Framework for the usage of data from real-time indoor localization systems to derive inputs for manufacturing simulation
| Autor: | Michael Henke, Carina Mieth, Anne Meyer |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computer science 02 engineering and technology 010501 environmental sciences Manufacturing systems 01 natural sciences Industrial engineering Single source of truth Poor quality 020901 industrial engineering & automation Work (electrical) Data quality General Earth and Planetary Sciences Production (economics) Discrete event simulation 0105 earth and related environmental sciences General Environmental Science |
| Zdroj: | Procedia CIRP. 81:868-873 |
| ISSN: | 2212-8271 |
| Popis: | Discrete event simulation is becoming increasingly important in the planning and operation of complex manufacturing systems. A major problem with today’s approach to manufacturing simulation studies is the collection and processing of data from heterogeneous sources, because the data is often of poor quality and does not contain all the necessary information for a simulation. This work introduces a framework that uses a real-time indoor localization systems (RTILS) as a central main data harmonizer, that is designed to feed production data into a manufacturing simulation from a single source of truth. It is shown, based on different data quality dimensions, how this contributes to a better overall data quality in manufacturing simulation. Furthermore, a detailed overview on which simulation inputs can be derived from the RTILS data is given. |
| Databáze: | OpenAIRE |
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