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Hierarchical modeling of stochastic manufacturing and service systems

Zhe George ZHANG, Xiaoling YIN

《工程管理前沿（英文）》 2017年第4卷第3期页码 295-303 doi: 10.15302/J-FEM-2017047

摘要： This paper presents a review of methodologies for analyzing stochastic manufacturing and service systems. On the basis of the scale and level of details of operations, we can study stochastic systems using micro-, meso-, and macro-scopic models. Such a classification unifies stochastic modeling theory. For each model type, we highlight the advantages and disadvantages and the applicable situations. Micro-scopic models are based on quasi-birth-and-death process because of the phase-type distributed service times and/or Markov arrival processes. Such models are appropriate for modeling the detailed operations of a manufacturing system with relatively small number of servers (production facilities). By contrast, meso-scopic and macro-scopic models are based on the functional central limit theorem (FCLT) and functional strong law of large numbers (FSLLN), respectively, under heavy-traffic regimes. These high-level models are appropriate for modeling large-scale service systems with many servers, such as call centers or large service networks. This review will help practitioners select the appropriate level of modeling to enhance their understanding of the dynamic behavior of manufacturing or service systems. Enhanced understanding will ensure that optimal policies can be designed to improve system performance. Researchers in operation analytics and optimization of manufacturing and logistics also benefit from such a review.

关键词： stochastic modeling QBD process PH distribution heavy traffic limits diffusion process

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流程工业智能优化制造的基础理论与关键技术

钱锋, 钟伟民, 杜文莉

《工程（英文）》 2017年第3卷第2期页码 154-160 doi: 10.1016/J.ENG.2017.02.011

摘要：

本文围绕流程工业转型升级的重大需求，剖析了当前流程工业在经营决策层面、生产运行层面、能效安环层面和信息集成层面存在的主要问题，提出了利用现代信息技术从生产、管理以及营销全过程优化出发，推进以高效化、绿色化和智能化制造为目标的流程工业智能优化制造的愿景目标。围绕制造过程从装备智能化到制造流程、操作模式、供应链管理等自适应智能优化，以需求驱动、应用导向为主，提出了当前亟须研究的核心工程科学问题，即：①生产与经营全过程信息智能感知与集成；②知识驱动的生产过程计划调度与管理决策；③人机物自然交互的生产过程全流程协同控制与优化；④全生命周期安全环境足迹监控与风险溯源分析及控制。并围绕核心科学问题进一步提出了拟突破的流程工业智能优化制造的基础理论与关键技术。

关键词：流程工业智能优化制造绿色制造高端制造最优性评价

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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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面向碳中和的智能流程制造——流程制造数字化转型助力实现双碳目标

钱锋

《工程（英文）》 2023年第27卷第8期页码 1-2 doi: 10.1016/j.eng.2023.07.005

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人工智能在过程工业绿色制造中的机遇与挑战

毛帅, 王冰, 唐漾, 钱锋

《工程（英文）》 2019年第5卷第6期页码 995-1002 doi: 10.1016/j.eng.2019.08.013

摘要：

智能制造是提高过程工业质量的关键。在智能制造中，有这样一种趋势：将各种新一代信息技术融合到过程安全分析中。目前，由于危险化学品的大量使用，绿色制造面临着安全管理方面的重大障碍，从而导致化工过程空间的不均匀化以及安全环保法规的日益严格化。新兴的信息技术，如人工智能（AI），作为克服这些困难的一种手段，是很有前景的。基于最先进的人工智能方法和过程工业中复杂的安全关系，我们识别并讨论了与过程安全相关的几个技术挑战：用过程安全的稀缺标签进行知识获取；基于知识的过程安全推理；不同来源异构数据的精确融合；以及动态风险评估和辅助决策的有效学习。在此背景下，本文还讨论了当前和未来的工作。

关键词：过程工业智能制造绿色制造人工智能

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流程工业制造系统智能化——人工智能与流程制造深度融合

钱锋

《工程（英文）》 2019年第5卷第6期页码 981-981 doi: 10.1016/j.eng.2019.10.002

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Discussion on advanced manufacturing

WANG Xiankui

《机械工程前沿（英文）》 2007年第2卷第3期页码 251-262 doi: 10.1007/s11465-007-0044-4

摘要： Advanced manufacturing consists of continuity of manufacturing, its broad sense, and the core of the manufacturing process. The technology of continuous manufacturing is discussed according to both historical and modern perspectives. The relationship between human development and manufacturing technology is also discussed. Manufacturing is a continuously evolving topic. It is not only the foundation and means of imagination, conception, the science, and the technology of material change, but also the expression of national economy, national defense, and the support industries. The broad sense of manufacturing theory, which extends the concept of manufacturing, is an important development in the 20th century. The sense is analyzed in connection with design, material forming theory, synthesis of manufacturing technology, manufacturing modes, life cycle of product, hardware and software, and support environment, etc. At the same time, the core action and the development of the theory and technology of process is also discussed. At the end of this paper, the development directions of mechanical manufacturing science and technology are mentioned.

关键词： development national manufacturing process support environment mechanical manufacturing

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Equipment–process–strategy integration for sustainable machining: a review

《机械工程前沿（英文）》 2023年第18卷第3期 doi: 10.1007/s11465-023-0752-4

摘要： Although the manufacturing industry has improved the quality of processing, optimization and upgrading must be performed to meet the requirements of global sustainable development. Sustainable production is considered to be a favorable strategy for achieving machining upgrades characterized by high quality, high efficiency, energy savings, and emission reduction. Sustainable production has aroused widespread interest, but only a few scholars have studied the sustainability of machining from multiple dimensions. The sustainability of machining must be investigated multidimensionally and accurately. Thus, this study explores the sustainability of machining from the aspects of equipment, process, and strategy. In particular, the equipment, process, and strategy of sustainable machining are systematically analyzed and integrated into a research framework. Then, this study analyzes sustainable machining-oriented machining equipment from the aspects of machine tools, cutting tools, and materials such as cutting fluid. Machining processes are explored as important links of sustainable machining from the aspects of dry cutting, microlubrication, microcutting, low-temperature cutting, and multidirectional cutting. The strategies for sustainable machining are also analyzed from the aspects of energy-saving control, machining simulation, and process optimization of machine tools. Finally, opportunities and challenges, including policies and regulations toward sustainable machining, are discussed. This study is expected to offer prospects for sustainable machining development and strategies for implementing sustainable machining.

关键词： sustainable machining equipment process strategy manufacturing

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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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Process Planning Support System for Green Manufacturing and its application

HE Yan, LIU Fei, CAO Huajun, ZHANG Hua

《机械工程前沿（英文）》 2007年第2卷第1期页码 104-109 doi: 10.1007/s11465-007-0018-6

摘要： Owing to a lack of practical methods and software tools in the existing researches on green manufacturing (GM), process planning support system for green manufacturing (GMPPSS) was developed to deal with the problems in optimization of environment-benign process planning. The GMPPSS consisted mainly of three function modules and related model repositories including: selection of process elements, optimization of process courses, and evaluation of process projects for GM. The database of the GMPPSS was used to provide plentiful information on resources consumption and environmental impact in manufacturing processes, which consisted of process attribute database, inventory database, machine database, tool database, and the cutting fluid database. Raw materials, secondary material consumption, energy consumption, and environment impacts of process planning were optimized to improve the green attribute of process planning of parts with the supports of the databases and model repositories. The gear processing in the machining tool factory was presented to verify the system s applicability.

关键词： environment selection GMPPSS consumption database

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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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Toward the development of process plans with reduced environmental impacts

Fu ZHAO, Vance R. MURRAY, Karthik RAMANI, John W. SUTHERLAND

《机械工程前沿（英文）》 2012年第7卷第3期页码 231-246 doi: 10.1007/s11465-012-0334-3

摘要：

Manufacturing process planning serves as a pivotal link between design and manufacturing. Process planning decisions play a critical role in determining the cost and environmental impacts associated with manufacturing. Past efforts to address environmental issues during process planning are briefly reviewed and potential approaches that can achieve reduced environmental impacts are then discussed. A proposed method is presented for environmentally conscious process planning. The method begins with an existing process plan, and then identifies impactful process steps, and associated design features, in terms of manufacturing cost and environmental impact. Alternative processes that can achieve these features are then considered to generate alternative process plans. These alternatives are then evaluated in terms of economic and environmental performance. The results of these evaluations are then used to generate a set of process plans that are non-dominated with respect to manufacturing cost and environmental impact objectives to produce a Pareto frontier. The proposed method is demonstrated using the manufacturing of a prosthetic hip shell as a case study.

关键词： process planning life cycle assessment (LCA) sustainable manufacturing prosthetic hip shell

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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

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一种新的流程工业企业智能制造准备度评估模型：流程工业智能制造准备度指数（PIMRI） Research Article

赵路军1,2,邵嘉铭2,3,祁雨奇2,褚健2,冯毅萍1

《信息与电子工程前沿（英文）》 2023年第24卷第3期页码 417-432 doi: 10.1631/FITEE.2200080

摘要：近年来，工业4.0的蓬勃发展在世界范围内已经成为了一个新的趋势，它给全球范围内的工业企业既带来了新的机遇也带来了新的挑战。因此，很多制造业企业开始尝试应用新兴的使能技术来推动自身的智能制造转型升级。本研究提出一种用于评估流程工业企业智能制造准备度情况的模型，目的是为了帮助企业明确自身智能制造发展水平，识别短板问题。尽管已经有学者提出了相关工业4.0准备度和成熟度评估的模型，但是目前还缺少流程工业企业的针对性评估模型。本文提出的流程工业智能制造准备度模型用6个层次来描述智能制造的不同发展阶段。此外，该模型结合了流程工业企业日常的生产经营特点与智能制造的能力要求，模型包含4个评估族、9个评估类和25个评估域。本模型还根据不同智能制造准备度等级的要求将25个评估域进一步划分成了249个特征项指标，用于企业智能制造准备度水平的准确评估。此外，为了方便企业进行自诊断自评估，本文还基于249个特征项指标开发了智能制造准备度评估问卷。最后，本文通过模型在196家流程工业企业的应用案例，介绍了模型的具体使用方法。希望本模型的提出可以给流程工业企业智能制造准备度的评估提供一个新的方法。

关键词：流程工业；工业4.0；准备度模型；智能制造；准备度指数

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人工智能赋能流程制造

钱锋

《工程（英文）》 2021年第7卷第9期页码 1193-1194 doi: 10.1016/j.eng.2021.08.003