The global mining automation market was valued at USD 4.90 billion in 2022 and is projected to grow at a compound annual growth rate (CAGR) of 7.3% from 2023 to 2030. This anticipated growth is primarily driven by rapid technological advancements, especially in the fields of Artificial Intelligence (AI) and robotics. These innovations have led to a higher adoption of mining automation solutions aimed at enhancing production efficiency. The increasing trend towards implementing cutting-edge technologies is significantly boosting the demand for automated mining systems.

Furthermore, the rise of the Internet of Things (IoT) in the mining sector is enabling mine management to access real-time data and analytics, supported by advanced visualization tools. Many mining operators are forming partnerships with technology companies to establish wireless networks in underground environments, further enhancing operational efficiency.

Gather more insights about the market drivers, restrains and growth of the Mining Automation Market

For instance, in April 2021, International Business Machines Corp. (IBM) made headlines by acquiring myInvenio, an Italian startup that specializes in process mining software. This acquisition aims to integrate myInvenio's process and task mining technology into IBM Cloud for Robotization, a platform designed to optimize and manage robotic operations. By utilizing this data-driven software and its associated tools, companies can enhance tracking across various functions such as sales, production, procurement, and accounting.

Moreover, the increasing emphasis on mine and worker safety is also contributing to the growth of the industry. Traditional mining methods often compromise worker safety, leading to heightened risks at mining sites. The growing focus on safety is driving further adoption of automated solutions, which can mitigate hazards and improve working conditions.

Application Segmentation Insights

The mineral mining segment led the market in 2022, accounting for more than 34.85% of the global revenue. The metal mining application is expected to show significant growth during the forecast period. This growth can be attributed to the increasing adoption of autonomous technology in metal exploration activities. Additionally, the rising demand for metals such as copper, zinc, lead, and nickel by various application industries is expected to contribute to revenue growth. Metal mining has also seen a surge in demand for automated solutions to meet the increasing need for base metals.

For example, in February 2022, UltimateSuite, a SaaS company, provided Task Mining results for automated business process analysis. The company launched robotic process mining software on its platform to enhance task discovery. This new extension allows clients to automatically identify duplicative tasks that can be automated or simplified, maximizing effectiveness and improving business return on investment. The software generates data on task frequency, total time spent on activities, and the number of users, processing this information to identify actions based on repetitive patterns, which can be excluded, simplified, or automated to achieve cost savings.

The coal mining segment is also expected to hold a significant market share. The increasing need to improve mining conditions at coal sites has led to the deployment of autonomous solutions in these areas. For instance, the Commonwealth Scientific and Industrial Research Organization (CSIRO) has partnered with the Australian coal industry to develop an underground automation system that isolates workers from mining hazards while simultaneously improving productivity.

Additionally, in April 2021, IBM began a partnership with Celonis, a data processing company that offers SaaS solutions to enhance business processes. This initiative aims to improve process mining software and identify inefficiencies across business processes. The software will help rectify various operational aspects, including finance, supply chain, HR, and customer experience, allowing companies to understand how their operations function and make necessary adjustments accordingly.

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