In the mining industry, competition is fierce, and the introduction of predictive maintenance technology can effectively improve the competitiveness of enterprises.

Losing critical assets can be devastating, especially in mining. The loss can cause unplanned downtime that can cost billions of dollars per year. To be more proactive in preventing these events, industrial organizations and mining companies are beginning to schedule downtime events by employing advanced technologies and predictive maintenance.

With predictive maintenance, critical assets are monitored, and data from connected technologies such as sensors, control systems and smart machines, is analyzed. Leveraging technology like FactoryTalk Analytics and applying machine learning technology, engineers can identify normal operations and build out data models to help predict, monitor for, and mitigate future failures or issues as part of a preventive maintenance strategy.

Using a prescriptive analytics solution helps customers achieve business outcomes such as overall equipment effectiveness (OEE) improvement, downtime reduction, and quality or process improvement.

About Shandong Mining

Shandong Mining maintains a complete industrial chain from exploration, mining, processing, refining and sales of gold products and relevant scientific and technological research and development. To provide an idea of size and scope, with Barrick Gold Corporation, Shandong Mining operates Veladero gold mine, the largest gold mine in Argentina and the second largest in South America.

Shandong Mining built an intelligent control industrial internet of things (IIoT) cloud platform data center in Optical Valley Software Park, Huangdao District, Qingdao City, Shandong Province, China.

Through this center, Shandong Mining wanted to unify hardware, software, network and other resources using cloud computing, big data and mobile technologies. The system would manage the operational data of conveyor equipment, customer information data, and provide full-life management of equipment.

For this project, Shandong Mining was focused on belt conveyor operation.

Digital transformation: The time is now

Like other cyclical industries, mining is driven by steady global economic growth and market fundamentals, and also by an increasing demand for materials to support new technologies.

The industry still faces major operational challenges, including process efficiency and cost control, specifically with equipment maintenance.

Mining companies have come up against these same challenges for decades, but the opportunity for addressing them has expanded with the addition of a new variable: digital transformation.

Digital transformation provides a major opportunity to address some of the greatest challenges in the mining industry. The World Economic Forum projects that digital transformation initiatives will result in more than $320 billion worth of value from 2016 to 2025.

With the maturity of the IoT — and big data technology — Shandong Mining decided that now was the time to invest in digital transformation. The goal: improve real-time monitoring of equipment, including vibration, temperature, pressure and noise.

Especially in big industries like mining, oil and gas, uptime of critical assets drives the bottom line. This also includes critical machines in continuous-manufacturing operations. Using preventive maintenance provides customers with the ability to monitor predictions and analyze details without needing to build their own data models or engineer their own solutions.

The team also focused on data analysis, predictive equipment failure, and additional options for remote service and troubleshooting to make maintenance more intelligent and reliable while lowering costs.


While investments in smart manufacturing are growing by the billions, many companies are finding they lack the leadership, infrastructure and worker skills to successfully implement digital transformation projects. The problem isn’t isolated to heavy industries either: a Gartner study showed that across market segments, 85% of big data projects fail.

Enabling successful initiatives in the mining industry requires the ability to leverage data effectively and then share it with everyone who needs to see both historic and real-time information to predict and help prevent downtime.

The operation of Shandong Mining’s maintenance system is controlled intelligently, and the expected operation and maintenance effect can save 12% of the scheduled maintenance cost and 30% of the maintenance cost, reduce 50% of the mechanical failure time and 70% of the failure rate.

The value of digital transformation for Shandong Mining is undeniable. Using this experience as a guideline, mining companies undertaking similar initiatives should be intentional and well-planned in their approach, defining the strategy and roadmap, and approach digital transformation as a journey and not one destination.