[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Morariu et al., 2019 - Google Patents

A distributed approach for machine learning in large scale manufacturing systems

Morariu et al., 2019

View PDF
Document ID
2355801520442399265
Author
Morariu C
Răileanu S
Borangiu T
Anton F
Publication year
Publication venue
Service Orientation in Holonic and Multi-Agent Manufacturing: Proceedings of SOHOMA 2018

External Links

Snippet

Large scale manufacturing systems are capable to execute manufacturing operations across multiple product batches by coordinating many shop floor actors. Monitoring and processing in real time the information flow from these systems becomes an essential part in optimizing …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46—Multiprogramming arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/005—Probabilistic networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B21/00—Systems involving sampling of the variable controlled
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems

Similar Documents

Publication Publication Date Title
Morariu et al. Machine learning for predictive scheduling and resource allocation in large scale manufacturing systems
Fei et al. CPS data streams analytics based on machine learning for Cloud and Fog Computing: A survey
Wang et al. Big data driven cycle time parallel prediction for production planning in wafer manufacturing
Girish et al. Anomaly detection in cloud environment using artificial intelligence techniques
Liu et al. An adversarial bidirectional serial–parallel LSTM-based QTD framework for product quality prediction
Siraskar et al. Reinforcement learning for predictive maintenance: A systematic technical review
Kaymakci et al. A holistic framework for AI systems in industrial applications
Luan et al. Out-of-distribution detection for deep neural networks with isolation forest and local outlier factor
Burmester et al. Big data and data analytics in aviation
Morariu et al. Manufacturing systems at scale with big data streaming and online machine learning
Cohen et al. Shapley-based explainable ai for clustering applications in fault diagnosis and prognosis
Shubyn et al. Federated learning for anomaly detection in industrial iot-enabled production environment supported by autonomous guided vehicles
Morariu et al. A distributed approach for machine learning in large scale manufacturing systems
Chen Big data analytics for semiconductor manufacturing
Ansari et al. AI-enhanced maintenance for building resilience and viability in supply chains
Lara-Benítez et al. Data streams classification using deep learning under different speeds and drifts
Melgar-García et al. Nearest neighbors-based forecasting for electricity demand time series in streaming
Lara-Benítez et al. On the performance of deep learning models for time series classification in streaming
US20230259807A1 (en) Providing online expert-in-the-loop training of machine learning models
Reimer et al. Identifying cause-and-effect relationships of manufacturing errors using sequence-to-sequence learning
Cupek et al. Data preprocessing, aggregation and clustering for agile manufacturing based on automated guided vehicles
Sarkar et al. Gsel: A genetic stacking-based ensemble learning approach for incident classification
Farooq et al. Machine learning method for spinning cyber-physical production system subject to condition monitoring
Chen et al. Edge computing-based proactive control method for industrial product manufacturing quality prediction
Maurya et al. Fft-asvr: an adaptive approach for accurate prediction of IoT data streams