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Production Planning Forecasting System Based on M5P Algorithms and Master Data in Manufacturing Processes

Song, Hasup ; Gi, Injong; Ryu, Jihyuk; Kwon, Yonghwan 1; Jeong, Jongpil
1 Karlsruher Institut für Technologie (KIT)

Abstract:

With the increasing adoption of smart factories in manufacturing sites, a large amount of raw data is being generated from manufacturers’ sensors and Internet of Things devices. In the manufacturing environment, the collection of reliable data has become an important issue. When utilizing the collected data or establishing production plans based on user-defined data, the actual performance may differ from the established plan. This is particularly so when there are modifications in the physical production line, such as manual processes, newly developed processes, or the addition of new equipment. Hence, the reliability of the current data cannot be ensured. The complex characteristics of manufacturers hinder the prediction of future data based on existing data. To minimize this reliability problem, the M5P algorithm, is used to predict dynamic data using baseline information that can be predicted. It combines linear regression and decision-tree-supervised machine learning algorithms. The algorithm recommends the means to reflect the predicted data in the production plan and provides results that can be compared with the existing baseline information. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000164058
Veröffentlicht am 09.11.2023
Originalveröffentlichung
DOI: 10.3390/app13137829
Scopus
Zitationen: 1
Web of Science
Zitationen: 1
Dimensions
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 2076-3417
KITopen-ID: 1000164058
Erschienen in Applied Sciences
Verlag MDPI
Band 13
Heft 13
Seiten Art.-Nr.: 7829
Vorab online veröffentlicht am 03.07.2023
Schlagwörter production planning; predictive modeling; master data; machine learning; M5P Algorithm
Nachgewiesen in Web of Science
Dimensions
Scopus
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