Journal of Industrial Information Integration最新文献_第2页

Expert opinion aggregation-based decision support for human-robot collaboration digital twin maturity assessment 基于专家意见汇总的人机协作数字孪生成熟度评估决策支持

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100710

Xin Liu , Gongfa Li , Feng Xiang , Bo Tao , Guozhang Jiang

Human-centered smart manufacturing is an essential direction for the future development of manufacturing. Safe and reliable smart human-robot collaboration is the foundation for realizing human-centered smart manufacturing. Digital twin-based human-robot collaboration has been proposed as a new manufacturing paradigm to devise collaborative strategies, simulate collaborative processes, and ensure worker safety. Establishing a maturity model is essential to accurately assess the capabilities of the constructed human-robot collaboration digital twin. This paper aims to contribute to the formalization and standardization of the human-robot collaboration digital twin. It constructs a novel assessment framework for the overall maturity measurement of existing digital twin-based human-robot collaboration projects. The developed human-robot collaboration digital twin maturity model includes 5 evaluation dimensions and 24 evaluation factors. Additionally, 5 maturity levels and their definitions are defined for each evaluation factor for maturity scoring. The expert opinion aggregation approach is proposed to quantify the evaluation factor metrics and ultimately to obtain a maturity level for the human-robot collaboration digital twin. The effectiveness and feasibility of the proposed method are verified through a collaborative assembly case study. This paper provides a generic method for assessing the competency level of human-robot collaboration digital twins, which can provide insights into the maturity of digital twins for practitioners in the human-robot collaboration field to develop targeted strategies for optimizing and upgrading human-robot collaboration digital twins.

以人为本的智能制造是未来制造业发展的重要方向。安全可靠的智能人机协作是实现以人为本的智能制造的基础。基于数字孪生的人机协作已被提出作为一种新的制造范式，用于设计协作策略、模拟协作过程和确保工人安全。建立成熟度模型对于准确评估所构建的人机协作数字孪生的能力至关重要。本文旨在促进人机协作数字孪生的正规化和标准化。它为现有基于数字孪生的人机协作项目的整体成熟度测量构建了一个新颖的评估框架。所开发的人机协作数字孪生成熟度模型包括 5 个评估维度和 24 个评估因素。此外，还为每个评估因素定义了 5 个成熟度等级及其定义，以便进行成熟度评分。提出了专家意见汇总法来量化评价因子指标，并最终得出人机协作数字孪生的成熟度等级。通过协作装配案例研究验证了所提方法的有效性和可行性。本文提供了一种评估人机协作数字孪生能力水平的通用方法，可为人机协作领域的从业人员深入了解数字孪生的成熟度，从而有针对性地制定优化和升级人机协作数字孪生的策略。

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引用次数: 0

Consensus reaching-based decision model for assessing resilient urban public health safety ecosystem with social network analysis 基于达成共识的决策模型，利用社会网络分析评估具有弹性的城市公共卫生安全生态系统

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100716

Zelin Wang , Xiangbin Wang , Weizhong Wang , Muhammet Deveci , Zengyuan Wu , Witold Pedrycz

In 2021, United Nations released the "Creating Resilient Cities 2030 Project", which aims to strengthen urban resilience in developing and implementing disaster reduction strategies. Resilient cities are a new type of urban development model that emphasizes the ability of cities to resist natural disasters and social pressures, reduce losses, and allocate resources reasonably to quickly recover from disasters. With the frequent occurrence of public health and safety accidents, the concept of public health safety ecosystem has become increasingly prominent in the field of urban resilience. To effectively manage public health incidents and enhance emergency response capabilities, evaluating the urban public health safety ecosystem is essential. A consensus-based decision-making model that accounts for the social networks among experts to accurately assess urban public health emergency capacity is introduced. To ensure the objectivity of indicator weights, we build up a novel model to calculate the weight of indicators utilizing social network analysis and consensus-reaching process analysis of indicator evaluation value. An illustrative case study on public health emergency capacity in Luoding is presented. This research expands the framework for assessing resilience in urban systems and provides a methodology for improving urban public health and resilience, introducing a novel approach for evaluating the urban public health safety ecosystem through social network analysis.

2021 年，联合国发布了 "创建 2030 年具有抗灾能力的城市项目"，旨在加强城市在制定和实施减灾战略中的抗灾能力。韧性城市是一种新型的城市发展模式，强调城市抵御自然灾害和社会压力的能力，减少损失，合理配置资源，从灾害中快速恢复。随着公共卫生安全事故的频发，公共卫生安全生态系统的概念在城市韧性领域日益凸显。为有效管理公共卫生事件，提高应急能力，对城市公共卫生安全生态系统进行评估至关重要。本文介绍了一种基于共识的决策模型，该模型考虑了专家之间的社会网络，以准确评估城市公共卫生应急能力。为确保指标权重的客观性，我们建立了一个新颖的模型，利用社会网络分析和指标评估值的共识达成过程分析来计算指标权重。本文还介绍了一个关于罗定市公共卫生应急能力的示例研究。该研究拓展了城市系统抗灾能力评估框架，并为提高城市公共卫生和抗灾能力提供了方法论，引入了一种通过社会网络分析评估城市公共卫生安全生态系统的新方法。

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引用次数: 0

Cross-domain intelligent diagnostics for rotating machinery using domain adaptive and adversarial networks 利用域自适应和对抗网络进行旋转机械的跨域智能诊断

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100722

Kui Hu , Yiwei Cheng , Jun Wu , Haiping Zhu

Accurate fault diagnosis of rotating machinery is critical to avoid catastrophic accidents. However, insufficient fault data seriously limit the performance of fault diagnosis in industrial applications. In this paper, a novel domain adaptive and adversarial network (DAAN) is proposed for data-driven fault diagnosis of the rotating machinery, which consists of a deep feature extractor, a domain classifier, and a label adaptive predictor. The deep feature extractor and domain classifier are constructed to obtain domain-invariant features by domain-adversarial training. Then, in the label adaptive predictor, a domain adaptation technique is used to reduce the feature discrepancy between the source domain and the target domain, so as to establish a mapping relationship between the data feature distribution of the two domains. Furtherly, a new transfer diagnosis method is proposed by using the DAAN, which combines the data generated by experimental simulation with deep transfer learning, to realize end-to-end intelligent fault diagnosis of the in-service machinery with few unlabeled fault samples. The proposed method explores a new solution for applying laboratory data to intelligent fault diagnosis in real scenarios. Several transfer experiments are implemented to verify the effectiveness of the proposed method by using 55 roller bearings and 4 gearboxes under various scenarios. The experimental results show that the diagnostic performance of proposed method is much better than other transfer learning methods and non-transfer learning methods.

旋转机械的准确故障诊断对于避免灾难性事故至关重要。然而，故障数据不足严重限制了故障诊断在工业应用中的性能。本文提出了一种用于旋转机械数据驱动故障诊断的新型域自适应对抗网络（DAAN），它由深度特征提取器、域分类器和标签自适应预测器组成。深度特征提取器和域分类器通过域对抗训练获得域不变特征。然后，在标签自适应预测器中，使用域自适应技术来减少源域和目标域之间的特征差异，从而建立两个域的数据特征分布之间的映射关系。此外，利用 DAAN 提出了一种新的迁移诊断方法，将实验仿真生成的数据与深度迁移学习相结合，实现了在役机械端到端智能故障诊断，只需少量未标记的故障样本。所提出的方法为将实验室数据应用于真实场景中的智能故障诊断探索了一种新的解决方案。通过使用 55 个滚动轴承和 4 个齿轮箱在不同场景下进行转移实验，验证了所提方法的有效性。实验结果表明，所提方法的诊断性能远远优于其他迁移学习方法和非迁移学习方法。

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引用次数: 0

Quantum machine learning: Classifications, challenges, and solutions 量子机器学习：分类、挑战和解决方案

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100736

Wei Lu , Yang Lu , Jin Li , Alexander Sigov , Leonid Ratkin , Leonid A. Ivanov

Recently, research at the intersection of quantum mechanics and machine learning has gained attention. This interdisciplinary field aims to tackle the computational efficiency of machine learning by leveraging quantum computing and to derive novel machine learning algorithms inspired by quantum principles. Despite substantial progress in quantum science research, several challenges persist, including the preservation of quantum coherence, mitigation of environmental constraints, advancing quantum computer development, and formulating comprehensive quantum machine learning algorithms. To date, a comprehensive theoretical framework for quantum machine learning is lacking, with much of the research still in the exploratory and experimental stages. This study conducts a thorough survey on quantum machine learning, with the aim of classifying quantum machine learning algorithms while addressing the existing challenges and potential solutions in this emerging field.

最近，量子力学与机器学习交叉领域的研究备受关注。这一跨学科领域旨在利用量子计算解决机器学习的计算效率问题，并从量子原理中获得新的机器学习算法。尽管量子科学研究取得了重大进展，但仍存在一些挑战，包括量子相干性的保持、环境约束的缓解、量子计算机的发展以及制定全面的量子机器学习算法。迄今为止，量子机器学习还缺乏全面的理论框架，大部分研究仍处于探索和实验阶段。本研究对量子机器学习进行了全面调查，旨在对量子机器学习算法进行分类，同时探讨这一新兴领域的现有挑战和潜在解决方案。

引用次数: 0

Enhancing mixed gas discrimination in e-nose system: Sparse recurrent neural networks using transient current fluctuation of SMO array sensor 增强电子鼻系统对混合气体的辨别能力：利用 SMO 阵列传感器的瞬态电流波动的稀疏递归神经网络

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100715

Namsoo Lim , Seokyoung Hong , Jiwon Jung , Gun Young Jung , Deok Ha Woo , Jinwoo Park , Daewon Kong , Chandran Balamurugan , Sooncheol Kwon , Yusin Pak

Despite recent significant advancements in gas sensor array technology, accurately identifying gases in mixed environments remains challenging. This difficulty is primarily due to the rapid and competing processes of gas molecules attaching to (adsorption) and detaching from (desorption) the sensor. In this study, we present a simple method to fabricate a 2 × 4 SMO-based gas sensor array, coupled with a sparse recurrent neural network (SRNN) that employs weight regularization. The recurrent layers of the SRNN process nonlinear information and capture temporal dependencies in the sensor data, while the regularization technique simplifies the model, making it both efficient and easier to interpret. Additionally, we introduce a novel feature: the dynamics of current, labeled as ΔI. This feature enables the SRNN model to efficiently detect the adsorption and desorption of gas molecules. We demonstrate that our model can distinguish between three intuitively indistinguishable datasets of gas species (NO₂, HCHO, and a mixture) with up to 92 % accuracy. By utilizing the fast and competitive adsorption/desorption information of gas molecules, our model can be applied to various gas combination environments, unlike conventional gas sensing data measured over longer periods. By integrating the sensor array with the advanced SRNN model, we pave the way for sophisticated e-nose systems, with potential applications in advanced gas sensing technologies, such as disease diagnosis through exhaled breath analysis and the detection of toxic species in mixed gas environments.

尽管气体传感器阵列技术最近取得了重大进展，但在混合环境中准确识别气体仍然具有挑战性。造成这种困难的主要原因是气体分子吸附（吸附）和脱附（脱附）传感器的快速和竞争过程。在本研究中，我们提出了一种简单的方法来制造基于 SMO 的 2 × 4 气体传感器阵列，并将其与采用权重正则化的稀疏递归神经网络 (SRNN) 相结合。SRNN 的递归层处理非线性信息并捕捉传感器数据中的时间依赖性，而正则化技术简化了模型，使其既高效又易于解释。此外，我们还引入了一个新特征：电流动态，标记为 ΔI。这一特征使 SRNN 模型能够有效地检测气体分子的吸附和解吸。我们证明，我们的模型可以区分三个直观上无法区分的气体物种数据集（NO2、HCHO 和一种混合物），准确率高达 92%。通过利用气体分子快速、竞争性的吸附/解吸信息，我们的模型可以应用于各种气体组合环境，而不像传统的气体传感数据需要长时间测量。通过将传感器阵列与先进的 SRNN 模型相结合，我们为复杂的电子鼻系统铺平了道路，该系统有望应用于先进的气体传感技术，例如通过呼出气体分析进行疾病诊断，以及检测混合气体环境中的有毒物质。

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引用次数: 0

Integration of an IoT sensor with angle-of-arrival-based angle measurement in AGV navigation: A reliability study 在 AGV 导航中将物联网传感器与基于到达角的角度测量相结合：可靠性研究

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100707

Zhen Cai , Fanhang Zhang , Yuan Tan , Stephan Kessler , Johannes Fottner

Automated guided vehicle (AGV), which was initially designed for indoor operations in industry, has been increasingly applied in outdoor heavy-duty logistics tasks. In typical navigation tasks, such as the autonomous tracking of a designated object or a person, relative angle and relative distance between AGV and the target is required. To obtain the necessary information, various on-board sensors are extensively integrated. In this paper, the reliability of measuring the relative angle with the Angle-of-Arrival (AoA) method with two different Internet of Things (IoT) sensor sets from Texas Instrument (TI) and u-blox, according to Bluetooth 5.1 was investigated. The performance of IoT sensors was validated with angle accuracy parameters and received signal strength indicator (RSSI). The better IoT sensor was then integrated into the AGV navigation system, and the information gathered from IoT sensor enabled the AGV to turn toward the direction of the target. The process of AGV turning to the targeted direction based on IoT sensor information was respectively tested in the simulation and actual environment and evaluated by the disparity between the real relative angle and the rotation angle of the AGV. The results showed that this disparity was within ±5° in both simulated and actual environments, and methods for higher accuracy were proposed. In this way, the reliability and performance of Angle of Arrival (AoA) sensors in measuring the relative angle, which remains unexplored by other researchers, was systematically assessed contributing to extending the usability of AoA sensors in complex, real-world applications.

自动导引车（AGV）最初是为工业领域的室内作业而设计的，现在已越来越多地应用于户外重型物流任务。在典型的导航任务中，例如自主跟踪指定物体或人员，需要 AGV 与目标之间的相对角度和相对距离。为了获得必要的信息，各种车载传感器被广泛集成。本文研究了德州仪器（TI）和 u-blox 两种不同的物联网（IoT）传感器组根据蓝牙 5.1 采用到达角（AoA）方法测量相对角度的可靠性。通过角度精度参数和接收信号强度指示器（RSSI）验证了物联网传感器的性能。然后将性能较好的物联网传感器集成到 AGV 导航系统中，通过物联网传感器收集的信息，AGV 可以转向目标方向。基于物联网传感器信息的 AGV 转向目标方向的过程分别在模拟和实际环境中进行了测试，并通过实际相对角度与 AGV 旋转角度之间的差距进行了评估。结果表明，在模拟和实际环境中，这一差距都在±5°以内，并提出了更高精度的方法。通过这种方式，系统地评估了到达角（AoA）传感器在测量相对角度方面的可靠性和性能（其他研究人员尚未对此进行探索），从而有助于扩大 AoA 传感器在复杂的实际应用中的可用性。

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引用次数: 0

Evaluating municipal solid waste management with a confidence level-based decision-making approach in q-rung orthopair picture fuzzy environment 用基于置信度的决策方法评估q-rung正交图模糊环境下的城市固体废物管理

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100708

Prayosi Chatterjee, Mijanur Rahaman Seikh

Municipal solid waste (MSW) management is a critical aspect of urban planning and public health. As societies strive towards environmental sustainability and socio-economic development, robust techniques to transform waste into energy become paramount. Assessment of waste-to-energy (WTE) techniques is based on a spectrum of criteria that are often vague and imprecise. The current study addresses this multi-criteria group decision-making problem of assessing and evaluating WTE methods for MSW management using q-rung orthopair picture fuzzy (qRPF) numbers. The study proposes an innovative combination of the Defining Interrelationships Between Ranked-criteria (DIBR) and Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) methods. The criteria are assessed using the recently developed DIBR method, while the alternatives are assessed using a popular distance-based method, namely CRADIS. Moreover, new confidence level-based aggregation operators for qRPF numbers are proposed and used to aggregate fuzzy data, while a novel triangular divergence-based distance measure is proposed and used to modify the existing CRADIS method. The results show that anaerobic digestion and pyrolysis are the two most preferred WTE methods for MSW management. An extensive comparative analysis demonstrates the applicability of the proposed methodology, while an exhaustive sensitivity analysis confirms the proposed method’s stability. The results of Spearman’s correlation coefficient validate the model’s practicality. The findings of this research yield significant insights beneficial to policymakers, industry stakeholders, and researchers alike. By implementing sustainable waste management strategies, municipalities can improve recycling rates, minimize landfill use, and promote a cleaner, healthier environment for urban populations.

城市固体废物（MSW）管理是城市规划和公共卫生的一个重要方面。随着社会努力实现环境可持续性和社会经济发展，将废物转化为能源的强大技术变得至关重要。对废物变能源（WTE）技术的评估基于一系列标准，而这些标准往往是模糊和不精确的。本研究利用 q-rung正交图象模糊（qRPF）数解决了这一多标准群体决策问题，即评估和评价用于 MSW 管理的 WTE 方法。研究提出了一种创新的组合方法，即 "排序标准间相互关系定义法"（DIBR）和 "距离理想解决方案备选方案折中排序法"（CRADIS）。标准采用最近开发的 DIBR 方法进行评估，而备选方案则采用流行的基于距离的方法（即 CRADIS）进行评估。此外，还提出了新的基于置信度的 qRPF 数聚合算子，用于聚合模糊数据，同时提出了新的基于三角发散的距离测量方法，用于修改现有的 CRADIS 方法。结果表明，厌氧消化和热解是 MSW 管理中最受欢迎的两种 WTE 方法。广泛的比较分析证明了所提方法的适用性，而详尽的敏感性分析则证实了所提方法的稳定性。斯皮尔曼相关系数的结果验证了模型的实用性。这项研究的结果为政策制定者、行业利益相关者和研究人员提供了有益的重要启示。通过实施可持续的废物管理策略，市政当局可以提高回收率，最大限度地减少垃圾填埋场的使用，并为城市人口创造更清洁、更健康的环境。

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引用次数: 0

Generating the assembly instructions of helicopter subassemblies using the hierarchical pruning strategy and large language model 使用分层剪枝策略和大型语言模型生成直升机组件的装配指令

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100723

Mingjie Jiang, Yu Guo, Shaohua Huang, Jun Pu

Assembly instructions are process documents in detail describing the operation steps, materials, tools, fixtures, and assembly sequences in assembly procedures. Due to assembly instructions including numerous contents, and the content being easy for workers to understand, process designers need to spend lots of time thinking and authoring assembly instructions to ensure that workers can complete the assembly task according to the assembly instructions. Focusing on the difficulties of the variety of assembly instructions and the process factors implicit in the standard languages of assembly instructions, a method of assembly instruction generation for helicopter subassemblies is proposed. First, a data representation model of multi-source heterogeneous knowledge and information based on knowledge graphs is designed and established. Then, a hierarchical pruning VF3 algorithm is presented to reuse assembly instructions according to hybrid similarity. Finally, a process factor revision model based on RoBERTa-BiLSTM-CRF is proposed to generate revised assembly instructions. Helicopter subassemblies, which contain 11,240 assembly procedures, are used to evaluate the performance of the method for generating assembly instructions. The proposed method greatly reduces the time cost of assembly instruction authoring and promotes the intelligent development of assembly process design.

装配指导书是详细描述装配程序中的操作步骤、材料、工具、夹具和装配顺序的工艺文件。由于装配指导书包含的内容繁多，且内容易于工人理解，工艺设计人员需要花费大量时间思考和编写装配指导书，以确保工人能够按照装配指导书完成装配任务。针对装配指令种类繁多、标准装配指令语言隐含工艺因素等难点，提出了一种直升机分总成装配指令生成方法。首先，设计并建立了基于知识图谱的多源异构知识和信息的数据表示模型。然后，提出了一种分层剪枝 VF3 算法，根据混合相似性重用装配指令。最后，提出了一种基于 RoBERTa-BiLSTM-CRF 的过程因素修订模型，用于生成修订后的装配指令。直升机子装配体包含 11,240 个装配程序，用于评估生成装配指令方法的性能。所提出的方法大大降低了装配指令编写的时间成本，促进了装配工艺设计的智能化发展。

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引用次数: 0

Proximal policy optimization with population-based variable neighborhood search algorithm for coordinating photo-etching and acid-etching processes in sustainable storage chip manufacturing 利用基于群体的可变邻域搜索算法进行近端策略优化，以协调可持续存储芯片制造中的光蚀刻和酸蚀刻工艺

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100727

Weijian Zhang , Min Kong , Yajing Zhang , Amir M. Fathollahi-Fard

In the complex process of manufacturing storage chips, the photo-etching and acid-etching stages play a crucial role, significantly affecting energy consumption and environmental impact. This paper introduces a novel Bi-Level Programming Model for Storage Chip Manufacturing (BLPM-SCM) aimed at optimizing the coordination between these two stages. The upper-level model focuses on minimizing the time it takes to complete wafer production, while the lower-level model seeks to reduce the number of acid-etching tanks used, thereby balancing production efficiency with resource utilization. To address the inherent complexity of the bi-level model, we present a hybrid meta-heuristic algorithm that combines Proximal Policy Optimization (PPO) with a Population-based Variable Neighborhood Search (PVNS) method. The PPO-PVNS algorithm enhances the intensification phase by adaptively selecting shaking and local search strategies, while PVNS supports the diversification phase, ensuring comprehensive exploration of the search space through iterative updates of the solution population. Extensive numerical experiments demonstrate the algorithm's superior performance and generalization capabilities in optimizing the manufacturing process. It significantly improves the coordination between the photo-etching and acid-etching stages, achieving dual optimization of energy consumption and environmental benefits. Furthermore, this study provides valuable insights and decision-making tools for industry practitioners, offering innovative solutions for scheduling optimization in the semiconductor sector and promoting more sustainable and efficient production practices.

在复杂的存储芯片制造过程中，光蚀刻和酸蚀刻阶段起着至关重要的作用，对能源消耗和环境影响有重大影响。本文介绍了一种新颖的存储芯片制造双层编程模型（BLPM-SCM），旨在优化这两个阶段之间的协调。上层模型的重点是最大限度地缩短完成晶圆生产所需的时间，而下层模型则力求减少酸蚀槽的使用数量，从而在生产效率与资源利用之间取得平衡。为了解决双层模型固有的复杂性，我们提出了一种混合元启发式算法，该算法结合了近端策略优化（PPO）和基于种群的变量邻域搜索（PVNS）方法。PPO-PVNS 算法通过自适应选择摇动和局部搜索策略来加强强化阶段，而 PVNS 则支持多样化阶段，通过迭代更新解群确保对搜索空间的全面探索。广泛的数值实验证明了该算法在优化生产流程方面的卓越性能和泛化能力。它大大改善了光蚀刻和酸蚀刻阶段之间的协调，实现了能耗和环境效益的双重优化。此外，这项研究还为行业从业人员提供了宝贵的见解和决策工具，为半导体行业的排程优化提供了创新解决方案，促进了更可持续和高效的生产实践。

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引用次数: 0

6G wireless communications for industrial automation: Scenarios, requirements and challenges 用于工业自动化的 6G 无线通信：应用场景、要求和挑战

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2024-11-01 DOI: 10.1016/j.jii.2024.100732

Engin Zeydan , Suayb Arslan , Yekta Turk

Industrial automation is an essential part of modern industries, including manufacturing and utilities, driven by the need to enhance productivity, precision and efficiency. This paper provides a comprehensive review of recent advances in industrial automation, focusing on the role of 6G wireless communication as a key enabler. We explore various categorizations and reference use cases within industrial automation and show how 6G technology can meet the evolving needs of these environments. The functional, service and non-functional system requirements needed to support these advanced automation scenarios are also outlined. A critical analysis of the challenges associated with the application of 6G technology in industry is presented, highlighting technical, operational and implementation barriers. At the end of the paper, we also discuss the key lessons learned from the efforts to date and suggest future directions for research and development to address the aforementioned challenges. By addressing various complex issues, this paper aims to provide a clear path for the integration of next-generation communication technologies into industrial automation systems

工业自动化是现代工业（包括制造业和公用事业）的重要组成部分，其驱动力是提高生产力、精确度和效率。本文全面回顾了工业自动化领域的最新进展，重点关注 6G 无线通信作为关键推动因素的作用。我们探讨了工业自动化领域的各种分类和参考用例，并展示了 6G 技术如何满足这些环境不断发展的需求。我们还概述了支持这些先进自动化场景所需的功能、服务和非功能系统要求。本文对 6G 技术在工业中的应用所面临的挑战进行了批判性分析，强调了技术、操作和实施方面的障碍。在本文的最后，我们还讨论了从迄今为止的工作中汲取的主要经验教训，并提出了应对上述挑战的未来研发方向。通过解决各种复杂问题，本文旨在为下一代通信技术融入工业自动化系统提供一条清晰的道路

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引用次数: 0