Industrial Software

Waste and Loss Reduction: Digital Mining’s Simplest ROI Story

“You don’t know what you don’t know.” A simple, obvious statement often used as an excuse by someone who has made the wrong decision. A defendable, reliable and justified excuse, but it is still an EXCUSE. Much of the waste and inefficiencies within the mining industry happens by accident or unexpected circumstances. Equipment malfunction, process failures and misunderstandings all can result in expensive waste. How would this excuse stack up to a mining executive who is under pressure to rein in costs?

It all comes down to removing that excuse. And Digital Mining holds the most effective key to removing this excuse: Validated, reliable and timely DATA. Adopting a data-driven improvement culture will ensure that you can and will know more about what is causing your waste. So time can be invested in working out ways of solving those problems. Today, that time is usually spent fixing and recovering from something that occurred because “You don’t know what you don’t know”.

Data is king in virtually every industry today. In mining, data is worth more because assets are worth more. Usually by one and sometimes two orders of magnitude. So it’s much easier to justify from an ROI perspective. Where manufacturing lines talk about thousands of dollars per minute of production, a copper concentrator is easily twenty to a hundred times that. So an investment of US$5M could only take a few days or maybe weeks of increased production to pay back the investment. This increased production comes from reducing waste and losses.

Beginning the journey is quite simple. Accurate, raw data about production throughput across various parts of the plant is a good start. An accurate history of this can tell you about what your plant is capable of doing and what it is currently averaging in terms of production. For most operations that information alone will provide insight into opportunities for improvement. Beyond the obvious “big hitters”, there will be opportunities that are much less obvious. And those will require better data and the ability to turn that data into information.

That information comes in two forms: First is in the form of historical, contextualized data and used to drive continuous improvement initiatives. Second is in the form of near real-time performance indicators for operators to respond to process losses. Together, they cover both the strategic and tactical approaches to improving productivity by reducing waste and loss. Medium to long term improvement projects can be qualified, justified and prioritized. Short term problem containment and quick countermeasures will ensure stability and sustainability. Together, both forms of information combine to become knowledge. This knowledge will allow the operations to improve performance and also to sustain this improvement.

Preparing for the journey is less simple. This requires commitment at the top and an overall desire by the staff to improve in performance and in capability. There will be change in the way that people do their jobs. There will also be changes in the way meetings and reporting are done. This is inevitable when a culture changes. There will be friction at first but the triumphs that quickly come will positively energize the teams. Without change management, there will be less desire to change by the staff. Without commitment good data will go to waste and the Digital Mine is lost.

Once the commitment is made, the operational leader should gain some insight into what this journey may look like depending on their own special set of circumstances. Every mining operation is different and has to be considered individually. Experienced software solutions vendors know to offer a high-level survey of the operations gratis. This will give the leader a chance to evaluate their options and to choose the best path forward. With the help of a good technology vendor, they can plot their own journey towards higher availability, utilization, yields and overall performance in the shortest time possible.

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