RESEARCH REPORT

In brief

In brief

  • Autonomous operations in mining have the potential to significantly improve efficiency and productivity, while increasing safety and sustainability.
  • The key to taking autonomy to the next level will be increasing the use of intelligence—such as AI, machine learning, analytics and more—in systems.
  • Several factors will be instrumental for success as mining companies explore increased autonomy.


Mining’s changing imperatives

In the mining industry, “purpose” has become an increasingly critical factor for a variety of stakeholders.

Consumers are demanding responsibly sourced products from companies that provide fair and safe employment for their workforce, while looking after the environment and the communities in which they operate. Investors too are seeing value in behavior that leads to less risk and more reward—and they are becoming less willing to invest in companies that don’t measure up.

These pressures are evident in the growing demand for companies to assess their performance against a Triple Bottom Line—one that measures social, environmental and financial performance. At the same time, the traditional pressures to be efficient and cost-competitive are still very much in force. Autonomous operations have the potential to succeed on both fronts.

Autonomous operations: A broader view

As self-driving vehicles continue to mature, and the Internet of Things (IoT) and wireless connectivity become more widespread, the mining industry has shown a growing interest in automating haul trucks and other mobile equipment. Today, a number of companies have fleets of autonomous trucks, trains and loaders at mine sites, or are piloting the use of these vehicles.

These efforts are a great leap forward from traditional practices, but they are just scratching the surface of how autonomous systems can be used in mining. Most of the industry’s autonomous initiatives focus on individual pieces of equipment and are, for many, still in the early stages with just three percent of mobile equipment in the industry being autonomous.

In Accenture’s view, autonomous mine operations can and will go much further.

Perhaps the fullest example of autonomy at work is a Resolute Mining operation in Mali. The entire production operation—drilling, charging, blasting, loading and trucking—is carried out via an autonomous system. This has reduced the cost of gold production by $135 per ounce and cut mining costs by 30 percent.

While the example above is relatively isolated, it provides a sense of the potential value that autonomous operations could deliver.

Mined Over Matter: The Future of Autonomous Operations

Future mining operations will drive efficiency and safety while attracting the best talent with a focus on creating more responsible, sustainable operations.

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3%

of the industry’s mobile equipment is currently autonomous

+15%

Productivity improvements between 15 and 30 percent are being reported from autonomous hauling

Autonomous operations also have the potential to reduce fuel consumption, greenhouse gas emissions, water and energy consumption and waste.

The World Economic Forum projects that automation and robotics could prevent 10,000 injuries in the mining and metals industries in the decade to 2025.

The World Economic Forum has projected that automation and new technologies will significantly reduce injuries in the decade ending in 2025. This, in a period where autonomous operations have just been gaining a foothold:

10K

Injuries automation and robotics

22K

Injuries connected worker technologies

12K

Injuries remote operating centers

The building blocks of autonomy

The key to taking autonomy to the next level will be the increasing use of intelligence in systems, in the form of artificial intelligence (AI); machine learning; robotic process automation; descriptive, diagnostic, predictive and prescriptive analytics; and scenario modeling. These technologies allow systems to understand the data flowing through operations, enable situational awareness, develop near-real-time insights into operations, and determine what options to consider.

As companies explore increased autonomy, there are several factors to keep in mind that will be instrumental to success. Companies need to:

  • Focus on value. The autonomous path to value will be as different as each business. Having clear visibility of the key value drivers is critical to avoiding false starts and matching stakeholder expectations.
  • Address the foundation. Ensure IT architectures are ready to support communications between various systems and types of equipment. Assess the interoperability of systems, which is key to integrating operations across the mine and the value chain. Companies also need to assess cybersecurity requirements, because a breach of autonomous systems could mean losing control of systems and processes.
  • Ensure data readiness. Being able to use data from various sources is critical to AI and analytics-based insights and decision making. Companies need to consider their data-handling capabilities to capture and manage ever-growing volumes of data, while ensuring the data used to drive decision making is accurate and trusted. Overall, ensuring data readiness is a key prerequisite—without it, autonomous capabilities will be limited, at best.
  • Manage the change. Mining companies can help their people feel more comfortable with new approaches by communicating clearly, building trust and preparing them to succeed in the new environment. Companies can also apply these concepts to local communities to manage fears about the potential impact of autonomous operations on employment and safety—and help maintain the license to operate granted by the community.


David Burns

Managing Director, Lead – Global Mining​


Liv Carroll

Senior Principal – Mining Transformation and Applied Intelligence


Constantino Seixas Filho

Executive Principal – Industry

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