Japanese mining firm

Data Infrastructure Overhaul – Japanese Mining Firm (Copper Mines, Eastern Europe)

 

Outcome:

• 33% decrease in unscheduled equipment downtime
• 47% increase in mine yield forecasting accuracy
• €2.6 million/year production drop
• 19% increase in EBITDA due to better efficiency and resource allocation

How?

 

Situation:

A Japanese conglomerate specialising in mining and resource extraction had recently acquired two operational copper mines in Eastern Europe. These mines were previously managed under disparate local systems with limited digital integration, inconsistent record-keeping, and very little central oversight. The new management needed accurate production, safety, and equipment maintenance data to make timely decisions and ensure profitability, but current data collection practices made that nearly impossible.

Challenge:

Both sites lacked a structured data collection framework. Daily reports were manually written and stored in local formats, production data was inconsistent, and environmental and safety metrics were tracked reactively rather than proactively. There was no visibility from HQ in Tokyo into real-time mine operations. These inefficiencies resulted in unnecessary downtime, maintenance delays, inaccurate production forecasting, and overspending on procurement and logistics. The company estimated it was losing over €3.8 million annually due to poor visibility and delays in decision-making.

Solution:

Our consultancy led a full data infrastructure transformation. We implemented IoT-enabled sensors across mining equipment and logistics chains to automate real-time data capture. A centralised cloud database was established to consolidate data across both mines. Using this dataset, we built a custom dashboard that visualised production metrics, safety alerts, and equipment health in real time. We also trained local teams on new data entry protocols and deployed machine learning algorithms to forecast maintenance needs and detect anomalies in production patterns.