Mining technology must deliver measurable improvements in safety, productivity and predictability rather than simply digitise operations, industry leaders said at the 2026 BME Technical Summit yesterday.
According to the leaders, mining companies need to move beyond adopting individual digital tools and embrace integrated, evidence-driven operating systems that connect drilling, blasting, fragmentation and downstream processing, according to speakers at the summit held on Wednesday.
Speaking during the summit, Nishen Hariparsad, General Manager – Technology and Marketing at BME, said the mining industry’s growing access to artificial intelligence (AI), automation, robotics and digital applications would deliver meaningful benefits only when these technologies improved operational decision-making and generated measurable value.
“The test is whether the operation can make a better decision, with greater confidence, and demonstrate that result under the operating environment,” Hariparsad said.
His presentation highlighted the need to connect design, field execution, performance measurement and operational learning into a continuous feedback loop, enabling mining operations to understand why particular outcomes occur and use that knowledge to improve subsequent activities.
Hariparsad argued that technological sophistication alone does not constitute innovation. Instead, innovation occurs when a capability is adopted in everyday operations, changes decisions and produces a demonstrable advantage.
“If a technically brilliant solution does not fit the workflow, it will not be used consistently,” he said, warning that technologies that add administrative complexity without improving the quality or speed of decisions risk becoming another layer of work.
Closing the mine-to-mill information gap
A central theme of Hariparsad’s presentation was the fragmentation of operational information across the mining value chain.
He noted that mining companies routinely measure blasting performance, equipment activity and downstream production outcomes, but the information is often disconnected, making it difficult to establish reliable cause-and-effect relationships.
The resulting information gaps can prevent operators from determining whether performance variations stem from the original design, execution in the field, geological conditions or constraints elsewhere in the production process.
“A connected evidence chain would allow operations to compare design intentions with actual field conditions, establish whether activities were executed as planned and link the resulting fragmentation and material movement to downstream productivity and recovery,” Hariparsad said.
This would enable mining companies to distinguish between design weaknesses and execution problems, while identifying opportunities to improve subsequent blasting plans and operational decisions.
“Measurement without a change decision is merely informative. It is not a closed-loop optimisation,” he said.
The approach places particular emphasis on ensuring that information collected after a blast becomes an input into the next design rather than remaining a retrospective performance report.
For BME, this means integrating its explosives, initiation systems, digital applications, manufacturing capabilities and technical expertise into a connected operating framework.
Hariparsad cited BME’s software suite, including XxploLog, XxploCharge, BlastMap and XxploSmart, as part of the capabilities supporting planning, field execution, analysis and the preservation of design intent.
“The competitive advantage lies not in any single product or software application, but in how the components work together to generate useful data, develop insights and inform better decisions,” he said.
Visual AI strengthens operational visibility
The summit also highlighted the role of visual artificial intelligence in mine-to-mill optimisation, with Ravi Sahu, Chief Executive Officer of Strayos, bringing the perspective of a platform focused on applying visual AI to mining operations.
Visual AI can support the collection and analysis of operational information, helping mining teams connect observations from the field with decisions affecting productivity and downstream performance.
Within an integrated mine-to-mill framework, the objective is to improve visibility across interdependent stages of production and help operators understand how upstream activities influence subsequent processes.
“Connecting these stages is particularly important because improvements in one operational measure do not necessarily translate into better overall mine performance,” said Sahu.
Changes in fragmentation, for example, must be assessed alongside loading efficiency, crushing performance, recovery, dilution and environmental considerations.
Measuring value across the entire operation
Hariparsad said mining companies should evaluate technology against a balanced set of operational indicators rather than relying on a single measure of success.
These include fragmentation size distribution, oversize material, material movement, loading rates, cycle times, crushing utilisation, recovery, dilution control, consistency and environmental performance.
“An improvement in fragmentation, for instance, should not automatically be considered successful if recovery deteriorates, costs increase or environmental risks emerge.”
He stressed that performance targets must reflect the conditions and priorities of individual mining sites, as geological characteristics, operational constraints and production requirements differ.
Predictability is also critical. Mining operations need results that can be repeated across changing geological and climatic conditions, allowing more reliable planning, resource utilisation and production commitments.
Integration and partnerships are essential
Hariparsad said successful digital transformation does not require every mine to replace its existing applications with one large technology system. Instead, operations need compatible data sources, shared identifiers and integration mechanisms that preserve context across the mining value chain.
He outlined a progressive approach beginning with establishing common foundations, connecting workflows and optimising relationships between design and execution before introducing greater automation.
“Automation, he argued, should be introduced only when the underlying evidence and operational processes are sufficiently reliable,” he said.
He also emphasised that technology must strengthen, rather than replace, accountable human judgement in high-consequence mining decisions. Security, appropriate interfaces and the ability to work across technology providers should be considered from the outset.
Partnerships between mining companies, technology providers, service contractors and technical teams are therefore necessary to establish shared objectives and performance indicators.
“Integration is the value multiplier,” Hariparsad said, explaining that individual products and data streams may generate value independently, but their combined contribution increases when design, execution, outcomes and performance measures are connected.
According to the leaders, the future of mining technology will depend less on the number of digital tools deployed and more on the industry’s ability to turn connected data into safer operations, more consistent production and measurable improvements across the mine-to-mill value chain.
