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Creation date: 2024-11-12
Creation time: 02-41-18
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incollection
2023_rueppel_crd-b2.ii
Model-Based Controlling Approaches for Manufacturing Processes
2023
2
8
221-246
The main objectives in production technology are quality assurance, cost reduction, and guaranteed process safety and stability. Digital shadows enable a more comprehensive understanding and monitoring of processes on shop floor level. Thus, process information becomes available between decision levels, and the aforementioned criteria regarding quality, cost, or safety can be included in control decisions for production processes. The contextual data for digital shadows typically arises from heterogeneous sources. At shop floor level, the proximity to the process requires usage of available data as well as domain knowledge. Data sources need to be selected, synchronized, and processed. Especially high-frequency data requires algorithms for intelligent distribution and efficient filtering of the main information using real-time devices and in-network computing. Real-time data is enriched by simulations, metadata from product planning, and information across the whole process chain. Well-established analytical and empirical models serve as the base for new hybrid, gray box approaches. These models are then applied to optimize production process control by maximizing the productivity under given quality and safety constraints. To store and reuse the developed models, ontologies are developed and a data lake infrastructure is utilized and constantly enlarged laying the basis for a World Wide Lab (WWL). Finally, closing the control loop requires efficient quality assessment, immediately after the process and directly on the machine. This chapter addresses works in a connected job shop to acquire data, identify and optimize models, and automate systems and their deployment in the Internet of Production (IoP).
Process control; Model-based control; Data aggregation; Model identification; Model optimization
internet-of-production
https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-rueppel-iop-b2.i.pdf
Springer
Interdisciplinary Excellence Accelerator Series
Internet of Production: Fundamentals, Applications and Proceedings
978-3-031-44496-8
10.1007/978-3-031-44497-5_7
1
Adrian KarlRüppel
MuzafferAy
BenediktBiernat
IkeKunze
MarkusLandwehr
SamuelMann
JanPennekamp
PascalRabe
Mark P.Sanders
DominikScheurenberg
SvenSchiller
TiandongXi
DirkAbel
ThomasBergs
ChristianBrecher
UweReisgen
Robert H.Schmitt
KlausWehrle