A Software Platform for Use Case Driven Human-Friendly Factory Interaction Using Domain-Specific Assets

Brandt, Felix; Brandt, Eric; Heik, David; Reichelt, Dirk; Ghofrani, Javad

doi:10.1007/978-3-030-63092-8_71

Cited by 1 publication

(1 citation statement)

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“…Among other things, CASO provides a standardized data acquisition layer that supports OPC UA as a communication protocol. Digital events are acquired via the OPC UA communication standard [28][29][30]. For the selection of required signal sources, the graphical user interface of UA Expert is used (1.2).…”

Section: Data Pipeline Of the Case Studymentioning

confidence: 99%

Systematic Approach for Investigating Temporal Variability in Production Systems to Improve Production Planning and Control

Telatko

Reichelt

2023

JMMP

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Including the inherent temporal variability in a production system in planning and control processes can ensure the fulfillment of the production schedule and increase key performance indicators. This benefits the sustainable and efficient use of the system. The current lack of consideration of this inherent temporal variability in production planning leads to optimistic estimates and calculations of planned values that cannot be met. To complete this information, the inherent temporal variability in a production system is investigated using a systematic approach. This approach detects, identifies, and quantifies inherent temporal variability and is applied to a data base created via an automated, event-driven procedure. The approach is tested in a smart factory laboratory. The results to date on improving production planning and control are promising as key performance indicators have been increased. There is still a need for action to ensure the fulfillment of the production schedule. Concluding, work on this topic has just begun, as can be seen from the discussion section. More data need to be collected and aggregated for future research. This publication is intended to motivate researchers to address this issue and better manage the existing uncertainty in production through the use of data.

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Section: Data Pipeline Of the Case Studymentioning

confidence: 99%