Thermographic monitoring and computer vision analyzing the shell of an operating grinding mill to detect abnormal heat patterns while maintenance specialists review equipment condition in real time.
心を動かす会話

Thermal Vision for Mill Reliability

Revealing hidden mill-shell anomalies through thermographic monitoring and computer vision while critical grinding equipment remains in operation.
会議のスケジューリング
ポッドキャストを聴く
-15
+15
0:00
/
0:00
The most expensive problems are often the ones developing out of sight.
WHY THIS "MILL-RELIABILITY" CHALLENGE?
Direct inspection can require stopping the mill and entering the asset, while liner detachments, damaged bolts, and seal failures may progress between scheduled inspections. Thermal behavior creates another source of evidence, visible while the equipment is still operating.
主なメリット
Heat can become an early maintenance signal

Thermographic monitoring helps maintenance teams distinguish normal variation from conditions that deserve targeted verification without waiting for the next shutdown.

チェックアイコン
See beneath the shell without going inside

Gain external visibility of potential internal conditions during operation.

チェックアイコン
Intervene on evidence, not suspicion

Identify thermal indicators linked to wear, detachment, leakage, or damaged bolts.

チェックアイコン
Narrow the maintenance search area

Focus inspection and repair scopes where evidence is strongest.

チェックアイコン
Use components with greater confidence

Support better timing for replacement, continued use, and shell-life decisions.

NTTデータのサポート体制は？

01
Establish the thermal baseline

Define capture locations, operating conditions, inspection frequency, and expected temperature patterns.

Engineer using a thermal camera to inspect a mill shell during operation, capturing temperature patterns to establish a baseline for condition monitoring and maintenance.
02
Compare what changes over time

Analyze temperatures across neighboring bolts, shell areas, and successive observations.

Overhead view of maintenance engineers analysing thermal data from a mill shell, comparing temperature patterns across bolts and adjacent areas during operation.
03
Separate normal heat from meaningful anomalies

Identify patterns associated with loose or damaged bolts, liner deterioration, and sealing problems.

A computer screen with a image identifying patterns associated with loose or damaged bolts
04
Make condition easy to interpret

Represent normal, warning, and critical zones in a digital shell integrity view.

An image identifiying normal, warning, and critical zones in a digital shell
05
Turn evidence into maintenance action

We don’t stop at anomaly detection. We translate findings into prioritized inspection and maintenance decisions.

Mining team using digital connectivity to improve safety, operational intelligence and autonomous mining operations.
hermal imaging reveals hidden heat patterns in mining operations
実証済みの効果
Hidden heat. Visible evidence. Better-timed maintenance.
重要な結果
The value lies in narrowing uncertainty before shutdown decisions are made.
チェックアイコン
Surface earlier signs of deterioration

Thermal indicators reveal structural anomalies before direct inspection.

チェックアイコン
Focus intervention precisely

Maintenance effort targets shell areas with the strongest evidence.

チェックアイコン
Reduce exposure between inspections

Earlier visibility lowers the risk of undetected progression.

チェックアイコン
Support asset-life decisions

Better timing can improve availability and component-life management.

See the signals that conventional inspection can miss.

Turn thermal evidence into smarter maintenance decisions.

話しましょう

NTT DATA関連の話題 
すべての講演を見る
Mining operations team deploying Physical AI through controlled implementation waves, progressing from supervised use cases to domain-level autonomy and cross-domain orchestration while monitoring safety, performance, and operational continuity.
天然資源
自律運転
Implementing the Agentic IROC
Deploying Physical AI in controlled waves so the operation builds trust, demonstrates value, and advances toward cross-domain orchestration without compromising safety or continuity.
Mining engineers transforming an approved autonomous operating model into production-ready engineering packages covering AI agents, data, integrations, authority, cybersecurity, testing, and commissioning.
天然資源
Engineering the Agentic IROC
Turning an approved autonomous operating model into buildable, testable, cybersecure engineering packages for agents, data, integrations, authority, and commissioning.
Integrated mining operations center using Physical AI to connect mine, plant, maintenance, logistics, energy, water, and safety operations while specialized AI agents coordinate recommendations under human supervision.
天然資源
自律運転
From Recommenders to an Agentic IROC
Transforming the integrated operations center into a Physical AI system that understands the end-to-end operation, coordinates specialized agents, and turns insight into governed action.
Mining safety professionals reviewing camera evidence while an operational vehicle and ore train interact at an active mine rail crossing monitored by computer vision.
天然資源
Rail Crossing Intelligence: Before the Train Arrives
Using computer vision to detect unsafe vehicle behavior and expose time-critical interactions between road and rail.
Motion analytics monitoring a suspended industrial load during a lifting operation at a mining site, tracking speed, oscillation, amplitude, and trajectory while an operator supervises the operation.
天然資源
Predictive Lifting Safety
Using motion analytics to detect abnormal speed and oscillation in suspended loads before lifting risk escalates.
Automated visual inspection system analysing copper cathodes on a production line while an industrial operator monitors quality data in a modern mining processing facility.
天然資源
AI-Assisted Copper Cathode Inspection
Embedding real-time visual quality control into cathode production to detect defects, reduce errors, and strengthen traceability.
Computer vision analyzing ore fragments in real time as they move along a mining conveyor belt, while engineers review particle-size distribution and identify oversized material before it reaches downstream grinding equipment.
天然資源
Ore Size Intelligence in Motion
Automating real-time granulometry on conveyor belts to reduce jams and stabilize material entering the grinding process.
Mining operations team using real-time computer vision to monitor dust and haul-road conditions across multiple camera feeds and coordinate targeted water-truck deployment.
天然資源
Vision-Optimized Haul Roads
Turning mine cameras into real-time intelligence for dust, surface condition, and more targeted water-truck deployment.
Mining operations team deploying Physical AI through controlled implementation waves, progressing from supervised use cases to domain-level autonomy and cross-domain orchestration while monitoring safety, performance, and operational continuity.
天然資源
自律運転
Implementing the Agentic IROC
Deploying Physical AI in controlled waves so the operation builds trust, demonstrates value, and advances toward cross-domain orchestration without compromising safety or continuity.
Mining engineers transforming an approved autonomous operating model into production-ready engineering packages covering AI agents, data, integrations, authority, cybersecurity, testing, and commissioning.
天然資源
Engineering the Agentic IROC
Turning an approved autonomous operating model into buildable, testable, cybersecure engineering packages for agents, data, integrations, authority, and commissioning.
Integrated mining operations center using Physical AI to connect mine, plant, maintenance, logistics, energy, water, and safety operations while specialized AI agents coordinate recommendations under human supervision.
天然資源
自律運転
From Recommenders to an Agentic IROC
Transforming the integrated operations center into a Physical AI system that understands the end-to-end operation, coordinates specialized agents, and turns insight into governed action.
Mining safety professionals reviewing camera evidence while an operational vehicle and ore train interact at an active mine rail crossing monitored by computer vision.
天然資源
Rail Crossing Intelligence: Before the Train Arrives
Using computer vision to detect unsafe vehicle behavior and expose time-critical interactions between road and rail.
Motion analytics monitoring a suspended industrial load during a lifting operation at a mining site, tracking speed, oscillation, amplitude, and trajectory while an operator supervises the operation.
天然資源
Predictive Lifting Safety
Using motion analytics to detect abnormal speed and oscillation in suspended loads before lifting risk escalates.
Automated visual inspection system analysing copper cathodes on a production line while an industrial operator monitors quality data in a modern mining processing facility.
天然資源
AI-Assisted Copper Cathode Inspection
Embedding real-time visual quality control into cathode production to detect defects, reduce errors, and strengthen traceability.
Computer vision analyzing ore fragments in real time as they move along a mining conveyor belt, while engineers review particle-size distribution and identify oversized material before it reaches downstream grinding equipment.
天然資源
Ore Size Intelligence in Motion
Automating real-time granulometry on conveyor belts to reduce jams and stabilize material entering the grinding process.
Mining operations team using real-time computer vision to monitor dust and haul-road conditions across multiple camera feeds and coordinate targeted water-truck deployment.
天然資源
Vision-Optimized Haul Roads
Turning mine cameras into real-time intelligence for dust, surface condition, and more targeted water-truck deployment.
ドラッグ