The mining equipment category is anticipated to grow at a CAGR of 5.1% from 2023 to 2030. Mining activities are increasing to extract metals and minerals from the earth in response to the growing demand for these resources, driving the growth of the category. Moreover, the adoption of natural complex and mineral resources such as diamond, iron ore, coal, and uranium, coupled with the increase in the need for mineral fertilizers to enhance agricultural yield supplements are fueling the demand for the category. The rising utilization of technologies such as IoT, sensors, and automation is reducing the labor cost and operational time associated with the activities. For instance, radar sensors are being used to process bulk solids whereas magnetic susceptibility meters and spectrometers are being used to detect wear and tear in mining equipment. All these factors result in a demand for innovative equipment.

The mining equipment industry is diverse, covering a wide range of heavy equipment and light machinery for either underground, surface, or other mining operations. Mining can occur at the underground or surface level. Surface mining is one of the most common methods for non-fuel minerals, accounting for 97% of the total quantity extracted. Heavy mining equipment includes large machines such as excavators, haul trucks, bulldozers, drills, and crushers. Surface mining equipment consists of hydraulic machine shovels, wheel loaders, highwall miner, draglines, etc. Other equipment includes mobile mining units, drill rigs, water trucks, and autonomous machinery. Mobile mining units are an alternative to truck and shovel dredging and a sustainable way of mining. Autonomous machinery includes teleoperated bulldozers, self-driven trains, and remote-controlled excavators, among others.

In the mining industry, IoT is utilized to achieve not only cost and productivity optimization but also to ensure the safety of people and equipment. Under IoT, the mine sensor network is one of the key innovations. By leveraging IoT, AI, and advanced analytics, mining companies can predict with 85% accuracy about the amount of ore present in crushed bins. The data is collected from 100,000 machinery sensors across international mining sites. By utilizing devices such as wearables, drones, scanners, and proximity detection sensors on moving machinery and vehicles, it is possible to achieve significant gains in productivity. Different ore grades can be identified by these devices and the information can be fed to the various components of the mining value chain.

Order your copy of the Mining Equipment Procurement Intelligence Report, 2023 - 2030, published by Grand View Research, to get more details regarding day one, quick wins, portfolio analysis, key negotiation strategies of key suppliers, and low-cost/best-cost sourcing analysis

By using AI, mining companies can predict the material requirements, extraction volume, and material consumption by analyzing data. This results in an increase in efficiency and material savings. AI-driven remote monitoring systems are becoming a crucial part of underground mining surveillance. Inspecting the location and condition of workers and assets with respect to environmental parameters are critical to running mines safely, productively, and effectively. AI predictive models also help mining companies to improve their metal processing methods.

Mining equipment that runs on batteries frequently possesses comparable power to its diesel-powered counterparts. The substitution of diesel engines with electric ones can substantially diminish the CO2 emissions produced during mining operations. Currently, battery-powered machinery include trucks, rigs, and wheel loaders. Companies such as Epiroc manufacture battery-driven electric fleet that enables savings in maintenance, ventilation, and cooling. It offers zero-emission underground machinery such as loaders, mini trucks and rigs, production drilling, and rock reinforcement.

The global category is highly fragmented in nature. The mining industry has a complex value chain, which includes elements such as exploration, mining, and processing. As a result of the complexity of the mining supply chain, different jurisdictions, countries, and companies become connected and hence play an important role. Moreover, system fragmentation is one of the major barriers to businesses in this industry, due to which companies have no single platform to standardize the process among organizations. In many companies, mining divisions operate independently, and as a result, there is a lack of coordination and information sharing. This leads to increased fragmentation and a lack of integration in the processes. Companies are trying to implement AI and other digital solutions to enable standardization and thereby increase operational efficiency.

For instance, regionally in India, this highly fragmented market has organized as well as unorganized sectors. Organized segments mainly include large private organizations that cater to small, medium, and large-scale projects. On the other hand, the unorganized sector mainly operates on a small-scale basis. Global companies are also developing new digital mining solutions to enhance their offering. Caterpillar, Komatsu, Metso, and other large firms are also involved in new product launches and partnerships to sustain in the market and attain a competitive edge. For instance:

• In December 2023, Epiroc introduced new digital solutions in the surface mining industry, which consists of safe blast and blast support. This solution can direct warning messages to persons situated in defined risk zones.

• In October 2023, Epiroc and Newcrest, a gold mining company, entered a MOU (memorandum of understanding) agreement. The main aim was to implement a comprehensive approach to the mining process. Under this collaboration, Epiroc's automation, electrification, and digitalization technology will be employed in Newcrest's mines to enhance and optimize the excavation process.

Buyers in the category, such as mining companies, can have moderate to high bargaining power. They are often large entities with significant purchasing volumes. However, the specialized nature of mining equipment and the importance of reliable and high-quality machinery might limit the buyers' power to some extent.

Browse through Grand View Research’s collection of procurement intelligence studies:

• Bearings Procurement Intelligence Report, 2023 - 2030 (Revenue Forecast, Supplier Ranking & Matrix, Emerging Technologies, Pricing Models, Cost Structure, Engagement & Operating Model, Competitive Landscape)

• Metal Finishing Procurement Intelligence Report, 2023 - 2030 (Revenue Forecast, Supplier Ranking & Matrix, Emerging Technologies, Pricing Models, Cost Structure, Engagement & Operating Model, Competitive Landscape)

The total cost of ownership of manufacturing machinery can be divided into fixed and variable costs. Fixed costs include elements such as capital, machinery, depreciation and salvage value. Variable costs include material, labor, repair and maintenance, legal costs, and others. The mining equipment cost can range from USD 1 million to USD 5 million. Mining equipment maintenance costs account for 30% to 50% of the overall operational costs. The cost of equipment also depends on the type of equipment and other specifications.

Under sourcing intelligence, end-user companies or clients generally outsource their mining equipment requirements to these category vendors. It is estimated that more than 85% of mining companies outsource more mining activities than mineral processing. Vendors are evaluated on equipment quality and type (underground or surface equipment), and technology offered (e.g., technology-driven fleets, automated vehicles, etc.) during mining equipment purchases. When selecting the equipment, it's crucial to consider factors such as the analyzing mining site, the reliability and effectiveness of the machinery, the equipment's cost, and the suppliers' experience. 

Mining Equipment Procurement Intelligence Report Scope

• Mining Equipment Category Growth Rate: CAGR of 5.1% from 2023 to 2030

• Pricing growth Outlook: 5% - 6% (annual)

• Pricing Models: Volume-based pricing, product-based pricing, competition-based pricing

• Supplier Selection Scope: Cost and pricing, past engagements, productivity, geographical presence

• Supplier selection criteria: Types of equipment offered, application of equipment, delivery time and option, technology-driven products, regulatory compliance, operational and functional capabilities, and others

• Report Coverage: Revenue forecast, supplier ranking, supplier matrix, emerging technology, pricing models, cost structure, competitive landscape, growth factors, trends, engagement, and operating model

Key companies 

• Caterpillar

• Liebherr

• John Deere

• Epiroc

• Metso

• Komatsu

• Guangdong Leimeng Intelligent Equipment Group

• Sandvik

• Baichy

• Vipeak Mining Machinery

Brief about Pipeline by Grand View Research:

A smart and effective supply chain is essential for growth in any organization. Pipeline division at Grand View Research provides detailed insights on every aspect of supply chain, which helps in efficient procurement decisions.

Our services include (not limited to):

• Market Intelligence involving – market size and forecast, growth factors, and driving trends

• Price and Cost Intelligence – pricing models adopted for the category, total cost of ownerships

• Supplier Intelligence – rich insight on supplier landscape, and identifies suppliers who are dominating, emerging, lounging, and specializing

• Sourcing / Procurement Intelligence – best practices followed in the industry, identifying standard KPIs and SLAs, peer analysis, negotiation strategies to be utilized with the suppliers, and best suited countries for sourcing to minimize supply chain disruptions