Organizations continue to invest in core technologies to mitigate the challenges they face. These challenges include depleting grades of ore bodies impacting multifactor productivity, remoteness of new deposits with the lack of infrastructure and skills at the site, deeper underground mining which increases safety risks, etc. An ecosystem of suppliers and research institutions have been working at mitigating many of these challenges by applying innovation and technologies such as sensors, autonomous operations, drones and UAVs, mining simulators etc. Most of these technology innovations affect field level controls. There needs to be corresponding innovation in Production Process Operating Controls, Operation Management Level Controls and Planning, Recording and Analysis Level Control to reap the full benefi ts of the new technologies being leveraged. This is where IT-OT integration can play a key role.
This paper explores how IT-OT integration can help reap the full benefits of a close feedback loop (the analysis level control) through innovations, improve productivity and reduces costs.
Introduction
The Mining industry has had a fair share of innovations across field level and operations management controls in the last couple of decades. We’ve seen the emergence of autonomous haulage systems, airborne surveys, larger sized trucks (400 tons), online analyzers and collision detection systems during the boom in mining after World War II.
But innovation has begun to slow down in the industry. A study conducted by BAE research for Rio Tinto shows that there has been consistent decline of multifactor productivity. Deeper deposits have been the largest contributing factor. Stripping ratios (moving a higher volume of waste tons due to deeper open pits) and the rising level of impurities (lower grades) have led to greater milling/ processing costs.
There is an urgent need for innovating in operations management and analysis controls. Data from field level controls -- which by themselves are incremental innovations – can lead to steep change for a mining organization when they are integrated with IT.
Field level control innovations
Let us look at the range of innovations in an automated underground mine as depicted by the diagram below.
The diagram shows a number of sensors that can be put to play, which continuously will sense equipment operating conditions, trip cycle events and mine environments using a Wireless Mesh network. These sensors and systems can manage a wide array of mining requirements:
IT-OT integration perspective
These innovations offer incremental improvements to a mining organization. They also create a wealth of data. But they don’t necessarily translate into big ticket cost reductions by themselves. But, when the data is used at a Planning, Analysis and Control level to increase operations visibility, profitability improves by several magnitudes.
As depicted below, sensors provide the raw data which is historized into a data archive and translated into process transactions. As an example, a trip cycle from an ore draw point to a crusher generates an inventory record of mine production at the extraction level.
Integration benefits
At a shift control level, this implies the ability to record downtime events and trigger condition monitoring alerts. Aggregated records provide the drivers that influence mining output. These can include the ore volumes moved and tons mined. When combined with economic parameters such as commodity price, the system provides critical revenue side information to gauge profitability. Likewise, the cost side of the equation is derived from several variables such as the number of cycles for mobile fleets, effective operating time, fuel consumption and costs from Enterprise Resource Planning that captures fuel consumption, labor hours etc. The business gains come from the ability to rapidly assimilate data from OT into models that drive optimization for short term production planning, aid sensitivity analysis of parameters that influence economic output, causal analysis of variables that influence productioni or dynamic capacity balancing.
Such modelling technologies provide exponential benefits with the growth in data inputs. With effective IT-OT integration, access to data fuels innovation within the organization. For example, in a recent engagement, a production focused model with data integration from OT delivered an improvement of 1 rail rake per day. In real terms this translated into a 10% improvement in output.
Conclusion
The innovation journey for a mining organization is incomplete without a robust IT-OT integration program. Current technology makes it possible to integrate IT and OT and consolidate data in a single instance, enabling organizations to explore the data for improvement, efficiency and innovation.
Achieving a significantly high return is not difficult. This is more so because mining organizations are already making large investments in smart infrastructure. On the IT side, the investments now required are minimal, making this the ideal time to roll out IT-OT integration initiatives.
References
i e.g. the degree of influence of fill factor of particular model of trucks in a shift
ii e.g. to understand the bottleneck between fleet, ore passes, rail
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