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A Real-Time Digital Twin to Inform In-Process Decision Support in Additive Manufacturing

https://doi.org/10.2139/ssrn.4680266
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inferredcites →https://doi.org/10.1002/9781119798798.ch2openalex-extracted
Decision Support Methodology for Scheduling Orders in Additive Manufacturing
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Economics of additive manufacturing for end-usable metal parts
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A decision support system for the validation of metal powder bed-based additive manufacturing applications
inferredcites →https://doi.org/10.1007/s10845-019-01512-wopenalex-extracted
A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives
inferredcites →https://doi.org/10.1016/j.cad.2019.02.004openalex-extracted
Status, comparison, and future of the representations of additive manufacturing data
inferredcites →https://doi.org/10.1016/j.cirp.2018.04.055openalex-extracted
Digital twin driven prognostics and health management for complex equipment
inferredcites →https://doi.org/10.1016/j.cirpj.2017.09.007openalex-extracted
On thermal modeling of Additive Manufacturing processes
inferredcites →https://doi.org/10.1016/j.cirpj.2020.02.002openalex-extracted
Characterising the Digital Twin: A systematic literature review
inferredcites →https://doi.org/10.1016/j.ifacol.2018.08.474openalex-extracted
Digital Twin in manufacturing: A categorical literature review and classification
inferredcites →https://doi.org/10.1016/j.jmsy.2020.05.010openalex-extracted
Digital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems
inferredcites →https://doi.org/10.1016/j.jmsy.2020.05.012openalex-extracted
How to model and implement connections between physical and virtual models for digital twin application
inferredcites →https://doi.org/10.1016/j.jmsy.2021.01.008openalex-extracted
Toward in-situ flaw detection in laser powder bed fusion additive manufacturing through layerwise imagery and machine learning
inferredcites →https://doi.org/10.1016/j.jmsy.2021.02.010openalex-extracted
Digital Twin-driven online anomaly detection for an automation system based on edge intelligence
inferredcites →https://doi.org/10.1016/j.jmsy.2021.02.017openalex-extracted
Worker assistance systems in manufacturing: A review of the state of the art and future directions
inferredcites →https://doi.org/10.1016/j.jmsy.2021.05.011openalex-extracted
Digital twins-based smart manufacturing system design in Industry 4.0: A review
inferredcites →https://doi.org/10.1016/j.jmsy.2023.02.008openalex-extracted
Digital twin-enabled automated anomaly detection and bottleneck identification in complex manufacturing systems using a multi-agent approach
inferredcites →https://doi.org/10.1016/j.matpr.2021.12.217openalex-extracted
A state-of-the-art review on implementation of digital twin in additive manufacturing to monitor and control parts quality
inferredcites →https://doi.org/10.1016/j.mfglet.2022.07.075openalex-extracted
Data organization in laser-based powder bed fusion for metals
inferredcites →https://doi.org/10.1016/j.procir.2021.05.098openalex-extracted
Approach of simulation data management for the application of the digital simulation twin
inferredcites →https://doi.org/10.1016/j.procir.2021.11.278openalex-extracted
A decision support method for knowledge-based Additive Manufacturing process selection
inferredcites →https://doi.org/10.1016/j.procs.2020.09.314openalex-extracted
Machine Learning-enabled feedback loops for metal powder bed fusion additive manufacturing
inferredcites →https://doi.org/10.1016/j.procs.2022.03.098openalex-extracted
Rule-based Clinical Decision Support System using the OpenEHR Standard
inferredcites →https://doi.org/10.1016/j.promfg.2017.04.043openalex-extracted
The Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems
inferredcites →https://doi.org/10.1016/j.promfg.2018.01.019openalex-extracted
Lifecycle design and management of additive manufacturing technologies
inferredcites →https://doi.org/10.1016/j.promfg.2020.10.153openalex-extracted
A microservice architecture for predictive analytics in manufacturing
inferredcites →https://doi.org/10.1016/j.promfg.2021.07.039openalex-extracted
Application of the STRAY statistical learning algorithm for the evaluation of in-situ process monitoring data during L-PBF additive manufacturing.
inferredcites →https://doi.org/10.1016/j.rcim.2017.12.005openalex-extracted
Integrated product-process design: Material and manufacturing process selection for additive manufacturing using multi-criteria decision making
inferredcites →https://doi.org/10.1038/d41586-019-02849-1openalex-extracted
Make more digital twins
inferredcites →https://doi.org/10.1049/iet-cim.2020.0009openalex-extracted
Integration of digital twin and deep learning in cyber‐physical systems: towards smart manufacturing
inferredcites →https://doi.org/10.1080/10618600.2020.1807997openalex-extracted
Anomaly Detection in High-Dimensional Data
inferredcites →https://doi.org/10.1088/1361-6501/aa5c4fopenalex-extracted
Process defects and in situ monitoring methods in metal powder bed fusion: a review
inferredcites →https://doi.org/10.1109/bigdata.2018.8622377openalex-extracted
A Framework for Five Big V’s of Big Data and Organizational Culture in Firms
inferredcites →https://doi.org/10.1115/detc2015-47802openalex-extracted
Towards an Integrated Data Schema Design for Additive Manufacturing: Conceptual Modeling
inferredcites →https://doi.org/10.1115/detc2019-98415openalex-extracted
A Review of Machine Learning Applications in Additive Manufacturing
inferredcites →https://doi.org/10.1115/msec2015-9439openalex-extracted
Fundamental Requirements for Data Representations in Laser-Based Powder Bed Fusion
inferredcites →https://doi.org/10.1186/s40192-016-0050-7openalex-extracted
Overview of Additive Manufacturing Informatics: “A Digital Thread”
inferredcites →https://doi.org/10.1520/ssms20160003openalex-extracted
Toward a Digital Thread and Data Package for Metals-Additive Manufacturing
inferredcites →https://doi.org/10.3390/app10238350openalex-extracted
Digital Twins for Additive Manufacturing: A State-of-the-Art Review
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