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Hybrid method integrating machine learning and particle swarm optimization for smart chemical processoperations

Haoqin Fang, Jianzhao Zhou, Zhenyu Wang, Ziqi Qiu, Yihua Sun, Yue Lin, Ke Chen, Xiantai Zhou, Ming Pan

《化学科学与工程前沿（英文）》 2022年第16卷第2期页码 274-287 doi: 10.1007/s11705-021-2043-0

摘要： Modeling and optimization is crucial to smart chemical process operations. However, a large number of nonlinearities must be considered in a typical chemical process according to complex unit operations, chemical reactions and separations. This leads to a great challenge of implementing mechanistic models into industrial-scale problems due to the resulting computational complexity. Thus, this paper presents an efficient hybrid framework of integrating machine learning and particle swarm optimization to overcome the aforementioned difficulties. An industrial propane dehydrogenation process was carried out to demonstrate the validity and efficiency of our method. Firstly, a data set was generated based on process mechanistic simulation validated by industrial data, which provides sufficient and reasonable samples for model training and testing. Secondly, four well-known machine learning methods, namely, K-nearest neighbors, decision tree, support vector machine, and artificial neural network, were compared and used to obtain the prediction models of the processes operation. All of these methods achieved highly accurate model by adjusting model parameters on the basis of high-coverage data and properly features. Finally, optimal process operations were obtained by using the particle swarm optimization approach.

关键词： smart chemical process operations data generation hybrid method machine learning particle swarm optimization

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A literature review of smart warehouse operations management

《工程管理前沿（英文）》 2022年第9卷第1期页码 31-55 doi: 10.1007/s42524-021-0178-9

摘要： E-commerce, new retail, and other changes have highlighted the requirement of high efficiency and accuracy in the logistics service. As an important section in logistics and supply chain management, warehouses need to respond positively to the increasing requirement. The “smart warehouse” system, which is equipped with emerging warehousing technologies, is increasingly attracting the attention of industry and technology giants as an efficient solution for the future of warehouse development. This study provides a holistic view of operations management problems within the context of smart warehouses. We provide a framework to review smart warehouse operations management based on the characteristics of smart warehouses, including the perspectives of information interconnection, equipment automation, process integration, and environmental sustainability. A comprehensive review of relevant literature is then carried out based on the framework with four perspectives. This study could provide future research directions on smart warehouses for academia and industry practitioners.

关键词： smart warehouse operations management interconnection automation integration sustainability

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Operations management of smart logistics: A literature review and future research

Bo FENG,Qiwen YE

《工程管理前沿（英文）》 2021年第8卷第3期页码 344-355 doi: 10.1007/s42524-021-0156-2

摘要： The global collaboration and integration of online and offline channels have brought new challenges to the logistics industry. Thus, smart logistics has become a promising solution for handling the increasing complexity and volume of logistics operations. Technologies, such as the Internet of Things, information communication technology, and artificial intelligence, enable more efficient functions into logistics operations. However, they also change the narrative of logistics management. Scholars in the areas of engineering, logistics, transportation, and management are attracted by this revolution. Operations management research on smart logistics mainly concerns the application of underlying technologies, business logic, operation framework, related management system, and optimization problems under specific scenarios. To explore these studies, the related literature has been systematically reviewed in this work. On the basis of the research gaps and the needs of industrial practices, future research directions in this field are also proposed.

关键词： smart logistics operations management optimization Internet of Things

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Special issue on “Green chemical process and intensification”

《化学科学与工程前沿（英文）》 2022年第16卷第11期页码 1533-1535 doi: 10.1007/s11705-022-2263-y

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Multiscale process systems engineering—analysis and design of chemical and energy systems from moleculardesign up to process optimization

《化学科学与工程前沿（英文）》 2022年第16卷第2期页码 137-140 doi: 10.1007/s11705-021-2135-x

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Integrating operations research into green logistics: A review

《工程管理前沿（英文）》页码 517-533 doi: 10.1007/s42524-023-0265-1

摘要： Logistical activities have a significant global environmental impact, necessitating the adoption of green logistics practices to mitigate environmental effects. The COVID-19 pandemic has further emphasized the urgency to address the environmental crisis. Operations research provides a means to balance environmental concerns and costs, thereby enhancing the management of logistical activities. This paper presents a comprehensive review of studies integrating operations research into green logistics. A systematic search was conducted in the Web of Science Core Collection database, covering papers published until June 3, 2023. Six keywords (green logistics OR sustainable logistics OR cleaner logistics OR green transportation OR sustainable transportation OR cleaner transportation) were used to identify relevant papers. The reviewed studies were categorized into five main research directions: Green waste logistics, the impact of costs on green logistics, the green routing problem, green transport network design, and emerging challenges in green logistics. The review concludes by outlining suggestions for further research that combines green logistics and operations research, with particular emphasis on investigating the long-term effects of the pandemic on this field.

关键词： green logistics operations research environment literature review

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流程工业智能优化制造

柴天佑,丁进良

《中国工程科学》 2018年第20卷第4期页码 51-58 doi: 10.15302/J-SSCAE-2018.04.009

摘要：

本文在分析流程工业的特点、运行现状和国际智能制造发展状况的基础上，提出了我国流程工业智能制造的新模式——智能优化制造。在分析流程企业采用的由企业资源计划、制造执行系统、过程控制系统组成的三层架构和控制与管理信息化系统的发展状况基础上，提出了未来流程企业应采用的智能优化制造的架构和系统愿景功能，分析了实现愿景功能所需要攻克的关键共性技术和对自动化、计算机和通信、数据科学挑战的科学问题，提出了突出流程工业战略地位、实施战略规划与顶层设计等发展流程工业智能优化制造的建议。

关键词：流程工业智能优化制造发展愿景科学挑战

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流程工业智能制造展望：过程系统工程师面临的挑战

Lockhart Bogle Ian David

《工程（英文）》 2017年第3卷第2期页码 161-165 doi: 10.1016/J.ENG.2017.02.003

摘要：

本文讨论了流程工业智能制造对过程系统工程(PSE) 研究人员提出的挑战。现有的研究在实现全厂和全站点优化方面已经取得了很大进展，进行基准化测试能够增加说服力。本文进一步讨论了过程系统工程师在开发可用工具和技术时遇到的技术性挑战，包括灵活性和不确定性，响应性和敏捷性，鲁棒性和安全性，混合物性质和功能的预测，以及新的建模和数学范式。利用大数据进行智能化开发来驱动系统灵活性需要面对新的挑战，例如，如何在漫长又复杂的供应链中确保数据的一致性和机密性。建模方面也存在很多挑战，涉及如何对所有的关键技术进行恰当的建模，特别是健康、安全和环境方面，需要在特定地点对微小却关键的量进行准确预测。对环境方面的关注要求我们紧密跟踪所有的分子种类，以便于它们能被最佳地用于创造可持续的解决方案。而源自于新型个性化产品的破坏性商业模式对环境的影响则难以预测。

关键词：智能制造过程系统工程不确定性灵活性优化基于模型的控制

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流程工业智能制造的未来

钱峰

《工程（英文）》 2023年第22卷第3期页码 20-22 doi: 10.1016/j.eng.2022.04.029

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Computational design of structured chemical products

Faheem Mushtaq, Xiang Zhang, Ka Y. Fung, Ka M. Ng

《化学科学与工程前沿（英文）》 2021年第15卷第5期页码 1033-1049 doi: 10.1007/s11705-020-2002-1

摘要： In chemical product design, the aim is to formulate a product with desired performance. Ingredients and internal product structure are two key drivers of product performance with direct impact on the mechanical, electrical, and thermal properties. Thus, there is a keen interest in elucidating the dependence of product performance on ingredients, structure, and the manufacturing process to form the structure. Design of product structure, particularly microstructure, is an intrinsically complex problem that involves different phases of different physicochemical properties, mass fraction, morphology, size distribution, and interconnectivity. Recently, computational methods have emerged that assist systematic microstructure quantification and prediction. The objective of this paper is to review these computational methods and to show how these methods as well as other developments in product design can work seamlessly in a proposed performance, ingredients, structure, and manufacturing process framework for the design of structured chemical products. It begins with the desired target properties and key ingredients. This is followed by computation for microstructure and then selection of processing steps to realize this microstructure. The framework is illustrated with the design of nanodielectric and die attach adhesive products.

关键词： product design performance ingredients structure manufacturing process framework structured chemical products microstructure design

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Applying chemical sedimentation process in drinking water treatment plant to address the emergent arsenic

Pengfei LIN,Xiaojian ZHANG,Hongwei YANG,Yong LI,Chao CHEN

《环境科学与工程前沿（英文）》 2015年第9卷第1期页码 50-57 doi: 10.1007/s11783-014-0733-2

摘要： Arsenic (As) spills occurred more frequently and sometimes polluted water sources in recent years in China. It is as urgent need to develop emergency treatment technologies to address the arsenic threat for large-scale water treatment plants. In response, we developed a chemical sedimentation technology to remove arsenic contaminants for water treatment plants. Bench-scale experiments were conducted to investigate the efficiency of arsenic removal and the influencing factors of the chemical sedimentation treatment process. The influencing factors included the choice and dosage of coagulants, the valence of arsenic and pH value of solution. The As(V) contaminants can be almost completely removed by ferric or alum coagulants. The As(III) contaminants are more recalcitrant to chemical sedimentation, 75% for ferric coagulant and 40% for alum coagulant. The quantitative results of arsenic removal load by different ferric or alum coagulants were presented to help determine the parameters for arsenic treatment technology. The dominant mechanism for arsenic removal is static combination, or adsorption of negative arsenic species onto positive ferric hydroxide or alum hydroxide flocs. The efficiency of this treatment technology has also been demonstrated by a real production test in one water treatment plant with arsenic-rich source water and one emergency response. This technology was verified to be quick to set-up, easy to operate and highly efficient even for high concentration of arsenic.

关键词： Arsenic spill chemical sedimentation coagulation drinking water emergency treatment

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Physical and chemical processes of wintertime secondary nitrate aerosol formation

Qi YING

《环境科学与工程前沿（英文）》 2011年第5卷第3期页码 348-361 doi: 10.1007/s11783-011-0343-1

摘要： The UCD/CIT model was modified to include a process analysis (PA) scheme for gas and particulate matter (PM) to study the formation of secondary nitrate aerosol during a stagnant wintertime air pollution episode during the California Regional PM /PM Air Quality Study (CRPAQS) where detailed measurements of PM components are available at a few sites. Secondary nitrate is formed in the urban areas from near the ground to a few hundred meters above the surface during the day with a maximum modeled net increase rate of 4 μg·m ·d during the study episode. The secondary nitrate formation rate in rural areas is lower due to lower NO . In the afternoon hours, near-surface temperature can be high enough to evaporate the particulate nitrate. In the nighttime hours, both the gas phase N O reactions with water vapor and the N O heterogeneous reactions with particle-bound water are important for secondary nitrate formation. The N O reactions are most import near the surface to a few hundred meters above surface with a maximum modeled net secondary nitrate increase rate of 1 μg·m ·d and are more significant in the rural areas where the O concentrations are high at night. In general, vertical transport during the day moves the nitrate formed near the surface to higher elevations. During the stagnant days, process analysis indicates that the nitrate concentration in the upper air builds up and leads to a net downward flux of nitrate through vertical diffusion and a rapid increase of surface nitrate concentration.

关键词： secondary nitrate aerosol N₂O₅ heterogeneous reaction process analysis

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智能过程制造中的数据解析与机器学习——大数据时代的最新进展与展望 Perspective

尚超、 Fengqi You

《工程（英文）》 2019年第5卷第6期页码 1010-1016 doi: 10.1016/j.eng.2019.01.019

摘要：

安全、高效、可持续的运行是工业生产过程控制的主要目标。然而，目前的技术严重依赖人为干预，因此在实际应用中体现出明显的局限性。蓬勃发展的大数据时代对流程工业产生了巨大的影响，为实现智能制造提供了前所未有的机遇。这种新的生产方式不仅要求机器能够帮助人类减轻繁重的体力劳动，还要能有效地承担智力劳动，甚至能够实现自主创新。为了实现这一目标，数据分析与机器学习扮演着不可或缺的角色。在本文中，我们回顾了数据分析和机器学习在工业生产过程监控、控制和优化方面的最新进展，着重分析机器学习模型的可解释性和功能性。通过分析实际需求与研究现状之间的差距，为未来的研究方向给出了建议。

关键词：大数据机器学习智能制造过程系统工程