Digital twinning in the metallurgical industry: the role of behavioural modelling and simulation, J.D.T. Steyl and G.B. Grobbelaar

Two examples are presented to show how first-principles – physical-dynamic, here termed behavioural modelling, is used to build digital twins of unit processes or plant sections. A digital twin equips the metallurgist, engineer, or manager with a powerful tool to conduct model-based design, solve process problems and improve operations. It is particularly relevant in the metallurgical industry where plant behaviour is highly integrated, rates respond to particle dynamics in complicated ways and mineral flows across flowsheet boundaries are variable. The two examples used to illustrate the behavioural modelling methodology are 1) a flotation column unit block and 2) a multi-compartment pressure oxidation (POX) autoclave. It simultaneously accounts for the causality of material and heat flow, takes care of mineral particle dynamics, physical and chemical reaction rates, the plant control system behaviour and operating heuristics. The basic modelling building blocks are briefly reviewed to show how the behavioural modelling attributes constrain the mass and heat flow dynamics to physically realistic values. This is the key aspect that allows project value to be created with minimal input data. Behavioural modelling is especially valuable where the process dynamics are poorly understood or controlled, where data-driven models fail to cope with complex and highly integrated plant behaviour, where quality data is lacking or limited funds are available to generate the data required to fill all the knowledge gaps. The paper uses the flotation column example to show how behavioural modelling and simulation can be used to optimise plant performance, while the multi-compartment POX autoclave model shows how it can be used to diagnose process problems. It also provides a solid basis to add a data-driven component – in other words, it makes a strong case for a hybrid first-principle– data-driven approach to solve process problems, especially where microscopic-level understanding is poor. Keywords: Digital twin, behavioural modelling, simulation, flotation column, pressure oxidation