Abstract
The full digitization of industry promises significant efficiency gains. This development has started to have an
impact on the operation in steel plants, when decisions are made based on traceable data.
This paper presents an approach to discover patterns in big data sets and applying methods of artificial intelligence (AI) for interpretation. The paper will present the use of AI to identify the main refractory wear mechanism in the hot
spots and the use of AI to predict the refractory behaviour.
Further, we applied this intelligent system to analyze and compare different maintenance philosophies.
As example of the impact on daily operations in steel plants, we present the Daily Report, which provides all necessary key information when a refractory related decision is to be made.
The paper also examines and discusses the operational
impact and future applications.
impact on the operation in steel plants, when decisions are made based on traceable data.
This paper presents an approach to discover patterns in big data sets and applying methods of artificial intelligence (AI) for interpretation. The paper will present the use of AI to identify the main refractory wear mechanism in the hot
spots and the use of AI to predict the refractory behaviour.
Further, we applied this intelligent system to analyze and compare different maintenance philosophies.
As example of the impact on daily operations in steel plants, we present the Daily Report, which provides all necessary key information when a refractory related decision is to be made.
The paper also examines and discusses the operational
impact and future applications.
| Originalsprache | englisch |
|---|---|
| Seiten (von - bis) | 12-20 |
| Fachzeitschrift | Bulletin: the Journal of Refractory Innovations |
| Jahrgang | 2017 |
| Ausgabenummer | 1 |
| Publikationsstatus | Veröffentlicht - 2017 |