Automated Remote Condition Monitoring Improves Mine Site Operations
Over the past two years, there has been a significant increase in both the number and type of parameters being monitored by mining companies. This jump was not unique to a specific region or commodity class and appeared to be a global phenomenon.
To better understand this trend, Bentley Systems and ThoughtLab surveyed 500 industry experts across a broad spectrum of functional roles, including those in the mining sector. The results of the study, published in the 2023 Condition Monitoring Report, offer valuable insights into the state of monitoring practices, and show a growing adoption of automated remote monitoring in the mining industry.
Mining Industry Trends
The transition from manual to automated condition monitoring is on the rise as organizations embrace connected sensor technology, reducing the need for frequent manual sampling. The study revealed that 26% of mining companies fully automate their condition monitoring practices.
The study also confirmed the trend toward monitoring a growing range of parameters, with 34% of companies having increased the number of parameters measured over the past two years. The primary parameter monitored at mine sites is particulates/air quality — with 98% of mining companies monitoring this parameter. Other top parameters for mine sites include load/pressure/strain, wind/temperature, and peak particle acceleration.
By moving to automated remote monitoring, these companies are broadening their monitoring scope, tracking more parameters, and more importantly integrating data with advanced software workflows in real time. This is highlighted by the fact that 55% of mining companies combine sensor data with asset management systems, while half integrate it with geographic data from GIS layers. Furthermore, 44% of companies incorporate their mine site sensor data with digital twins—virtual models of assets created from real-world sensor data.
Respondents indicated that digital twins offer a more comprehensive and holistic view of conditions and trends and provide them with the ability to conduct forecasting and what-if scenario analysis as they contextualize the increase in monitored data.
Condition Monitoring Pain Points
According to the survey results, more than half of mining companies cited time delays as their most significant challenge. These delays often stem from manual data collection, laboratory analysis time, complex data processing and analysis, equipment downtime, and the lack of automation.
Sampling errors were also a concern, arising from inadequate sample sizes, poor sampling techniques, or human error. Notably, organizations that rely mainly on manual monitoring tend to encounter a higher number of hurdles.
Automated remote monitoring offers solutions to these pain points, as organizations practicing this approach experience fewer challenges related to sample time, cost, and safety issues, as well as fewer issues tied to infrequent samples when compared to those that do mostly manual monitoring.
Return on Investment
Currently, mining companies automate 64% of their condition monitoring. Over the next two years, that number is expected to increase to nearly 73%. The motivation behind moving to automated monitoring in the mining industry is clear—it provides critical insights for the safe and efficient operation of mine sites, including a deeper understanding of complex factors at play.
Moreover, the switch to automated condition monitoring is a means to achieve cost benefits and increase return on investment. There is little difference in total costs between automated and manual monitoring methods. In fact, after recovering the initial investment associated with automating monitoring systems, the ongoing costs are typically lower than those incurred with the time-consuming manual approach.
For example, a shift to automated remote condition monitoring yielded cost savings at the largest tailings storage facility in North America. The solution was implemented in just five days and saved $218,000 in upfront engineering time. Furthermore, it increased data availability to real time, resulting in an annual cost reduction of $143,000.
Ultimately, organizations will find that the benefits and returns from automated remote monitoring far outweigh the initial investment, with some organizations reporting returns of $1 million or more.
For deeper insights into the latest condition monitoring trends and practices within the mining industry, download the 2023 Condition Monitoring Report.