Journal of Intelligent Manufacturing最新文献_第4页

Enhancing weld line visibility prediction in injection molding using physics-informed neural networks 利用物理信息神经网络加强注塑成型中的焊缝可见度预测

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-13 DOI: 10.1007/s10845-024-02460-w

Andrea Pieressa, Giacomo Baruffa, Marco Sorgato, Giovanni Lucchetta

{"title":"Enhancing weld line visibility prediction in injection molding using physics-informed neural networks","authors":"Andrea Pieressa, Giacomo Baruffa, Marco Sorgato, Giovanni Lucchetta","doi":"10.1007/s10845-024-02460-w","DOIUrl":"https://doi.org/10.1007/s10845-024-02460-w","url":null,"abstract":"This study introduces a novel approach using Physics-Informed Neural Networks (PINN) to predict weld line visibility in injection-molded components based on process parameters. Leveraging PINNs, the research aims to minimize experimental tests and numerical simulations, thus reducing computational efforts, to make the classification models for surface defects more easily implementable in an industrial environment. By correlating weld line visibility with the Frozen Layer Ratio (FLR) threshold, identified through limited experimental data and simulations, the study generates synthetic datasets for pre-training neural networks. This study demonstrates that a quality classification model pre-trained with PINN-generated datasets achieves comparable performance to a randomly initialized network in terms of Recall and Area Under the Curve (AUC) metrics, with a substantial reduction of 78% in the need for experimental points. Furthermore, it achieves similar accuracy levels with 74% fewer experimental points. The results demonstrate the robustness and accuracy of neural networks pre-trained with PINNs in predicting weld line visibility, offering a promising approach to minimizing experimental efforts and computational resources.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"25 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141608985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revolutionizing sheet metal stamping through industry 5.0 digital twins: a comprehensive review 通过工业 5.0 数字孪生革新钣金冲压：全面回顾

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-11 DOI: 10.1007/s10845-024-02453-9

Ossama Abou Ali Modad, Jason Ryska, Abdallah Chehade, Georges Ayoub

{"title":"Revolutionizing sheet metal stamping through industry 5.0 digital twins: a comprehensive review","authors":"Ossama Abou Ali Modad, Jason Ryska, Abdallah Chehade, Georges Ayoub","doi":"10.1007/s10845-024-02453-9","DOIUrl":"https://doi.org/10.1007/s10845-024-02453-9","url":null,"abstract":"In this manuscript, we present a comprehensive overview of true digital twin applications within the manufacturing industry, specifically delving into advancements in sheet metal forming. A true digital twin is a virtual representation of a physical process or production system, enabling bidirectional data exchange between the physical and digital domains and facilitating real-time optimization of performance and decision-making through synchronized data from sensors. Hence, we will highlight the difference between Industry 4.0 and the digital twin concept, which is considered synonymous with Industry 5.0. Additionally, we will be outlining the relationship between the true digital twin and Zero Defect Manufacturing. In manufacturing processes, including sheet metal stamping, the advantages of high production speed, cost-effective tooling, and consistent component production are counterbalanced by the challenge of dimensional variability in finished parts, which is influenced by process parameters. Data collection, storage, and analysis are essential for understanding manufactured parts variability, and leveraging true digital twins ensures high-quality parts production and processes optimization.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"55 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141609081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of multi-modal feedback channel of human–robot cognitive interface for teleoperation in manufacturing 设计用于制造业远程操作的人机认知界面的多模式反馈通道

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-09 DOI: 10.1007/s10845-024-02451-x

Chen Zheng, Kangning Wang, Shiqi Gao, Yang Yu, Zhanxi Wang, Yunlong Tang

{"title":"Design of multi-modal feedback channel of human–robot cognitive interface for teleoperation in manufacturing","authors":"Chen Zheng, Kangning Wang, Shiqi Gao, Yang Yu, Zhanxi Wang, Yunlong Tang","doi":"10.1007/s10845-024-02451-x","DOIUrl":"https://doi.org/10.1007/s10845-024-02451-x","url":null,"abstract":"Teleoperation, which is a specific mode of human–robot collaboration enabling a human operator to provide instructions and monitor the actions of the robot remotely, has proved beneficial for application to hazardous and unstructured manufacturing environments. Despite the design of a command channel from human operators to robots, most existing studies on teleoperation fail to focus on the design of the feedback channel from the robot to the human operator, which plays a crucial role in reducing the cognitive load, particularly in precise and concentrated manufacturing tasks. This paper focuses on designing a feedback channel for the cognitive interface between a human operator and a robot considering human cognition. Current studies on human–robot cognitive interfaces in robot teleoperation are extensively surveyed. Further, the modalities of human cognition that foster understanding and transparency during teleoperation are identified. In addition, the human–robot cognitive interface, which utilizes the proposed multi-modal feedback channel, is developed on a teleoperated robotic grasping system as a case study. Finally, a series of experiments based on different modal feedback channels are conducted to demonstrate the effectiveness of enhancing the performance of the teleoperated grasping of fragile products and reducing the cognitive load via the objective aspects of experimental results and the subjective aspects of operator feedback.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"52 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stable pushing in narrow passage environment using a modified hybrid A* algorithm 使用改进的混合 A* 算法在狭窄通道环境中稳定推进

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-08 DOI: 10.1007/s10845-024-02455-7

Kuan-Cheng Kuo, Kuei-Yuan Chan

{"title":"Stable pushing in narrow passage environment using a modified hybrid A* algorithm","authors":"Kuan-Cheng Kuo, Kuei-Yuan Chan","doi":"10.1007/s10845-024-02455-7","DOIUrl":"https://doi.org/10.1007/s10845-024-02455-7","url":null,"abstract":"Pushing is a fundamental ability in mobile robotics for transporting objects when grippers are not applicable. A successful “box-pushing” requires good coordination between model prediction, pushing strategy, and motion planning, therefore presents a well-known challenge in mobile robot transportation community. However, current research often focuses on local planning for altering push direction, while global planning remains inadequate. This can lead to inefficient pushing trajectories, especially in narrow passages where robots may unintentionally push the box into a dead end due to the lack of robust global path. To address this, we propose the use of stable pushing as an effective technique and develop a unique global planning approach based on the hybrid A* algorithm. We enhance the hybrid A* algorithm by modifying the node expansion approach and incorporating a mechanism for predicting push direction, enabling the system to adapt to changing push side behavior and discover optimal pathways. Extensive simulations validate our system’s effectiveness in handling complex scenarios with limited passageways. As a result, our method significantly improves the robot’s capability to generate superior global paths for box-pushing, mitigating wasteful trajectories and enhancing overall performance.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"24 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two-phase cost-sensitive-learning-based framework on customer-side quality inspection for TFT-LCD industry 基于两阶段成本敏感学习的 TFT-LCD 行业客户方质量检测框架

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-07 DOI: 10.1007/s10845-024-02448-6

Ming-Sung Shih, James C. Chen, Tzu-Li Chen, Ching-Lan Hsu

{"title":"Two-phase cost-sensitive-learning-based framework on customer-side quality inspection for TFT-LCD industry","authors":"Ming-Sung Shih, James C. Chen, Tzu-Li Chen, Ching-Lan Hsu","doi":"10.1007/s10845-024-02448-6","DOIUrl":"https://doi.org/10.1007/s10845-024-02448-6","url":null,"abstract":"The Covid-19 outbreak in 2020 boosted the stay-at-home economy, causing a surge in electronics industry demand, especially benefiting the LCD panel sector. However, as the pandemic situation improved, countries revised policies, leading to the gradual discontinuation of remote work arrangements in various industries. This resulted in declining dividends for the stay-at-home economy. The decreased demand created intense competition within the TFT-LCD industry, urging panel companies to prioritize product quality enhancement to meet customer expectations. Panel quality inspection heavily relied on manual labor, causing varying inspection levels due to subjective judgments. Understanding and aligning with customer expectations regarding product quality inspections became imperative. Identifying defective products during inspection led to additional costs for the companies. Balancing customer product quality requirements and re-inspection costs became crucial for optimal benefits. This study addresses the binary classification problem of customer-side quality inspection through cost-sensitive learning. The predictive model considers panel process yield, production history, customer feedback, inspection capacity constraints, and cost minimization to predict panel quality as accepted or defective. To tackle the highly imbalanced data, a two-phase cost-sensitive-learning-based framework is proposed, combining data preprocessing methods and models, while considering re-inspection capacity constraints and costs to enhance accuracy. The model’s evaluation uses key performance indicators like AUC and G-mean. Actual inspection cost and defective parts per million (DPPM) are calculated based on the company’s practical assessment. Two products are used for experimentation to validate the proposed model, demonstrating over 50% reduction in inspection cost and over 10% improvement in DPPM.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"46 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MPTP-Net: melt pool temperature profile network for thermal field modeling in beam shaping of laser powder bed fusion MPTP-Net：熔池温度曲线网络，用于激光粉末床熔化的光束整形热场建模

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-06 DOI: 10.1007/s10845-024-02449-5

Shengli Xu, Rahul Rai, Robert D. Moore, Giovanni Orlandi, Fadi Abdeljawad

{"title":"MPTP-Net: melt pool temperature profile network for thermal field modeling in beam shaping of laser powder bed fusion","authors":"Shengli Xu, Rahul Rai, Robert D. Moore, Giovanni Orlandi, Fadi Abdeljawad","doi":"10.1007/s10845-024-02449-5","DOIUrl":"https://doi.org/10.1007/s10845-024-02449-5","url":null,"abstract":"To thoroughly investigate the impact of beam shaping on melt pool behavior and accurately predict the microstructure and mechanical properties of the final product in laser powder bed fusion (LPBF) for metal additive manufacturing (AM), it is crucial to efficiently model the temperature profiles of melt pools subjected to different laser beam shapes. Numerical methods necessitate significant computational resources and time. Machine learning (ML) based surrogate models, on the other hand, are incapable of precisely predicting three-dimensional temperature profiles and lack generalizability in modeling distinct beam shapes beyond the Gaussian beam. To address these limitations, this paper introduces the Melt Pool Temperature Profile Network (MPTP-Net), a novel model developed to efficiently predict the three-dimensional temperature profile of the melt pool based on laser beam parameters, including power, scan velocity, standard deviation of power distribution, and ring radius (applicable to ring beams). By incorporating an auxiliary geometry branch alongside the temperature profile head, our constructed multi-task learning framework is capable of learning the underlying connection between the laser beam parameters and melt pool morphology in the latent space. Hence, the proposed model improves accuracy and generalizability in predicting the 8-layer temperature profile across a wide range of melt pool dimensions. Additionally, the progressively upsampling module of MPTP-Net contributes in predicting the high-fidelity temperature profile with accurate boundaries and smooth temperature gradients of the melt pool. Through extensive validation using datasets derived from both Gaussian and ring beams, our model consistently demonstrates a superior degree of concordance between the predicted and actual melt pool temperature profiles than the state-of-the-art methods.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"26 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient textile anomaly detection via memory guided distillation network 通过记忆引导蒸馏网络高效检测纺织品异常情况

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-03 DOI: 10.1007/s10845-024-02445-9

Jingyu Yang, Haochen Wang, Ziyang Song, Feng Guo, Huanjing Yue

{"title":"Efficient textile anomaly detection via memory guided distillation network","authors":"Jingyu Yang, Haochen Wang, Ziyang Song, Feng Guo, Huanjing Yue","doi":"10.1007/s10845-024-02445-9","DOIUrl":"https://doi.org/10.1007/s10845-024-02445-9","url":null,"abstract":"Textile anomaly detection with high accuracy and fast frame rates are desired in real industrial scenarios. To this end, we propose an efficient memory guided distillation network, which includes encoder, decoder, and segmentation networks. Instead of utilizing a pre-trained large network as the encoder, we utilize a small feature extraction network, whose features are distilled from a teacher network. To improve the reconstruction quality with small networks, we further introduce an efficient memory bank, whose features are extracted by the teacher network with normal reference inputs. Considering the blurry reconstruction may lead to false-positive results, we further introduce a pseudo-normal simulation method by augmenting the inputs with blurry effects. Besides, we construct a Textile Anomaly dataset (Textile AD) for textile anomaly detection with pixel-wise labels for comprehensively evaluation and our method demonstrates superior performance on the Textile AD dataset. Additionally, we performed experiments using the publicly accessible MVTec-AD industrial anomaly dataset and our approach aligns closely with the performance of cutting-edge methodologies, which demonstrates that our method is applicable to other industrial product categories. Our Textile AD is shared in https://github.com/Songziyangtju/Textile-AD-dataset.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"31 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Foreground–background separation transformer for weakly supervised surface defect detection 用于弱监督表面缺陷检测的前景-背景分离转换器

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-03 DOI: 10.1007/s10845-024-02446-8

Xiaoheng Jiang, Jian Feng, Feng Yan, Yang Lu, Quanhai Fa, Wenjie Zhang, Mingliang Xu

{"title":"Foreground–background separation transformer for weakly supervised surface defect detection","authors":"Xiaoheng Jiang, Jian Feng, Feng Yan, Yang Lu, Quanhai Fa, Wenjie Zhang, Mingliang Xu","doi":"10.1007/s10845-024-02446-8","DOIUrl":"https://doi.org/10.1007/s10845-024-02446-8","url":null,"abstract":"In industrial scenarios, weakly supervised pixel-level defect detection methods leverage image-level labels for training, significantly reducing the effort required for manual annotation. However, existing methods suffer from confusion or incompleteness in predicting defect regions since defects usually show weak appearances that are similar to the background. To address this issue, we propose a foreground–background separation transformer (FBSFormer) for weakly supervised pixel-level defect detection. FBSFormer introduces a foreground–background separation (FBS) module, which utilizes the attention map to separate the foreground defect feature and background feature and pushes their distance intrinsically by learning with opposite labels. In addition, we present an attention-map refinement (AMR) module, which aims to generate a more accurate attention map to better guide the separation of defect and background features. During the inference stage, the refined attention map is combined with the class activation map (CAM) corresponding to the defect feature of FBS to generate the final result. Extensive experiments are conducted on three industrial surface defect datasets including DAGM 2007, KolektorSDD2, and Magnetic Tile. The results demonstrate that the proposed approach achieves outstanding performance compared to the state-of-the-art methods.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"179 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trigonometric-based mechanisms hybridized African vulture optimization algorithm for multi-manned disassembly line balancing involving worker heterogeneity and collaboration 基于三角函数机制的混合非洲秃鹫优化算法，用于涉及工人异质性和协作的多人拆卸线平衡

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-02 DOI: 10.1007/s10845-024-02443-x

Yufan Huang, Binghai Zhou

{"title":"Trigonometric-based mechanisms hybridized African vulture optimization algorithm for multi-manned disassembly line balancing involving worker heterogeneity and collaboration","authors":"Yufan Huang, Binghai Zhou","doi":"10.1007/s10845-024-02443-x","DOIUrl":"https://doi.org/10.1007/s10845-024-02443-x","url":null,"abstract":"The rapid replacement of large-scale end-of-life (EOL) heavy machineries like automobiles, aircrafts and industrial robots necessitates efficient resource recovery to promote sustainable and eco-friendly manufacturing. This study therefore focuses on multi-manned disassembly lines in recycling large-scale products, bridging the gap between theory and practice. We introduce complex, safety-sensitive tasks that require collaborative efforts of multiple workers in the Multi-Manned Disassembly Line Balancing Problem (MMDLBP) for the first time. We also consider worker heterogeneity due to varying training and skills, as manual stations are inherently worker-dependent in nature. To address this Multi-Manned Disassembly Line Balancing Problem with Worker Heterogeneity and Collaboration (MMDLBP-HC), we establish a mixed-integer programming model to minimize cycle time and labor cost simultaneously. Given its NP-hard nature, we develop a Multi-Mechanism-Enhanced Bi-Objective African Vultures Optimization Algorithm (MBAVOA). It employs specified encoding with numerical branching, precedence-priority concurrent decoding, and selective opposition-based learning. We also combine trigonometric-based mechanisms with the African vulture optimization algorithm (AVOA) to enhance exploration. Additionally, adaptive neighborhood search mechanisms are tailored for inter-individual information exchange. Numerical experiments compare MBAVOA to four meta-heuristics and an exact algorithm. The results demonstrate the model accuracy and the effectiveness of the encoding and decoding mechanisms, while MBAVOA outperforms benchmark algorithms significantly. Finally, we offer managerial applications to guide practitioners in balancing plan formation and training program design.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"24 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved wafer map defect pattern classification using automatic data augmentation based lightweight encoder network in contrastive learning 在对比学习中使用基于轻量级编码器网络的自动数据增强技术改进晶片图缺陷模式分类

IF 8.3 2区工程技术

Journal of Intelligent Manufacturing Pub Date : 2024-07-01 DOI: 10.1007/s10845-024-02444-w

Yi Sheng, Jinda Yan, Minghao Piao

{"title":"Improved wafer map defect pattern classification using automatic data augmentation based lightweight encoder network in contrastive learning","authors":"Yi Sheng, Jinda Yan, Minghao Piao","doi":"10.1007/s10845-024-02444-w","DOIUrl":"https://doi.org/10.1007/s10845-024-02444-w","url":null,"abstract":"In recent years, supervised learning has been the predominant method for wafer map defect pattern classification (WM-DPC), requiring a substantial amount of labeled data to build effective models. Nonetheless, gathering industrial data is challenging and demands significant manual labeling efforts, making it both expensive and time-consuming. To overcome these obstacles, we introduced a contrastive learning framework for WM-DPC based on automatic data augmentation. This innovative augmentation approach takes account of the regional defect density characteristic of various defect types, addressing the limitations of traditional fixed data augmentation and improving the model’s generalization capacity. The framework operates in two phases. At first, a lightweight encoder extracts rich representative features from unlabeled data. Then, the classification network is fine-tuned with a limited labeled data set. Experimental outcomes using the public WM-811K dataset showed that the proposed automatic data augmentation and lightweight encoder effectively captured detailed representative features from unlabeled data, and achieved an average accuracy close to 91% after fine-tuning with minimal labeled data.","PeriodicalId":16193,"journal":{"name":"Journal of Intelligent Manufacturing","volume":"13 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0