Speaker
Description
The forging industry is increasingly turning to data-driven process optimization and artificial intelligence systems to enhance efficiency, product quality and sustainability. These technologies rely heavily on robust, high-quality databases that provide consistent and reliable data for analysis and decision making. However, in many forging shopfloors, data is often dispersed across multiple separate IT systems, creating significant challenges for integration and utilization of the data. Downsampling methods and expert systems are used to address these challenges and enable the consolidation of scattered data into valuable insights. Downsampling reduces the size of the data sets while preserving the critical information in the data, thus minimising the amount of storage and computing power required and allowing for faster visualisation and analysis of the data. Expert systems complement these efforts by incorporating domain knowledge into algorithms and translating raw data into key metrics that can be interpreted by human process experts. This paper not only describes how these techniques have been used to build a quality data set that contains all the relevant technical data for the forge shop, but also how this dataset was used to build a data visualization dashboard that delivers immediate business value.
| Speaker Company/University | voestalpine Böhler Edelstahl GmbH & Co KG |
|---|