Control integration, business justification, and adoption barriers of digital twins in flotation: A conceptual framework

Abstract:

This paper explores the potential of digital twins for flotation control and their integration into existing control hierarchies. While most literature delves directly into technical details such as model architectures and data-driven techniques, this study takes a step back to evaluate broader implementation value. It examines how digital twins can enhance advanced process control (APC) performance, from soft-sensor outputs and optimisation through recommendations (decision support), to direct interventions (autonomous control), fault detection and mitigation, and maintenance workflows. A business case based on a steady-state model is presented, using mass pull control as a practical example. The economic evaluation employs simplified models to avoid unnecessary complications, and results suggest an average benefit of approximately USD 3 million per annum. Implementation costs are assessed by drawing parallels with APC systems, and a net present value (NPV) analysis shows breakeven is achievable even under conservative scenarios where only 10% of the projected benefit is realised. Six key challenges are identified - including limited sensor coverage, data quality, model complexity, and the human/twin interface - that must be addressed for successful adoption. Ultimately, this work aims to foster a grounded discussion between researchers and practitioners on the real-world value and practicality of implementing digital twins in flotation control.