Most companies generate vast amounts of information; fewer can access and use it effectively, writes Wilhelm Swart, chief OT officer, 4Sight OT Cluster.

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In the ever-evolving mining industry, professionals must improve safety and quality, boost margins and efficiency, and reduce risk, waste, cost overruns and missed deadlines. Achieving this depends on adequate access to information. The industry is now transforming through artificial intelligence (AI), which requires feeding the right data into AI-driven solutions.

Importance of quality data in AI

The adage “garbage in, garbage out” holds particularly true in the realm of AI. AI algorithms are only as effective as the data they are trained on. For mining operations, inaccurate, incomplete or inconsistent data can lead to suboptimal outcomes, affecting everything from predictive maintenance to resource optimisation. Therefore, ensuring data accuracy, completeness and consistency is the first step towards harnessing AI’s full capabilities.

 

Data cleansing – foundation of reliable AI

Data cleansing is detecting and correcting (or removing) corrupt or inaccurate records from a dataset. It is a critical step in preparing data for AI applications. At 4Sight, we employ advanced data cleansing techniques to ensure that the data fed into AI models is of the highest quality.

This involves several steps:

  1. Data validation involves ensuring that the data collected from various sources is accurate and complete. This entails checking for missing values, outliers and inconsistencies.
  2. Data standardisation requires the conversion of data into a consistent format, making it easier to analyse and integrate with other datasets.
  3. Data enrichment involves enriching the dataset with additional information to provide more context and improve the accuracy of AI predictions.

By meticulously cleansing and preparing data, we lay a solid foundation for AI-driven solutions that can make a tangible impact on mining operations.

Feeding the right data into AI-driven solutions is the key to revolutionising mining operations.

Feeding the right data into AI-driven solutions is the key to revolutionising mining operations. All images supplied by 4Sight

Leveraging AI for operational excellence

With high-quality data in place, the next step is to leverage AI to drive operational excellence. Here are some key areas where AI can revolutionise mining operations:

  1. Predictive maintenance: AI algorithms can analyse historical and real-time data to predict equipment failures before they occur. This allows for proactive maintenance, reducing downtime and extending the lifespan of machinery.
  2. Resource optimisation: AI can optimise the allocation of resources, such as labour, equipment and materials, to maximise productivity and minimise costs. This is particularly valuable in large-scale mining operations where efficient resource management is critical.
  3. Safety and risk management: AI can identify potential safety hazards and risks by analysing sensor data and monitoring systems. This enables mining companies to take preventive measures, enhancing the safety of their operations.
  4. Environmental impact reduction: AI can help mining companies monitor and reduce their environmental impact by analysing emissions, waste management and energy consumption data. This is increasingly important as the industry faces growing pressure to adopt sustainable practices.

 

4sight’s role in AI-driven mining

At 4Sight, our deep understanding of the mining industry and our expertise in AI and data management enable us to provide tailored solutions that address the unique challenges of mining operations. We offer a comprehensive suite of services designed to help mining companies harness the power of AI, including:

  1. Data management solutions: Advanced data management solutions ensure that mining companies can access highquality data. We provide data collection, cleansing, integration and analysis tools, empowering companies to make datadriven decisions.
  2. AI implementation: We assist mining companies in implementing AI solutions – from developing custom AI models to integrating AI with existing systems, we provide end-to-end support to ensure seamless adoption and maximum impact.
  3. Consulting services: Our team of experts offers consulting services to help mining companies identify opportunities for AI adoption and develop strategies to achieve their operational goals.

Case study: enhancing efficiency with AI

A large mining company faced challenges with equipment downtime and maintenance costs. Leveraging our data management and AI expertise, 4Sight implemented a predictive maintenance solution that significantly improved their operations.

We started by cleansing and standardising our client’s historical maintenance data, ensuring it was ready for AI analysis. Next, we developed an AI model that analysed this data and real-time data from sensors to predict equipment failures. The model provided early warnings of potential issues, allowing the company to perform maintenance before breakdowns occurred.

The results were impressive:

  • Equipment downtime was reduced by 30%.
  • Maintenance costs were cut by 25%.
  • The overall efficiency of their operations improved.

This case study demonstrates the tangible benefits of feeding the right data into AI-driven solutions and the transformative impact it can have on mining operations.

The future of AI in mining

As the mining industry continues to evolve, AI’s role will become increasingly prominent. The ability to analyse vast amounts of data and derive actionable insights is a game-changer for mining companies seeking to enhance their operational efficiency and sustainability.

At 4Sight, we are committed to staying at the forefront of this transformation, continually developing innovative solutions that leverage the power of AI. Looking ahead, we see several exciting trends shaping the future of AI in mining:

  1. Autonomous operations: AI will enable fully autonomous mining operations, where machinery and equipment operate without human intervention. This will enhance safety, efficiency and productivity.
  2. Advanced robotics: AI-powered robots will play a critical role in mining operations, performing dangerous or difficult tasks for humans. These robots can navigate complex environments and make real-time decisions based on AI analysis.
  3. Real-time decision making: AI will allow mining companies to make real-time decisions based on data from various sources. This will enable more agile and responsive operations, which can quickly adapt to changing conditions and demands.
  4. Sustainable practices: AI will help mining companies adopt more sustainable practices by optimising resource usage, reducing waste and minimising environmental impact. This will be essential in meeting regulatory requirements and achieving long-term sustainability goals.

Feeding the right data into AI-driven solutions is the key to revolutionising mining operations. At 4Sight, we have the knowledge and expertise to ensure that mining companies have access to high-quality data and the tools they need to harness the power of AI. A focus on data cleansing, AI implementation and continuous innovation, will assist the mining industry achieve operational excellence and pave the way for a more efficient, sustainable future.

As we continue to push the boundaries of what is possible with AI, 4Sight invites mining companies to join them on this transformative journey. Together, we can unlock new levels of efficiency, productivity and sustainability, driving the future of mining.

About author:

Wilhelm Swart holds a Batchelor’s degree in Electronic Engineering from Stellenbosch University, among a vast array of academic qualifications earned throughout his career. He is currently the chief operational technology officer leading 4Sight OT Optimisation, a subsidiary of 4Sight Holdings, a JSElisted diversified holding company that invests in industry 4.0 technology businesses.

Swart started his career as an automation design engineer at Siemens South Africa, where he gained experience in Water and Waste Water (WWW) and Oil & Gas (O&G) Pipeline projects. The exposure to large project hunting and execution with Siemens in Germany, as systems engineer, led to Swart’s passion for industry project sales and execution throughout the total project life cycle. In 1996 he moved on to head up a start-up Automation Systems Integration business, Industrial Systems Integrators Pty Ltd as MD. Swart later fulfilled the MD and vice president role for seven years at Citect Pty Ltd (Africa), taking full P&L responsibility for all Sales, Marketing, Project Execution and installed base Services activities in the southern Africa operations. It was during this time that the company won and executed some of the largest Scada & PLC and Manufacturing Execution Systems (MES) solutions in Africa with various bluechip Industrial customers.

Thereafter, Swart worked for Schneider Electric for a period of 11 years – first as vice president – Industry & Automation Business southern Africa, then as vice president of the Mining, Minerals and Metals Segment for Africa Geography, Global Operations and finally as vice president and regional segment leader of Middle East & Africa (MEA ), Mining, Minerals and Metals, Global Operations, before moving over to 4Sight in 2018. (https://www.linkedin.com/in/wilhelm-swart-a2b1a73/)