance interventions. In this study, we will thoroughly examine the impact of predictive maintenance on the performance of businesses. We will explore the benefits and opportunities it offers in terms of reducing downtime, optimizing maintenance costs, and enhancing productivity. We will also investigate the various technologies and methods used in the implementation of predictive maintenance, along with potential challenges and best practices for successful adoption. This research focuses on studying the application of predictive maintenance within a company using data science and machine learning methods. Predictive maintenance represents an innovative approach aimed at anticipating equipment failures by leveraging real-time collected data. Through the analysis of this data using sophisticated algorithms, it becomes possible to identify early signals of potential problems and implement preventive maintenance actions before breakdowns occur. This approach not only reduces unexpected downtime but also optimizes maintenance operations by avoiding unnecessary interventions and maximizing resource utilization. The ultimate goal is to improve equipment availability, optimize operational performance, and maximize the overall yield of the company. © The Author(s), under exclusive licence to S

关键词： Artificial intelligence (AI) and machine learning (ML) Data science Optimizing maintenance Performance indicators Predictive maintenance Production

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