Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing | Paper Citation Record

Observation 49c0873e-ecda-4356-85a0-56b43e94a018 · outbound

This paper cites Machine learning in additive manufacturing: State-of- the-art and perspectives.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Machine learning in additive manufacturing: State-of- the-art and perspectives

Reference 1

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Observation 2aa520b5-274d-4c8c-a5d0-4e3cc87cb21b · outbound

This paper cites Additive manufacturing technologies.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Additive manufacturing technologies

Reference 2

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Observation acdbb155-4976-4c02-9880-bd8573c59a78 · outbound

This paper cites Process Screening in Additive Manufacturing: Detection of Keyhole Mode using Surface Topography and Machine Learning.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Process Screening in Additive Manufacturing: Detection of Keyhole Mode using Surface Topography and Machine Learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.916335Z

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Observation 8af34469-fce4-4050-8348-f5ecf6237e24 · outbound

This paper cites Surface Roughness Repeatability Analysis for Multi-Build Overhang Parts in Powder Bed Fusion Additive Manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Surface Roughness Repeatability Analysis for Multi-Build Overhang Parts in Powder Bed Fusion Additive Manufacturing

Reference 4

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Observation 7fc22c40-7733-49f5-bdd1-3ced37621f28 · outbound

This paper cites In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.898985Z

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Observation febb06c3-55d9-4c87-8826-cbb82fe93710 · outbound

This paper cites Metal-based additive manufacturing condition monitoring: A review on machine learning based approaches.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Metal-based additive manufacturing condition monitoring: A review on machine learning based approaches

Reference 6

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Observation 54472451-d5a6-4196-8c99-58fc46deeecc · outbound

This paper cites A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.881015Z

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Observation 08628bf8-5968-4d53-970a-4a34dadc714b · outbound

This paper cites Leveraging small-scale datasets for additive manufacturing process modeling and part certification: Current practice and remaining gaps.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Leveraging small-scale datasets for additive manufacturing process modeling and part certification: Current practice and remaining gaps

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.871272Z

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Observation 195d6b6c-4b0a-48ad-8a27-c280cdf6366e · outbound

This paper cites Accurate Inverse Process Optimization Framework in Laser Directed Energy Deposition.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Accurate Inverse Process Optimization Framework in Laser Directed Energy Deposition

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:12:14.525185Z

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Observation b806f1a8-66cd-4d3e-a6d5-f5402a7f7cda · outbound

This paper cites Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.862419Z

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Observation e332eba0-503e-43c5-be0b-55c2d261aec3 · outbound

This paper cites Current Applications of Machine Learning in Additive Manufacturing: A Review on Challenges and Future Trends.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Current Applications of Machine Learning in Additive Manufacturing: A Review on Challenges and Future Trends

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.852558Z

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Observation 83b60505-9e2e-4893-9288-510fb1cd518d · outbound

This paper cites Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:12:14.510709Z

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Observation e9ec8ec4-264f-4df4-bc53-40968bd7e8b2 · outbound

This paper cites Inference of Melt Pool Visual Characteristics in Laser Additive Manufacturing Using Acoustic Signal Features and Robotic Motion Data.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Inference of Melt Pool Visual Characteristics in Laser Additive Manufacturing Using Acoustic Signal Features and Robotic Motion Data

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.843341Z

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Observation 183cbbff-5e3d-4107-a970-2964fb1401fe · outbound

This paper cites an unresolved cited work.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Unresolved cited work

Reference 14

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Observation b0aceac1-c03c-479b-a8d2-cadb8b957b08 · outbound

This paper cites On the data quality and imbalance in machine learning- based design and manufacturing—A systematic review.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing On the data quality and imbalance in machine learning- based design and manufacturing—A systematic review

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.825006Z

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Observation 39e8512c-15ef-4c6f-bd3e-f2d8affc19db · outbound

This paper cites A hybrid model compression approach via knowledge distillation for predicting energy consumption in additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing A hybrid model compression approach via knowledge distillation for predicting energy consumption in additive manufacturing

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.816388Z

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Observation 4c157bb7-23e4-4063-93ef-62aa1edd9dce · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Distilling the Knowledge in a Neural Network

Reference 17

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Observation f3d949d6-4572-4bda-bb12-5214e5747193 · outbound

This paper cites Information theory: a tutorial introduction.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Information theory: a tutorial introduction

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.807925Z

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Observation 6ef20109-7292-4635-81f6-0caa98e9eb13 · outbound

This paper cites The elements of statistical learning: data mining, inference, and prediction.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing The elements of statistical learning: data mining, inference, and prediction

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.799348Z

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Observation d2fce074-ad29-4c32-961b-06c02a34c69d · outbound

This paper cites Feature engineering in additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Feature engineering in additive manufacturing

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.790283Z

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Observation a340367d-122e-457f-a759-e2e4bfe52c12 · outbound

This paper cites Feature selection and feature learning in machine learning applications for gas turbines: A review.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Feature selection and feature learning in machine learning applications for gas turbines: A review

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.780733Z

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Observation 3f0260a4-1ce4-4483-aedd-3eefe2316193 · outbound

This paper cites Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.770910Z

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Observation 6e7b64fd-4cac-43d0-be3f-3033a621fbf5 · outbound

This paper cites Active learning via adaptive weighted uncertainty sampling applied to additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Active learning via adaptive weighted uncertainty sampling applied to additive manufacturing

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.760772Z

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Observation 7b4b7d5a-0b9d-4f84-9f75-b94aa3f6c60d · outbound

This paper cites MeltpoolGAN: Melt pool prediction from path- level thermal history.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing MeltpoolGAN: Melt pool prediction from path- level thermal history

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.750757Z

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Observation cec3d956-7a98-4e89-97b5-47f524d60c16 · outbound

This paper cites Selecting subsets of source data for transfer learning with applications in metal additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Selecting subsets of source data for transfer learning with applications in metal additive manufacturing

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.742533Z

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Observation ebcf4266-14fe-4c20-9e54-53ce8fef80cf · outbound

This paper cites Knowledge distillation-based information sharing for online process monitoring in decentralized manufacturing system.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Knowledge distillation-based information sharing for online process monitoring in decentralized manufacturing system

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.733826Z

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Observation a02c061d-dd29-4c29-93b7-0f5a0524e9d3 · outbound

This paper cites In-situ monitoring additive manufacturing process with AI edge computing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing In-situ monitoring additive manufacturing process with AI edge computing

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.725662Z

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Observation 6a352327-597d-44a1-9ee2-1dbae4ebc0a6 · outbound

This paper cites Acoustic anomaly detection in additive manufacturing with long short-term memory neural networks.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Acoustic anomaly detection in additive manufacturing with long short-term memory neural networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.717418Z

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Observation 8e4e0a23-d173-4a26-8b16-0351131877da · outbound

This paper cites Segmentation of Additive Manufacturing Defects Using U-Net.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Segmentation of Additive Manufacturing Defects Using U-Net

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.706998Z

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Observation 9f93585e-a0de-4c53-a000-6aa0814a645b · outbound

This paper cites Augmented time regularized generative adversarial network (atr-gan) for data augmentation in online process anomaly detection.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Augmented time regularized generative adversarial network (atr-gan) for data augmentation in online process anomaly detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.697819Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f4db202-c975-4094-b71a-e14126dc1db0 · outbound

This paper cites Effective variational-autoencoder-based generative models for highly imbalanced fault detection data in semiconductor manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Effective variational-autoencoder-based generative models for highly imbalanced fault detection data in semiconductor manufacturing

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.688524Z

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Observation 072f80a4-00cd-4e86-be3e-1e18385c8c1f · outbound

This paper cites Diffusion generative model-based learning for smart layer-wise monitoring of additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Diffusion generative model-based learning for smart layer-wise monitoring of additive manufacturing

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.679174Z

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Observation 99327ba6-5bb6-4d10-bf9d-27fa607441f1 · outbound

This paper cites Engineering of Additive Manufacturing Features for Data-Driven Solutions: Sources, Techniques, Pipelines, and Applications.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Engineering of Additive Manufacturing Features for Data-Driven Solutions: Sources, Techniques, Pipelines, and Applications

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.669839Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c4dbd02a-bb47-4d4e-86b9-0ec041fd240d · outbound

This paper cites Porosity prediction: Supervised- learning of thermal history for direct laser deposition.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Porosity prediction: Supervised- learning of thermal history for direct laser deposition

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.660711Z

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Observation 15a489fa-fae0-4d0f-8fc0-ee297da2e6a9 · outbound

This paper cites Defect classification of laser metal deposition using logistic regression and artificial neural networks for pattern recognition.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Defect classification of laser metal deposition using logistic regression and artificial neural networks for pattern recognition

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.650544Z

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Observation d6589cb1-3965-451c-bb05-b257475a6e24 · outbound

This paper cites Physics- guided long short-term memory networks for emission prediction in laser powder bed fusion.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Physics- guided long short-term memory networks for emission prediction in laser powder bed fusion

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.640402Z

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Observation 6db2436a-55a1-4cad-8a36-d75d6c564d70 · outbound

This paper cites A hybrid deep learning model of process-build interactions in additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing A hybrid deep learning model of process-build interactions in additive manufacturing

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.630909Z

Source-reported events for the cited work

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Observation eb37e6df-df1f-444f-9566-d8028f3c0c10 · outbound

This paper cites Machine learning in additive manufacturing: State-of-the-art and perspectives.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Machine learning in additive manufacturing: State-of-the-art and perspectives

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.622600Z

Source-reported events for the cited work

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Observation 92858040-9683-4bfc-a3a1-42566357206e · outbound

This paper cites Evaluation of design information disclosure through thermal feature extraction in metal based additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Evaluation of design information disclosure through thermal feature extraction in metal based additive manufacturing

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.614213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 23d5d9b9-5827-461e-a2f2-1a437cbf8d6d · outbound

This paper cites Real-time FDM machine condition monitoring and diagnosis based on acoustic emission and hidden semi-Markov model.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Real-time FDM machine condition monitoring and diagnosis based on acoustic emission and hidden semi-Markov model

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.604851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2f01b36e-04e8-4caa-ac99-b10fad230bf7 · outbound

This paper cites Automated anomaly detection of laser-based additive manufacturing using melt pool sparse representation and unsupervised learning.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Automated anomaly detection of laser-based additive manufacturing using melt pool sparse representation and unsupervised learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.595550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 01a18388-6314-4e64-8b62-732222b747cb · outbound

This paper cites An LSTM-autoencoder based online side channel monitoring approach for cyber-physical attack detection in additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing An LSTM-autoencoder based online side channel monitoring approach for cyber-physical attack detection in additive manufacturing

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.586260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 407fcbd9-1cfe-46cd-81b6-45a80214d274 · outbound

This paper cites A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:14.443310Z

Source-reported events for the cited work

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Observation 435480a6-5700-4ef5-9f60-9bfdaebc8656 · outbound

This paper cites Reconciling modern machine-learning practice and the classical bias–variance trade-off.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Reconciling modern machine-learning practice and the classical bias–variance trade-off

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.576665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3fb90e3c-aa66-4a73-9c18-88d64814fff3 · outbound

This paper cites Deep learning-based data registration of melt-pool-monitoring images for laser powder bed fusion additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Deep learning-based data registration of melt-pool-monitoring images for laser powder bed fusion additive manufacturing

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.566823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a0c9ca2b-6c8f-4d9f-8fcd-1253d01571a4 · outbound

This paper cites Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.556659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68cb1685-471e-4de9-bd84-c58c66db80ad · outbound

This paper cites Optimal placement of non-redundant sensors for structural health monitoring under model uncertainty and measurement noise.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Optimal placement of non-redundant sensors for structural health monitoring under model uncertainty and measurement noise

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.547002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 90ece541-cc27-4f29-810e-614bddb6d8a4 · outbound

This paper cites Classification of specimen density in laser powder bed fusion (L-PBF) using in-process structure-borne acoustic process emissions.

Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Classification of specimen density in laser powder bed fusion (L-PBF) using in-process structure-borne acoustic process emissions

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:14.535358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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