Journal of Industrial Information Integration最新文献_第6页

A broker-embedded data distribution service for resource-constrained IoT environments 为资源受限的物联网环境提供嵌入代理的数据分发服务

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-15 DOI: 10.1016/j.jii.2025.100909

Hwimin Kim, Dae-Kyoo Kim

{"title":"A broker-embedded data distribution service for resource-constrained IoT environments","authors":"Hwimin Kim, Dae-Kyoo Kim","doi":"10.1016/j.jii.2025.100909","DOIUrl":"10.1016/j.jii.2025.100909","url":null,"abstract":"<div><div>The Data Distribution Service (DDS) is a middleware framework that facilitates brokerless, data-centric publish–subscribe communications across diverse domain networks. Its decentralized nature and a wide range of Quality of Service (QoS) policies enable DDS to be both scalable and reliable. However, DDS requires substantial resources, making it challenging to use with small devices, such as those commonly found in Internet of Things (IoT) environments – networks of interconnected physical devices embedded with sensors, software, and connectivity that collect and exchange data over the Internet, often under resource constraints. To address this, we present <span><math><mi>b</mi></math></span>-DDS (broker-embedded DDS), a novel approach that extends DDS by integrating broker functionalities. This enhances DDS’s compatibility with lightweight devices and its adoptability in resource-limited networks, while retaining the advantages of DDS, including scalability and reliability. The model was evaluated using a pedestrian safety system in the Vehicle-to-Everything (V2X) domain, and the results demonstrate that the model improves network traffic by 71.83% compared to standard DDS, provides resilience to the single-point failure problem in broker-based protocols, and exhibits the efficiency to satisfy stringent performance benchmarks for real-time systems.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100909"},"PeriodicalIF":10.4,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144652992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blockchain-based cloud controllers for reliable networked control systems 基于区块链的云控制器，用于可靠的网络控制系统

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-14 DOI: 10.1016/j.jii.2025.100902

Zhongcheng Lei , Luis de la Torre , Francisco-José Mañas-Álvarez , Wenshan Hu

{"title":"Blockchain-based cloud controllers for reliable networked control systems","authors":"Zhongcheng Lei , Luis de la Torre , Francisco-José Mañas-Álvarez , Wenshan Hu","doi":"10.1016/j.jii.2025.100902","DOIUrl":"10.1016/j.jii.2025.100902","url":null,"abstract":"<div><div>Networked control systems are critical in industrial applications but remain vulnerable to controller failures, which can destabilize operations. Blockchain technology offers a decentralized solution to enhance reliability. While blockchain technologies have been mainly used in financial systems (such as cryptocurrencies) so far, they are now being used in an increasing number of applications (such as logistics, power grids, or the Internet of Things) due to their powerful features and advantages. In this article, the use of blockchains is proposed and explored to deploy decentralized and reliable controllers. A blockchain-based controller architecture is presented to provide controllers that are permanently available, open accessible, and open source. Time to transaction finality and cost for transactions are analyzed in different blockchain networks, thus identifying their suitability. Our analysis reveals that blockchain networks can potentially be applied in slow processes with big enough time constants. Moreover, we propose the integration of event-based control to reduce transaction costs, thereby enhancing the viability of blockchain technologies in networked control systems. To demonstrate the practical application and cost efficiency of our approach, we present a case study focusing on a greenhouse climate control system. Results show that feasible blockchain networks – those compatible with sampling period constraints – consistently reduce control costs. For instance, on Fantom blockchain, event-based control achieved a 27.73-fold reduction in average control costs across six system variables over the eight-day operation period.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100902"},"PeriodicalIF":10.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strategic Cost Allocation with Value Stream Costing: Data-Driven Decision Analysis in Textile Manufacturing 价值流成本的战略成本分配：纺织制造业数据驱动决策分析

IF 15.7 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-09 DOI: 10.1016/j.jii.2025.100906

Mehmet Özçalıcı, Hasan Emin Gürler, Ahmet Kaya, Dragan Pamucar, Nazan Güngör Karyağdı, Ayşegül Ciğer

{"title":"Strategic Cost Allocation with Value Stream Costing: Data-Driven Decision Analysis in Textile Manufacturing","authors":"Mehmet Özçalıcı, Hasan Emin Gürler, Ahmet Kaya, Dragan Pamucar, Nazan Güngör Karyağdı, Ayşegül Ciğer","doi":"10.1016/j.jii.2025.100906","DOIUrl":"https://doi.org/10.1016/j.jii.2025.100906","url":null,"abstract":"Cost allocation holds paramount importance for businesses, serving as a fundamental aspect of competitiveness in the contemporary market milieu. This includes maintaining high-quality standards in products or services, alongside operational flexibility to adapt to changing customer demands and market conditions. Moreover, accurate assessment of product costs is crucial for guaranteeing the profitability of the company and maximizing the efficient utilization of operational resources. Businesses using the traditional costing approach may face difficulties when allocating total production expenses to individual products. Hence, this study aims to comprehensively analyze the cost system of a medium-sized textile company by incorporating principles of value stream costing. It employs methodologies namely COBRAC, FUCOM, and BWM to identify key cost drivers. The firm identified 12 value streams for its five products and relied on expert opinion to assess costs for eight of them without drivers. The results indicated that the method chosen for cost calculation notably impacts the gross profit showcased in the income statement. Specifically, the FUCOM approach emerges with the highest gross profit among the evaluated methods, closely trailed by the BWM technique, whereas the employment of the COBRAC method yields a relatively lower gross profit value. The suggested model will empower manufacturing firms to pinpoint product costs and effectively attain a sustainable competitive advantage.","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"38 1","pages":""},"PeriodicalIF":15.7,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review of manufacturing integration between production, maintenance and quality artificial intelligence systems 生产、维修和质量人工智能系统制造集成研究综述

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-08 DOI: 10.1016/j.jii.2025.100910

Bruno Mota, Pedro Faria, Carlos Ramos, Zita Vale

{"title":"Review of manufacturing integration between production, maintenance and quality artificial intelligence systems","authors":"Bruno Mota, Pedro Faria, Carlos Ramos, Zita Vale","doi":"10.1016/j.jii.2025.100910","DOIUrl":"10.1016/j.jii.2025.100910","url":null,"abstract":"<div><div>High inflation is causing major manufacturing cost increases, making optimizing production lines a priority in Industry 5.0 manufacturing. As a result, there has been a rising interest in reducing these costs by more efficiently optimizing production, maintenance, and quality costs. This can be accomplished in manufacturing systems by integrating production task and maintenance activity scheduling, predictive maintenance, and quality control, with the application of artificial intelligence, information integration, and interoperability techniques. Accordingly, the present paper’s premise is to perform a literature review regarding production, maintenance, and quality integration in manufacturing environments. It aims to answer the main research question: “What are the current state-of-the-art artificial intelligence techniques applied in production/maintenance scheduling, predictive maintenance, and quality control integration?”. To investigate this, a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-like methodology is followed to find the most efficient, reliable, and robust artificial intelligence techniques for production, maintenance, and quality optimization in production lines. Results show that Genetic Algorithms, Reinforcement Learning, Artificial Neural Networks, and Random Forests are among the most often used algorithms in the literature. Furthermore, integration between production/maintenance scheduling and predictive maintenance is done primarily through the rescheduling of production plans when a machine failure is detected. In addition, the same system employed for predictive maintenance is often integrated into also predicting product quality. However, while there have been some accomplishments in this field, research that considers full production, maintenance, and quality integration is still lacking, even if there is an increasing trend of research on this topic.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100910"},"PeriodicalIF":10.4,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An advanced robust possibilistic chance-constrained programming model for the animal fat-based biodiesel supply chain network 基于动物脂肪的生物柴油供应链网络的一种先进鲁棒可能性机会约束规划模型

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-08 DOI: 10.1016/j.jii.2025.100884

Biswajit Sarkar , Shubham Kumar Singh , Anand Chauhan

{"title":"An advanced robust possibilistic chance-constrained programming model for the animal fat-based biodiesel supply chain network","authors":"Biswajit Sarkar , Shubham Kumar Singh , Anand Chauhan","doi":"10.1016/j.jii.2025.100884","DOIUrl":"10.1016/j.jii.2025.100884","url":null,"abstract":"<div><div>The demand for non-renewable energy has grown due to rapidly depleting fossil fuels and rising energy demand. Biofuel can be utilized in engines without modification to reduce air pollution and carbon emissions and is a significant replacement for fossil fuels. Biodiesel can be produced from various inedible and edible biomass. Animal fat is a reasonable substitute among inedible resources due to its readily available and reasonably priced nature. Furthermore, the efficacy of the supply chain network at the strategic and tactical planning levels is compromised by risks of disruption due to labor strikes, natural disasters, operational downtime, and data uncertainty. This study proposes a robust possibilistic chance-constrained programming model for optimizing the animal fat-based biodiesel supply chain network under uncertainty. The model incorporates strategic and tactical planning decisions while accounting for potential disruptions and operational risks. The biodiesel smart manufacturing system reduces the amount of contaminants in the biodiesel with variable production rate, and an autonomation inspection system detects contaminants in the biodiesel. The biodiesel is purified in biorefineries after biodiesel natural manufacturing. The demand for biodiesel depends on the efficiency of awareness towards biodiesel and its selling price. To enhance resilience, the study introduces a p-robust algorithm that maximizes profitability under disruptive scenarios. A numerical example is analyzed, and the repercussions of the numerical example reveal that lower selling price and less awareness efficiency with more awareness expenditure and high selling price and awareness efficiency with less awareness expenditure increase the overall profit of the system. The findings of the designed model is valuable for policymakers to handle the uncertainty of a sustainable biodiesel supply chain network and biofuel production industry.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100884"},"PeriodicalIF":10.4,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A case study on implementing a flexible IIoT service framework for the integration of machine tools 为机床集成实现灵活的工业物联网服务框架的案例研究

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-07 DOI: 10.1016/j.jii.2025.100908

Wen-Ching Chen, Bo-Yu Ji, Hung-Hsiang Chen

{"title":"A case study on implementing a flexible IIoT service framework for the integration of machine tools","authors":"Wen-Ching Chen, Bo-Yu Ji, Hung-Hsiang Chen","doi":"10.1016/j.jii.2025.100908","DOIUrl":"10.1016/j.jii.2025.100908","url":null,"abstract":"<div><div>This paper presents the IIoT (Industrial Internet of Things) Gateway, an intermediary service framework designed to address the core challenges of industrial information integration. By creating a seamless bridge between OT (Operational Technology) systems and modern IT (Information Technology) infrastructures, our work provides a practical solution that directly contributes to the field of industrial information integration. The framework simplifies the integration process for information service providers by facilitating seamless communication and data exchange between diverse PLC (Programmable Logic Controller) devices and enterprise information systems. It achieves this by leveraging a combination of Operational Technology (OT) protocols, such as OPC UA (Open Platform Communications Unified Architecture) and Modbus, and Information Technology (IT) standards, including MQTT (Message Queuing Telemetry Transport) and JSON (JavaScript Object Notation). The proposed IIoT Gateway enables application engineers to utilize standardized protocols and JSON for control commands, data exchange, and real-time monitoring via webhook technology, significantly reducing development complexity and project timelines. The framework was initially implemented using a monolithic architecture and later refactored into a microservice-based architecture, leveraging Spring Cloud and Nacos to enhance scalability and flexibility. The IIoT Gateway has been successfully integrated and validated in a real-world industrial environment at Everising Machine Co., demonstrating high availability and stability. This work provides a practical blueprint for OT/IT convergence, with future research directions focused on visualized data mapping, AI-enabled automation, enhanced cybersecurity and performance optimization.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100908"},"PeriodicalIF":10.4,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On-device learning based vulnerability detection in IoT environment 物联网环境中基于设备上学习的漏洞检测

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-05 DOI: 10.1016/j.jii.2025.100900

Hongping Li , Shan Cang Li , Geyong Min

引用次数: 0

Industrial digital twin empowered soft sensing for key variables in oxidized pellet rotary kilns 氧化球团回转窑关键变量的工业数字孪生软测量

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-04 DOI: 10.1016/j.jii.2025.100907

Zhangjie Dai , Xiaoran Song , Yue Xu , Yaozu Wang , Zhengjian Liu , Jianliang Zhang

{"title":"Industrial digital twin empowered soft sensing for key variables in oxidized pellet rotary kilns","authors":"Zhangjie Dai , Xiaoran Song , Yue Xu , Yaozu Wang , Zhengjian Liu , Jianliang Zhang","doi":"10.1016/j.jii.2025.100907","DOIUrl":"10.1016/j.jii.2025.100907","url":null,"abstract":"<div><div>The grate-kiln oxidized pellet process plays a crucial role in the ironmaking process, and its efficient operation is of great significance for improving energy efficiency and environmental performance. However, the complexity of the rotary kiln process and the difficulty in directly measuring its internal state limit the monitoring and optimization of the production process. Digital twin technology, as a key enabler of the industrial internet of things in Industry 4.0, can create a virtual copy of a physical entity, enabling interaction between virtual and real systems and real-time monitoring, thus providing an innovative solution for intelligence-driven optimization of smart rotary kilns. Under this background, this study constructs a digital twin system for rotary kilns, which integrates key technologies including a three-dimensional temperature field simulation model, wall thickness monitoring model, and reduced-order model. A multi-physics coupling approach was employed to simulate the kiln's internal temperature field distribution. This simulation accounts for critical processes including pulverized coal combustion and pellet oxidation reactions. To enhance computational efficiency, we constructed a reduced-order temperature field model using random forest algorithms optimized by genetic algorithms. Wall thickness monitoring and caking detection were achieved through laser scanning technology combined with heat transfer principles. Field validation demonstrated the system's effectiveness: temperature prediction errors remained below 1 %, while wall thickness estimation accuracy reached 90 %. These results enable real-time operational guidance for production sites. Additionally, this method offers functions such as temperature monitoring alerts, caking/wall thickness monitoring, and prediction of caking growth trends, which are important for optimizing the production process and ensuring the safe operation of equipment.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100907"},"PeriodicalIF":10.4,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human-centric artificial intelligence towards Industry 5.0: retrospect and prospect 面向工业5.0的以人为中心的人工智能：回顾与展望

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-03 DOI: 10.1016/j.jii.2025.100903

Jiahe Yan , Zean Liu , Jiewu Leng , J.Leon Zhao , Chong Chen , Ding Zhang , Yong Tao , Yiwei Wang , Tingyu Liu , Chao Zhang , Yifei Tong , Dimitris Mourtzis , Lihui Wang

{"title":"Human-centric artificial intelligence towards Industry 5.0: retrospect and prospect","authors":"Jiahe Yan , Zean Liu , Jiewu Leng , J.Leon Zhao , Chong Chen , Ding Zhang , Yong Tao , Yiwei Wang , Tingyu Liu , Chao Zhang , Yifei Tong , Dimitris Mourtzis , Lihui Wang","doi":"10.1016/j.jii.2025.100903","DOIUrl":"10.1016/j.jii.2025.100903","url":null,"abstract":"<div><div>The technology-driven Industry 4.0 paradigm is in a prosperous stage. Meanwhile, the industry is shifting towards a more human-centric, sustainable, and resilient paradigm, which is envisioned as a value-oriented Industry 5.0. Embodied Artificial Intelligence (AI) has shown promising benefits, but challenges persist in the proper orchestration between AI and human beings. Human-Centric Artificial Intelligence (HCAI) emphasizes that AI systems should enhance and complement human abilities rather than replace humans. It focuses on the interaction between humans and AI, aims to improve human well-being, and ensures that AI technologies are consistent with human values and needs. HCAI prioritizes user experience and ethical considerations by following three principles: being inspired by human intelligence, guided by human impact, and augmenting human capabilities. This paper examines the growing trend of deep integration between AI and human intelligence in industries, emphasizing that AI development necessitates the interdependence of technology, people, and ethics to create reliable, safe, and trustworthy systems. This paper conducts a detailed analysis of the evolution stages and modes of human-AI collaboration in industry. Based on an in-depth examination of enablers of HCAI models in industry, this paper examines HCAI applications for the product lifecycle management. Social barriers, technology challenges, and future research directions of HCAI are underscored, respectively. We believe that our effort lays a foundation for unlocking the power of HCAI during the transition from Industry 4.0 to Industry 5.0.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100903"},"PeriodicalIF":10.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144564007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable deep learning framework for residual stress monitoring in laser shock peening via acoustic emission 激光冲击强化声发射残余应力监测的可解释深度学习框架

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-07-03 DOI: 10.1016/j.jii.2025.100904

Rui Qin , Zhifen Zhang , James Marcus Griffin , Jie Wang , Guangrui Wen , Weifeng He , Xuefeng Chen , Jing Huang

{"title":"Explainable deep learning framework for residual stress monitoring in laser shock peening via acoustic emission","authors":"Rui Qin , Zhifen Zhang , James Marcus Griffin , Jie Wang , Guangrui Wen , Weifeng He , Xuefeng Chen , Jing Huang","doi":"10.1016/j.jii.2025.100904","DOIUrl":"10.1016/j.jii.2025.100904","url":null,"abstract":"<div><div>In the field of intelligent manufacturing, leveraging acoustic emission (AE) technology for quality monitoring and assurance during laser manufacturing processes is paramount. Despite this, current monitoring techniques struggle to accurately characterize the time-frequency distribution and transient dynamics of AE signals, and there exists a paucity of neural network models tailored for these specific analytical tasks. To bridge this gap, this paper presents a cutting-edge monitoring approach that integrates a Bi-Differential Convolutional Network (BDCN) with a Frequency Bands Recalibration Spectrogram (FBRS). Firstly, a novel analytical technique employing FBRS for transient AE signals is introduced, which adaptively redistributes frequency resolution to highlight informative components within a constrained pixel space. The BDCN, a groundbreaking nonlinear network model, jointly performs directional feature processing and stress state classification by incorporating two specialized functional modules designed for horizontal and vertical differencing. The model emphasizes directional texture and gradient patterns while mitigating low-frequency feature loss through complementary enhancement strategies. The efficacy of the proposed methodology has been empirically confirmed through rigorous testing on aluminum alloy 7075 and titanium alloy TC4. When juxtaposed with state-of-the-art networks, the presented monitoring strategy exhibits enhanced discriminative precision and robustness, signifying its potential in the domain of intelligent manufacturing quality assurance.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100904"},"PeriodicalIF":10.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0