Industrial Anomaly Detection

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Overview

Industrial anomaly detection aims to identify defects or unusual behavior when examples of failures are scarce and normal operation can vary across products, machines, and conditions. Visual methods often learn normal patterns with reconstruction models, patch-memory methods such as PatchCore, or pretrained vision features; synthetic defects and vision-language models are increasingly used to extend detection to new defect types. For sensor and audio data, common approaches include forecasting and reconstruction, autoencoders, and graph models that capture relationships among signals, with benchmarks such as MVTec AD, VisA, SWaT, and WADI. A central challenge is moving from strong results on curated benchmarks to reliable deployment under shifts, contaminated training data, tight false-alarm limits, and edge-device constraints.

Latest papers

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260 papers33 papers in the last four weeks, up 38% on the four weeks before. 0.2% of all new papers.

  1. SGDB: Semantic-Geometric Decoupling and Evidence Binding for Logical Anomaly Detection

    Oct 26, 2026Chenrui Ji, Jiafan Lu, Zilu Luo +3Anomaly DetectionIndustrial Anomaly Detection

    School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China

  2. Real-Time Conveyor Belt Defect Detection via Edge TPU-Accelerated YOLOv11 on Raspberry Pi 5

    Oct 25, 2026Muhammad Nur Bijak Bestari, Mulki Indana ZulfaIndustrial Anomaly DetectionIndustrial Inspection

    Department of Electrical Engineering, Faculty of Engineering, Universitas Jenderal Soedirman, Purwokerto 53123, Central Java, Indonesia

  3. Flownomaly: Single-Step Conditional-Mean Recovery for Few-Shot Anomaly Detection

    Oct 23, 2026Bernardo Perrone Ribeiro, Erkut Akdag, Egor BondarevFew-Shot Anomaly DetectionIndustrial Anomaly Detection

    AIMS Group, Department of Electrical Engineering, Eindhoven University of Technology

  4. HARMONY: Hierarchical Anchor Retrieval on Manifold for Oblivious-source Machinery Acoustic Anomaly Detection

    Oct 22, 2026Yuhang Zhang, Yang Li, Qiang Wu +1Anomaly DetectionIndustrial Anomaly Detection

    School of Software and Microelectronics, Peking University, Beijing, China · Independent Researcher · Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China +2

  5. Region-Aware Multi-View Inspection Using Deep Learning and Domain-Informed Decision Fusion

    Oct 21, 2026Srivishnu Ethirajulu Krishnaraj, Rishikesh R. ChopadeIndustrial InspectionIndustrial Anomaly Detection

    Bosch Limited, India

  6. Online Open-World Wafer Defect Discovery using Hyperdimensional Computing

    Oct 20, 2026Quanling Zhao, Ava Emami, Tsuyoshi Idé +4Online Anomaly DetectionIndustrial Anomaly Detection

    University of California San Diego · IBM Research · Anderon

  7. Few-Shot Adaptation for Anomalous Sound Detection at Low False-Positive Rate

    Oct 14, 2026Simone Lugani, Christof Pichler, Hannes Wegleiter +3Anomaly DetectionIndustrial Anomaly Detection

    DITEN, University of Genoa, Genoa, Italy · Christian Doppler Laboratory for Measurement Systems for Harsh Operating Conditions, EMS, TU Graz, Graz, Austria · voestalpine Stahl GmbH, Linz, Austria

  8. Text-Informed Training Data Filtering for Enhanced Virtual Flow Meter Performance

    Oct 14, 2026Kristoffer Hjelmen Nesland, Bjarne Grimstad, Antorweep Chakravorty +1Training Data CurationIndustrial Anomaly Detection

    University of Stavanger, Stavanger, Norway · Solution Seeker AS, Oslo, Norway

  9. CORE: Contrast-and-Reflect for Self-Supervised Prompt Optimization in Anomaly Synthesis

    Oct 14, 2026Haoxiang Rao, Fang Zhao, Zhao Wang +3Synthetic Anomaly GenerationSynthetic Data Augmentation

    School of Intelligence Science and Technology, Nanjing University · China Mobile Zijin Innovation Institute

  10. Cross-Scenario Industrial Defect Detection via Domain-Robust Training and Metric-Aligned Selection

    Oct 14, 2026Dikai Li, Weijia Wang, Yuan-Gen WangIndustrial Anomaly DetectionDomain Generalization

    School of Artificial Intelligence, Guangzhou University, Guangzhou 510006, China

  11. Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies

    Oct 13, 2026Ufuk Efe, Alptekin TemizelAnomaly DetectionIndustrial Anomaly Detection

    Graduate School of Informatics, Middle East Technical University, Üniversiteler Mahallesi, Dumlupınar Bulvarı No:1, Ankara, 06800, Türkiye

  12. Federated Coreset Subsampling for Distributed Memory Banks

    Oct 12, 2026Jason Witzemann, Daniel Pröll, Sebastian HegenbartCoreset SelectionAnomaly Detection

    Digital Factory Vorarlberg GmbH, Dornbirn, Austria · University of Salzburg, Salzburg, Austria · Vorarlberg University of Applied Sciences, Dornbirn, Austria

  13. Distinguishing Process Change, Instrument Fault and Data-Path Corruption in Streaming Telemetry: A Reference Implementation and Benchmark

    Oct 11, 2026Oleksandr KlymenkoFault DiagnosisOnline Anomaly Detection

    Independent Researcher, Poland

  14. InCLAD: A Continual Learning Benchmark for Industrial Visual Anomaly Detection

    Oct 10, 2026Łukasz Marcjan, Dorota Wilk-Kołodziejczyk, Roberto CorizzoTask-Incremental LearningContinual Anomaly Detection

    AGH University of Krakow, Krakow, Poland · American University, Washington, DC, USA

  15. Seamless Deployment of Machine Learning Inference at the Far Edge: An Empirical AWS IoT Greengrass Architecture for Industrial Predictive Maintenance

    Oct 10, 2026Prince Kwabena Appiah Boadu, Jeffery Baafi Kyei, Enoch Kofi Koranteng +1Edge InferenceIndustrial Internet of Things

    Department of Computer Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

  16. Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding?

    Oct 8, 2026Xingwu Zhang, Duanyang Du, Huiling Zhu +5Industrial Anomaly DetectionMultimodal Anomaly Detection

    Hunan University · University of Aberdeen · South China Normal University +1

  17. Efficient Patch-Based Anomaly Detection Fused with Diffusion Driven Generative Modeling for Semiconductor Wafer Bin Map Open Set Anomaly Detection

    Oct 7, 2026Limon Bin Hossain, Md Sadib Rahman AnantaAnomaly DetectionIndustrial Anomaly Detection

    Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, 1000, Bangladesh

  18. Quantum anomaly detection in real scarce data

    Oct 7, 2026Emanuele Casciaro, Fabio Mascherpa, Alfonso Amendola +1Anomaly DetectionTime-Series Anomaly Detection

    Department of Physics and Astrophysics, University of Florence, Via Sansone, 1, Sesto Fiorentino, 50019, Italy · DICOX/C High Performance Computing Center of Excellence, DIT Digital & Information Technology, Eni S.p.A., Via Emilia 1, San Donato Milanese, 20097, Italy

  19. GRC-Net: Global Representation Consistency Network for Unsupervised Multimodal Anomaly Detection

    Oct 7, 2026Seyoung Jeong, Jong Pil Yun, Sang Jun LeeAnomaly DetectionIndustrial Anomaly Detection

    Jeonbuk National University, Jeonju, Republic of Korea · Korea Institute of Industrial Technology (KITECH), Incheon, Republic of Korea · Chung-Ang University, Seoul, Republic of Korea

  20. Anchor and Adapt: Asymmetric Prompt Adaptation for Few-Shot Industrial Anomaly Detection

    Oct 4, 2026Mengyang Zhao, Teng Fu, Haiyang Yu +3Prompt Learning for VLMsFew-Shot Anomaly Detection

    Shanghai Key Lab of Intelligent Information Processing and College of Computer Science and Artificial Intelligence, Fudan University, Shanghai 200433, China

  21. A Data-Driven Framework for Unsupervised Monitoring of Transmission Systems Using End-of-Line Testing Data: A Case Study at Ford Motor Company

    Oct 4, 2026Mohammad N. Bisheh, Mehrdad Moradi, Parinaz Farajiparvar +6Industrial Anomaly DetectionTime-Series Anomaly Detection

    Georgia Tech, Atlanta, Georgia, USA · Ford Motor Company, Dearborn, Michigan, USA

  22. Detecting Defects that Matter: An Application-Driven Benchmark for Anomaly Detection in Manufacturing and Retail Logistics (VAND 4.0 Challenge)

    Oct 3, 2026Lars Heckler-Kram, Dorian Henning, Ashwin Vaidya +6Anomaly DetectionIndustrial Anomaly Detection

    MVTec Software GmbH · Technical University of Munich · Amazon +2

  23. Low-Rank and Structured Sparse Tensor Decomposition for Anomaly Detection in Multivariate Functional Data

    Oct 3, 2026Mohammad N. Bisheh, Che-Yi Liao, Kamran PaynabarAnomaly DetectionIndustrial Anomaly Detection

    School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA · Stewart School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA

  24. Anomaly Detection and Localization for the Pantograph-Catenary System

    Oct 1, 2026Francesco Vitale, Hangli Ge, Francesco FlamminiIndustrial Anomaly DetectionAnomaly Localization

    DIETI University of Naples Federico II Naples, Italy · Interfaculty Initiative in Information Studies The University of Tokyo Tokyo, Japan · DIMAI University of Florence Florence, Italy +1

  25. From Benchmarks to Production: Transferring Time Series Anomaly Detection Methods for Electricity Production Monitoring

    Sep 30, 2026Nicolas Vautier, Paul Caron, Nardi Xhepi +4Interpretable Anomaly DetectionIndustrial Anomaly Detection

    EDF Lab Paris Saclay · EDF, DOAAT · Inria, Ecole Normale Sup´erieure (PSL), CNRS

  26. What Streaming Anomaly Detection Finds (and Misses) in Industrial Time Series

    Sep 30, 2026Magali Parrino, Antoine Ajenjo, Emmanuel Remy +2Online Anomaly DetectionIndustrial Anomaly Detection

    EDF R&D, France · Inria, ENS, CNRS, PSL, France

  27. Deep Learning for Anomaly Detection in Railway Systems: A Structured Survey

    Sep 30, 2026Ammar Bouketta, Smail Niar, Hamza OuarnoughiIndustrial Anomaly DetectionTime-Series Anomaly Detection

    Université Polytechnique Hauts-de-France, LAMIH CNRS UMR 8201, Valenciennes, France · Alstom, Crespin, France · Université Polytechnique Hauts-de-France, LAMIH CNRS UMR 8201, INSA Hauts-de-France, Valenciennes, France +1

  28. Cycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly Detection

    Sep 30, 2026Ammar Bouketta, Smail Niar, Hamza Ouarnoughi +1Industrial Anomaly DetectionFault Detection

    Universit´e Polytechnique Hauts-de-France, LAMIH CNRS UMR 8201, Valenciennes, France · Alstom, Crespin, France · Universit´e Polytechnique Hauts-de-France, LAMIH CNRS UMR 8201, INSA Hauts-de-France, Valenciennes, France +1

  29. Visual Anomaly Synthesis for Model Selection in Data Scarcity

    Sep 29, 2026Daniel Pröll, Thomas Kraxner, Tobias Schaefer +1Industrial Anomaly DetectionSynthetic Anomaly Generation

    Digital Factory Vorarlberg GmbH, Dornbirn, Austria · University of Salzburg, Salzburg, Austria · illwerke vkw AG, Bregenz, Austria +1

  30. FLASH: A "Generate Once, Synthesize Many" Framework for Synthetic Anomaly Generation in Industrial Anomaly Detection

    Sep 29, 2026Abhay Kumar Das, Rajesh Gangireddy, Ashwin Vaidya +1Synthetic Data AugmentationIndustrial Anomaly Detection

    Silicon University, Bhubaneswar, India · Intel