Abstract
Discrete Event Simulation (DES) is one of the most effective tools for planning, designing and improving material flows in production. One of the main weaknesses of operating DES is the exertion needed and costs spent on collecting and handling the input data from different organisation’s data resources. To tackle the problem of the time consuming input data process for DES projects an Open Source (OS) tool, called Knowledge Extraction (KE) tool was developed. The tool reads data from several organisations’ resources; analyses it and outputs it in a format that is applicable to be used by a simulation tool, all conducted in one automated process. The primary, readable to simulation software, output format follows the Core Manufacturing Simulation Data (CMSD). This paper presents the KE tool and a test implementation, as a first step towards the validation of the tool in a real case study in the medical industry.
| Original language | English |
|---|---|
| Pages (from-to) | 596-608 |
| Number of pages | 13 |
| Journal | International Journal of Simulation Modelling |
| Volume | 14 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Automation
- Core manufacturing simulation data
- Discrete event simulation
- Input data management
- Open source
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