Aprovechar el concepto de mina inteligente para mejorar la rentabilidad y la sostenibilidad
Leveraging the intelligent mine concept for improved profitability, sustainability
The case for digitalisation is clear, according to AspenTech’s Jeannette McGill*, with digitalisation being critical for the metals and mining industry to achieve sustainability and operational excellence in the years ahead.
This is why the more forward-looking decision makers in the mining industry are embedding digital capabilities in their operations so they remain agile, competitive and profitable over the long term, while realising immediate and measurable benefits, she says. Technology providers have responded to the industry’s needs with solutions designed for the mining sector that directly address the dual imperatives of greater business efficiency and enhanced sustainability.
The intelligent mine
In their digitalisation initiatives, today’s operators also know that managing data more efficiently and effectively will be crucial in helping them to meet the challenges they face. Multiple difficulties remain in the way that organisations across the sector manage their data.
Senior mining company executives frequently make tough decisions but, in doing so, they must aggregate isolated pockets of data to generate insights that are relevant and actionable. For data to be available is no longer sufficient. The top priority for effective decision making is for appropriate management of diverse and disparate data sets in a range of locations.
The key is to integrate data and conduct high-level analysis with an understanding of the domain work requirements. Mining companies achieving this will establish what has become known as the intelligent mine. This is a concept that focuses on centralising information from multiple locations and business processes to reveal useful insights. It supports senior level decision making with designed-for-purpose analytical platforms.
Data held in 50 separate systems will not in itself drive operational efficiencies or support sustainable operations. By addressing several issues simultaneously, an organisation is more likely to move towards the intelligent mine.
First, though, businesses must implement automated data gathering systems to capture relevant data from various parts of the mining process and facilities. Second, organisations must have tools that detect bad data because only good data enables good decisions. They must ensure all changes are consistent, correct and improve data processing. Third, the business should assist the mine personnel by providing the capability to integrate data with built-in relevant analytics, so they process and act on insights in a meaningful time frame.
The predictive dimension
To create an intelligent mine, good data is important but only one part of the equation. Organisations must also analyse data in different ways within a context of the problem to be solved with appropriate predictive outcomes.
Companies need to predict the degradation of equipment that, if unattended, will lead to equipment breakdowns and unplanned maintenance, thereby adversely affecting both operational efficiency, reliability, sustainability and safety. Mining is equipment- and infrastructure-intensive with expensive machinery. It demands operational continuity for profitability and sustainability.
Bringing in prescriptive maintenance
Traditional preventive maintenance methods generally fail on the benchmark of equipment availability and performance. Earlier preventive maintenance efforts were unable to deliver sufficient time-to-failure warnings to deliver a significant impact on profitability.
That is where modern prescriptive maintenance plays a vital role. The technology monitors data from sensors on and around the machine to develop intense multi-dimensional and temporal patterns of normal operation, abnormal operation and explicit degradation patterns that precede breakdown. This provides early warnings, using artificial intelligence (AI)/machine learning digital technology to spot patterns that humans will never pick up.
Also surpassing human capability, the technology can assess the health of numerous machines every few minutes. It also delivers early warnings to maintenance teams, often with prescriptive advice on resolution. Facing tough challenges and spread thinly over large sites, workers benefit from warnings. Much of the intense repetitive analytics and engineering help them prioritise what matters most. Maintenance teams with such prescriptive maintenance tools ensure an intelligent mine makes significant progress in eliminating unplanned breakdowns.
Finding a solution
An asset performance management (APM) approach – with integrated prescriptive maintenance capability – ensures mines improve reliability, availability and uptime, simultaneously reducing the considerable cost of redundant equipment.
Operations teams often work on the assumption of lower availability by, for example, installing three machines when they only need two, or purchasing 10 trucks to ensure they always have eight up and running. These practices are now deemed too wasteful and have become unsustainable.
By embracing the most effective technology, mines can achieve benchmark reliability without the need for more people, equipment, or expenditure. Companies can operate at the required production levels and either mothball or switch off redundant equipment. Being able to do this with full confidence it will actually enhance overall outcomes, makes a significant contribution to the bottom line. It reduces emissions and increases sustainability.
Yet to develop an efficient digitalisation strategy, certain components must be in place. All too often, mines try to invest minimally in digital solutions to save money. Without domain-centric AI/machine learning analytics, this limits the reach and value technology can deliver. Successful digital strategies deploy solutions that draw on data from sensors and other sources. Enterprise resource planning systems, manufacturing execution systems, laboratory information management systems and advanced process control systems are all part of the mix, as well as general mine planning and design systems. Machine learning and other data science techniques require timely delivery of available data, so historian technology plays a vital role.
Across the industry, a growing numbers of mines are pursuing an APM approach. Australia-based gold miner, Evolution Mining, for example, has deployed Aspen Mtell software at the company’s Mungari Gold Operations, in Western Australia, to help reduce unplanned downtime and provide information to support productivity improvements.
Greg Walker, previously Evolution Mining Mungari General Manager, said: “Evolution’s Data Enabled Business Improvement program has achieved excellent results in recent years. With this new technology, Mungari Gold Operations can achieve further productivity improvements via increased asset availability.”
Looking to the future
Today’s mining industry is now sufficiently mature that it should fully embrace digital optimisation technologies. Operators that fail to adapt and build a strategy to utilise such technology are destined to struggle against competitors that do. Prescriptive maintenance delivers quick results by improving the use of existing capital assets and eliminating the surprise of unplanned downtime, which directly affects productivity, safety and sustainability.
The industry should understand how scalable prescriptive maintenance solutions add value to assets. This works as well with a single asset, conveyer system, a processing plant, a large mill, as it does with equipment across a worldwide enterprise. The truly intelligent mine empowers mining companies across a vast array of contemporary challenges. From reducing unplanned downtime and decreasing safety risks, to greater operational efficiency, sustainability and increased profitability, this approach will be essential for mining companies to surmount all their challenges in short and longer terms.
*Jeannette McGill is VP and GM of Metals & Mining at AspenTech
Fuente: International Mining