Transforming mining safety with enterprise digital twin
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Employee health and safety are central to the mining industry. Government regulations and laws on the health and safety of workers require miners, particularly in Australia, to ensure that people are not injured because of their work. In addition, safe mining operations are protected by the regulatory and policy framework.
Also, ensuring the health and safety of employees is not only a moral responsibility, but a business imperative. Miners can avoid considerable loss of production due to the closure of sections, shafts, or a mine and increased costs associated with workplace injuries. Sometimes, the closure of a mining operation results in the loss of jobs in local communities, threatening their existence.
The mining industry has made significant improvements in health and safety over the past decade, reducing fatalities and serious injuries. However, it still has one of the highest fatality rates. In 2021, 43 people from the International Council of Mining and Metals member companies died at work. Safety, therefore, continues to be the top priority for mining companies and will remain at the forefront until ‘zero harm’ is achieved.
Digital technologies have the potential to significantly improve mining safety. Over the years, technology providers have helped transform the mining landscape. From fast and reliable connectivity to ensuring secure data transmission around and between sites to intelligent and connected devices and data analytics leveraging IoT, digital technologies have played a major role. Not surprising, then, that about 44% of mining companies believe digital technologies can help improve the health and safety of their employees at mining sites.
Mining safety: Challenges and solutions
The mining sector is inherently considered a risky industry. But with the introduction of strict safety legislation and protocol and advances in safety equipment, the industry has seen its fatality rate drop over time.
However, most of these efforts involve controlling risks using administrative controls such as training, policies, and procedures. Unfortunately, these administrative controls become less effective as they do not consider all aspects impacting the safety of the employees, such as dust and gas exposure, weather, and an employee’s psychophysical make-up. It is just assumed that employees will be safe if they adhere to the policies and are trained to do the work safely.
When employees land in situations outside the scope of their organization’s safety policy, they are more prone to injury. Following such an incident, a post-event investigation is done to understand the underlying cause, which usually results in process and policy modifications or retraining of the employees. The risks are always hidden unless discovered and decisions are delayed, which results in the persistence of risk. Thus, present controls are more reactive and insufficient to eliminate the risks altogether.
The mining industry needs an advanced mechanism to proactively measure and monitor safety risks and identify unsafe situations and behaviours to altogether avoid safety incidents. With such a tool, miners can proactively identify deviations from the processes and dangerous behaviours and problems. Having such information handy, miners can proactively respond to problems to avoid safety incidents. The tool should be able to measure and monitor risks such as:
An AI-enabled enterprise digital twin brings a proactive view of overall operational safety in real time, a solution that is built to provide a real-time risk index for each area of the mining operation.
Improving safety with digital twin
AI can support better and faster decision-making, which is critical to improve health and safety conditions for frontline workers and reduce their exposure to dangerous situations. Miners can leverage digital twin technology to completely reimagine the monitoring and managing of safety risks and adverse events.
Digital twins are virtual replicas of physical assets, processes, and systems. digital twins use AI, machine learning, and advanced analytics with data to render real-time digital simulation models that are continually updated as their real, physical counterparts, or ‘twins’, change.
Digital twins allow mining operators to assess and interpret data from smart sensors and machine interconnection to improve operational safety and efficiency through AI-enabled technologies. This will transform mining into one of the safest occupations of its kind.
An enterprise digital twin (EDT) is best suited to solve the mining safety puzzle.
An EDT should act as a system of convergence between various dimensions that affect safety and helps assess actual safety risks in any scenario. An AI-enabled EDT brings a proactive view of overall operational safety in real time, a solution that is built to provide a real-time risk index for each area of the mining operation. The solution integrates real-time and offline data from various sources such as HSE policies, work instructions, standard operating procedures, RCAs, FMEA, maintenance plans and schedules, ERP, training and competency, access and geo-location, CCTV, IoT sensors, mobiles, watches, wearables, weather data, and more.
The digital twin will use all this information to calculate the area-wise real-time risk index, provide area-wise real-time risk scores and trends, and enable miners to mitigate adverse events through real-time RCA and predictive analytics. Health and safety supervisors can use this information to take corrective actions to minimise or eliminate risk. The EDT can provide real-time alerts to supervisors and the plant/equipment operators. It can integrate alert notifications through SMS and emails. It should be a highly customisable solution that can be implemented in various areas of mining operations, such as mining, processing, and logistics. The solution will have a built-in auto-prediction video analytics feature for posture detection, PPE identification, moving object detection, fire detection, identification of unsafe areas, and triggering alerts and ‘what-if’ simulations for experimentation and improving strategic decisions.
EDTs can help miners gain insights across the organization and enable them to respond faster, proactively identify possible deviations, and have minimal oversight. An EDT can create various situational use cases and simulated scenarios to identify hidden risks. It can also help with a risk-predicting model that forecasts real-time risks and recommends the next-best actions for faster decision-making. Managers can confidently take a behind-the-scenes look into the real-time system and device data. Digital twins enable them with next-generation predictive analytics models. These models can help predict the probability of the next potential unsafe event and identify hazardous areas with probable reasons for the potential event.
There have been some successful implementations of EDTs in other industries that have significantly impacted the safety performance of companies. In these cases, EDTs encompassing an AI-based decision engine have been used responsibly for the following tasks:
Beyond ‘zero harm’
In recent years, the safety philosophy has evolved beyond ‘zero harm’. It is an evolution of the traditional way of thinking about health and safety to focus on opportunity and build resilience, capability, and efficiency while working to eliminate injuries. The industry needs advanced technologies to improve workplace safety to enable faster decisions with high accuracy and optimize operations by improving safety.
By employing digital technologies like EDT, miners can become more proactive as compared to the current reactive approach. By running multiple simulations before engaging in work, miners can identify and eliminate risks. The real-time monitoring of risky jobs and real-time alerts will help avoid adverse events and allow miners to demonstrate a significant reduction in their total injury frequency rate, enabling them to meet government regulations and health and safety laws