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10 results for “Smart Factory”
An IoT-Enriched Event Log for Process Mining in Smart Factories
<p><strong>DEPRECATED - current version: </strong><a href="https://figshare.com/articles/dataset/Dataset_An_IoT-Enriched_Event_Log_for_Process_Mining_in_Smart_Factories/20130794">https://figshare.com/articles/dataset/Dataset_An_IoT-Enriched_Event_Log_for_Process_Mining_in_Smart_Factories/20130794</a></p> <p> </p> <p>Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various domains, including Business Process Management (BPM) research. One main research area in BPM is process mining, which can be used to analyze event logs, e.g., for checking the conformance of running processes. However, there are only a few IoT-based event logs available for research purposes. Some of them are artificially generated, and the problem occurs that they do not always completely reflect the actual physical properties of smart environments. In this paper, we present an IoT-enriched XES event log that is generated by a physical smart factory. For this purpose, we created the DataStream XES extension for representing IoT-data in event logs. Finally, we present some preliminary analysis and properties of the log.</p>
Data set from Fischertechnik Smart Factory Model at University of St.Gallen
<p>This is the data set of IoT data from the Fischertechnik Smart Factory Model deployed at the Institute of Computer Science at the University of St.Gallen. It is used as basis for the interactive identification of process activity executions from the IoT data. The corresponding publication can be found here:</p> <p>Seiger, R., Franceschetti, M., & Weber, B. (2023). An Interactive Method for Detection of Process Activity Executions from IoT Data. <em>Future Internet</em>, <em>15</em>(2), 77.<br> <a href="https://doi.org/10.3390/fi15020077">https://doi.org/10.3390/fi15020077</a></p> <p>The data set contains:</p> <ul> <li><strong>cps_log.txt:</strong> A file of all sensor and actuator readings (in JSON format) from the smart factory during the execution of 3 instances of the storage process and 3 instances of the production process. For visualization, it can be fed line-by-line into an <a href="https://www.influxdata.com/">Influx</a> database and <a href="https://grafana.com/">Grafana</a> can then be used to create visualizations of the data.</li> <li><strong>wfms_log.txt:</strong> A file containing the corresponding event log (in JSON format) recorded and extracted from the <a href="https://camunda.com/">Camunda Platform</a> workflow management system during the execution of the process instances. For visualization, it can be fed line-by-line into an <a href="https://www.influxdata.com/">Influx</a> database and <a href="https://grafana.com/">Grafana</a> can then be used to create visualizations of the data.</li> <li><strong>storage_process.bpmn:</strong> Executable BPMN 2.0 model of the storage process executed in the smart factory model.</li> <li><strong>production_process.bpmn:</strong> Executable BPMN 2.0 model of the storage process executed in the smart factory model.</li> </ul> <p>More details on the systems architecture used to execute the processes and record the data from the smart factory can be found in the follow publication:</p> <p>Ronny Seiger, Lukas Malburg, Barbara Weber, Ralph Bergmann,<br> Integrating process management and event processing in smart factories: A systems architecture and use cases,<br> Journal of Manufacturing Systems, Volume 63, 2022, Pages 575-592, ISSN 0278-6125,<br> <a href="https://doi.org/10.1016/j.jmsy.2022.05.012">https://doi.org/10.1016/j.jmsy.2022.05.012</a></p>
PDF exports of pages from the Smart Data Factory web site
<p>The attached zip file contains (in all three languages of the web site, namely Italian, German, and English) the following PDF exports:</p> <ol> <li>Smart Data Factory - Main page.pdf: the main page of the Smart Data Factory web site containing general information about the Smart Data Factory as well as links to offers, past projects, and the research groups of the Faculty of Computer Science of the Free University of Bozen-Bolzano</li> <li>Smart Data Factory - Offers.pdf: an example of a list of offers.</li> <li>Smart Data Factory - Offer.pdf: an example of one offer.</li> <li>Smart Data Factory - Archive items.pdf: an example of a list of archive items (past projects).</li> <li>Smart Data Factory - Archive item.pdf: an example of an archive item.</li> <li>Smart Data Factory - Research group.pdf: an example of the presentation of a research group.</li> </ol>
Data set from Fischertechnik Smart Factory Model at University of St.Gallen (Custom Python Configuration)
<p>This is about 60 mins worth of data collected from Fischertechnik Industry 9.0V smart factory model available at the University of St.Gallen.</p> <p>In this data set, we used a custom Python-based software stack to control the smart factory via a business process system (Camunda Platform) that calls the functionality of the smart factory via web services implemented in Python flask. MQTT is used to collect the data.</p> <p>Each entry in the file (low-level_log_20230206-140808.txt) corresponds to one message (as JSON object) received on a specific topic via MQTT. Each line contains all the readings of all the sensors, actuators and additional data from <strong>one </strong>CPS component (i.e., production station) at <strong>one </strong>point in time.</p> <p>The data set contains the following files</p> <ul> <li>low-level_log_20230206-140808.txt: low-level IoT data from all the sensors and actuators <ul> <li>*.bpmn: executable BPMN 2.0 models of three different processes that have been executed several times via the Camunda Platform BPM system to control the smart factory</li> </ul> </li> <li>camunda_process-instance.json: event log generated by the BPM system regarding the process instance execution</li> <li>camunda_activity-instance.json: event log generated by the BPM system regarding the activity instance execution</li> </ul> <p>Check the following publications to learn more about our research using the model factory:</p> <p>Malburg, L., Seiger, R., Bergmann, R., & Weber, B. (2020). Using physical factory simulation models for business process management research. In <em>Business Process Management Workshops: BPM 2020 International Workshops, Seville, Spain, September 13–18, 2020, Revised Selected Papers 18</em> (pp. 95-107). Springer International Publishing.</p> <p>Seiger, R., Zerbato, F., Burattin, A., García-Bañuelos, L., & Weber, B. (2020, October). Towards iot-driven process event log generation for conformance checking in smart factories. In <em>2020 IEEE 24th International Enterprise Distributed Object Computing Workshop (EDOCW)</em> (pp. 20-26). IEEE.</p> <p>Seiger, R., Malburg, L., Weber, B., & Bergmann, R. (2022). Integrating process management and event processing in smart factories: A systems architecture and use cases. <em>Journal of Manufacturing Systems</em>, <em>63</em>, 575-592.</p>
Support data for conference paper "The Concept of Efficient Utilization of the Uplink Frequency Resource of a Smart Factory 5G Cluster by IIoT Devices"
<p>upport data for conference paper<br>Kovtun, and O. Kovtun, “The Concept of Efficient Utilization of the Uplink Frequency Resource of a Smart Factory 5G Cluster by IIoT Devices.” In Proc. 8th International Conference on Computational Linguistics and Intelligent Systems. Volume I: Machine Learning Workshop, CEUR-WS, vol. 3664, 2024; pp. 273-283.<br>This research is part of the project No. 2022/45/P/ST7/03450 co-funded by the National Science Centre and the European Union Framework Programme for Research and Innovation Horizon 2020 under the Marie Skłodowska-Curie grant agreement No. 945339.</p>
Synthetic log file recording the workflow of a smart factory.
<p>This file is a synthetic log file recording the workflow of a smart factory.</p>
Raw OPC-UA Dataset of a Working Industry 4.0 Smart Factory (H-DA AutFab)
<p>This OPC-UA dataset was recorded in the AutFab, the fully automated Industry 4.0 learning factory of the University of Applied Sciences Darmstadt (Description of the AutFab, refer to: 10.1016/j.promfg.2017.04.023). Recording Date was the 2019-03-13. Five successful assemblies would be done during recording. The Dataset consists of 17.464 columns and 11.455 rows. Each column correspond to an OPC-UA node. The pre-transformation was limited to transpose the logformat: time, opcua-nodeid, value to time, opcua-nodeid 1, ..., opcua-nodeid N and align all events by time. A short analysis was carried out, which shows that only 1022 columns change more than once. This dataset contains no anomalies or errors. Usage must be requested.</p>
Data set from Fischertechnik Smart Factory Model at University of St.Gallen (Standard Fischertechnik Configuration)
<p>This is about 90 mins worth of data collected via the MQTT interface of the Fischertechnik Industry 9.0V smart factory model available at the University of St.Gallen. Each entry in the file corresponds to one message (as JSON object) received on a specific topic via MQTT.</p> <p>The description of the MQTT interface can be found here: <a href="https://github.com/fischertechnik/txt_training_factory/blob/master/TxtSmartFactoryLib/doc/MqttInterface.md">https://github.com/fischertechnik/txt_training_factory/blob/master/TxtSmartFactoryLib/doc/MqttInterface.md</a></p> <p>Check the following publications to learn more about our research using the model factory:</p> <p>Malburg, L., Seiger, R., Bergmann, R., & Weber, B. (2020). Using physical factory simulation models for business process management research. In <em>Business Process Management Workshops: BPM 2020 International Workshops, Seville, Spain, September 13–18, 2020, Revised Selected Papers 18</em> (pp. 95-107). Springer International Publishing.</p> <p>Seiger, R., Zerbato, F., Burattin, A., García-Bañuelos, L., & Weber, B. (2020, October). Towards iot-driven process event log generation for conformance checking in smart factories. In <em>2020 IEEE 24th International Enterprise Distributed Object Computing Workshop (EDOCW)</em> (pp. 20-26). IEEE.</p> <p>Seiger, R., Malburg, L., Weber, B., & Bergmann, R. (2022). Integrating process management and event processing in smart factories: A systems architecture and use cases. <em>Journal of Manufacturing Systems</em>, <em>63</em>, 575-592.</p> <p> </p>
The CONTEXT Dataset containing Contextual Faults of a Smart Factory
<p>Here you download the CONTEXT Dataset containing Contextual Faults of a Smart Factory. Our work as part of the Proceedings of the International Conference on Industry 4.0 and Smart Manufacturing is now published in Procedia Computer Science (Elsevier). <strong>If you refer to or use this dataset, cite this publication:</strong></p> <p><strong>Kaupp, Lukas; Webert, Heiko; Nazemi, Kawa; Humm, Bernhard; Simons, Stephan (2021): CONTEXT: An Industry 4.0 Dataset of Contextual Faults in a Smart Factory. In: Procedia Computer Science 180, S. 492–501. DOI: 10.1016/j.procs.2021.01.265. </strong></p> <p>The dataset contains contextual faults recorded in the smart factory of the Darmstadt University of Applied Sciences. Each recording (CSV format) consists of an OPC-UA log file and log files of the corresponding machinery measured by our developed sensing units. Foldernames reflect experiment structure.</p> <p><date>-<run>_<count of build relays>_<g(ood/ok)/n(ot/failure)>_<experiment name></p> <p>You can find a detailed description of the experiments in our publication.</p> <p><strong>Description Update for a better data assessment.</strong></p> <p>OPC-UA Hierarchy - Factory Mapping:</p> <ul> <li>'Station10' - Management Station (send production instructions / receive production updates)[not physically involved in the production process]</li> <li>'Station 40 - Hochregallager' - High-Bay Storage Station</li> <li>'Station 50 - Roboter' - Robot Station</li> <li>'Station 60 - Presse' - Press Station</li> <li>'St20 SoftSPS' - Optical & Weight Inspection Station</li> <li>'Station30elPruefung' - Electrical Inspection Station</li> </ul>
SMART Therapist Training: A Hybrid Factorial-SMART Design
ClinicalTrials.gov study NCT07010770. IPD Sharing: NO. Countries: 1. Publications: 0.
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