The mining of minerals and coal have been cyclic industries for over a century with global periods of boom and bust following each other. In the last decade, or so, the emergence of China and India’s economies and the related expansion of heavy industry produced unprecedented demand for iron ore, coal and copper. In this environment Australia, Brazil and other countries to a smaller extent undertook to expand their capacity to export product to service this growing demand.
To place this level of demand in context, by 2014 China was consuming 800 million tonnes of iron ore per year compared to, say, 87 million tonnes by the USA. To increase export capacity, as well as lifting capacity in existing production areas the expansion of capacity involved mining previously unworked regions and developing suitable infrastructure from pits through to ports.
During the last 5 years a number of factors have combined to change the dynamics within the industry. While the key factors and their drivers may be argued, or disputed, the end result has been significant downward pressure on product pricing. The price of iron ore has dropped from over $150 per tonne to less than $50 per tonne, copper from over $8000 per tonne to less than $4700 per tonne and metallurgical coal from around $300 per tonne to less than $100 per tonne. This has brought significant pressure on smaller and high cost operations forcing many from the market. Projects still at the feasibility stage with high costs and low margins have been dropped or deferred while some producers have pulled out all together.
During the 2000’s, with a strong focus on growth, modelling and analytics was used to ensure that new plant and facilities could achieve target throughput levels as quickly as possible. A strong emphasis was placed on developing supply chains capable of delivering what seemed like an ever increasing demand.
The infrastructure to support these developments included mines sites, processing plants, rail, export terminal and port operations as well as significant buffer stocks at various locations. The use of simulation modelling proved its worth with major projects being subjected to the critical review of modelling to ensure that their production targets were achievable. The key operators introduced sophisticated models into their supply chain planning activities to ensure that as high a level of synergy as possible was achieved between the supply chain components to deliver maximum possible throughput.
With significantly reduced product pricing, volume alone is no longer a sure route to profit. Producers that have survived the last few years have refocussed with a strong drive to reduce costs. Options considered have ranged from reducing redundant capacity by decommissioning equipment, changes in operating practices.
With the aim of minimising costs the alignment of the integrated supply capacity with production and known customer demand has become increasingly important. Models previously used to drive throughput are now being used to develop leaner more cost effective production schedules. Traditional production plans are now being tested for robustness using simulation models and refined to generate cost effective outcomes.
Work undertaken to assist with the setup of new facilities is being revisited to identify opportunities to streamline operations by decommissioning lowly utilised equipment, even at the expense of outright capacity. Operators are using modelling to review operating strategies, shift patterns, equipment selection and product mix to minimise operating costs. Where opportunities exist other operators are looking to reduce costs by driving production through existing facilities. They look to identify bottlenecks which can be removed with little capital outlay or process changes that can lead to system wide capacity increase and resultant lowering of cost per tonne.
Obtaining approval for even relatively small capital outlays for process improvement can be challenging in a capital constrained environment. Organisations not only want a solid return on any outlay they need to feel comfortable that the risk associated with obtaining returns is low. Simulation modelling is a recognised technology for the mitigation of risks associated with process changes. Model testing allows the impact of uncertainty in key assumption to be understood. Typically models are used to provide a profile of the likelihood of a given rate of return being achieved.
For people providing modelling solutions the initial downturn in the mining sectors provided a challenge in presenting that service to an industry that perceived simulation modelling primarily as a means of proving capacity. However, with an acceptance of an environment in which low commodity prices are an ongoing reality modelling is again coming to the fore as a means of identifying and proving process improvement and cost savings opportunities.