Operators in the mineral processing sector have started utilising Artificial Intelligence (AI), not to only resolve their short-term challenges, but also enhance operational resilience as a longterm competitive advantage, a report by McKinsey & Company, a global management consultancy services company has stated. The firm stated this in a report titled: “How artificial intelligence can improve resilience in mineral processing during uncertain times,” obtained at the weekend. McKinsey & Company revealed that even before Covid-19, some mineral processing companies were already taking steps to build their capabilities to cope with fluctuations inherent in commodities markets. “Several pioneering operators are starting to harness AI to not only resolve the short-term challenges but also enhance operational resilience as a long-term competitive advantage,” it added. It pointed out that in recent years, frequent changes in market prices have buffeted fertilizer companies, requiring new oreprocessing strategies in order to maximise long-term profitability. This integrated player had already started building AI tools and agile-operations capabilities in its processing, stated while citing an example with a company. It explained that for some companies, the pandemic offered a chance to test new skills. “Agile teams that were focused on reducing bottlenecks or optimising production pivoted to support the COVID-19 response. In one instance, a cross-functional agile team focused on how it could dramatically reduce the exposure risk for its haul-truck operators.
According to McKinsey & Company, as companies work to protect their workforce and maintain profitability during and after the Covid-19 crisis, they need to switch from using empirical models to AI in day-to-day management and operations decision making. In addition, they need to move from relatively rigid production planning using long-term budgets to short two-week-horizon planning and increased agility across the value chain; shift from single-recipe, plug-and-play tools to multiple value-driven, built for-purpose methods tailored to specific requirements; and turn from rigid workforce planning to more agile models, with a multidimensional team focusing on the highest-priority areas. It explained: “Processing companies that are just beginning digital transformations have an even stronger incentive to move quickly to build their agility and AI muscle because doing so is essential to managing the crisis. “They can begin by setting up a team with new skill sets required for implementation. This team would include data scientists to build the machinelearning tool, data engineers to structure and clean the data, and an agile coach to accelerate agile deployment.