Mineral process plants collect a huge amount of data, across hundreds of control parameters and quality measurements, due to the large volumes of production materials these plants typically process. Pre-industry 4.0 plants are constrained by their inability to capitalize upon this valuable resource, often resulting in poor operational performance and sub-optimal quality.
A growing recognition of the benefits of combining valuable plant data with artificial intelligence (AI) for the purpose of improving productivity is driving an increase in the adoption rate. However, there are complexities that need to be considered when reviewing the wealth of data available in mineral processing plants. We explore how mineral processing plants compare with manufacturing plants when deploying AI including:
- Tolerance levels
- Volume and scale
Read the full paper here.