How leading mining companies are getting
smarter with condition monitoring

Unplanned maintenanceerodes profitability

Proactive maintenanceaverts losses

60% to 80%

2 to 3 times

2 to 5 times> 4 weeks$1 million USD /day20%of equipment malfunctions at mining sites
occur due to improper maintenancelifespan extension for mining plant equipment, madepossible with the proactive maintenance solutionsof planned maintenance expenditure overruns
happen due to a significantly higher unplanned
downtime for mining companies

Overall production losses and secondary
process and equipment damage due tounplanned downtime

advance alert on equipment wear andfailure, thereby reducing
downtime andfinancial risk

average savings onannual maintenanceexpenditure

Triggers to adopt condition monitoring (CM) systems
Reduceunplanned
downtime

Need for proactive
40%
maintenance60%

Improve47%
productivity

Costcontrol27%(% of mining companies surveyed)

Critical mining applications for condition monitoring
Screens: Due to high vibration and loads, there can be
structural damage and spring failures. Proper vibration
analysis performed, and vibrations constrained under setlimits can reduce this problem.

Crushers: Crushers operate at highpower to produce materials, putting
a lot of strain on internal parts, filters,and bearings.

Conveyers : Due to less lube oil supply andloads on the bearing there can be an
occurrence of bearing failure.

Electric Motors: Bearing failure is amajor issue in electric motors. It is
generally analyzed by vibration
analysis.

Ball/SAG Mills: Thermal stresses result from oil
lubrication failure and excessive vibration.
Slurry Pumps: Pumps undergo immense strain
due to the transfer of viscous material
throughout the pumping process. Sludge andslurry contain high solid content, which causes
pitting and cracking.
Turbines: Turbine bearing failures canresult from structural misalignments andlubrication oil defects. The malfunction canalso occur due to dislocation and fatigue
in joints while in operation.

Fans: Fans aresubjected to excessive
thermal and vibrationstress, a major reason
for fan failures.
Critical Nodes for Condition Monitoring:
Primary: Slurry pumps, Fans, Turbines, and Compressors.
Secondary: Blowers, Motors and Screeners.

Mining equipment with high frequency of failure

Our survey reveals that critical assets for miners differ based on the mineral they are extracting. The chart shows % of respondents identifying
an asset as critical.

Conveyors

100%

Crushers

89%

71%

56%

Screens

Gearboxes

67%

57%

44%

Blowers

57%

33%

22%

33%

33%

43%

Motors

29%

67%

78%

Compressors

22%

29%

33%

% of companies surveyed

33%

Steel & Ferrous Metals

33%
Coal

Other

Note: Other metals include gold, silver, nickel, aluminum, zinc, and potashRemaining challenges

Escalating safetyconcerns

Decreasing
productivityIncreasing skill gap due
to high retirement rates

Sustaining
equipment life

Bently Nevada's portfolio and expertise helps achieve productivity goals
A modular condition monitoring and evaluation system that supports up to 12 dynamic vibration and/or pressure
sensors, along with up to three pulse-based machine speed sensors
Real-time data collection across all active channels
Portable size and shape for mounting locally on the machinery that it would be monitoring, eliminating the need for longsensor cable runs to centralized rack-based systems
Event data recorder for smarter data collection

Site-wide condition monitoring is the future of effective maintenanceSite-wide solutions enable an eagle’s-eye view of operations, facilitating higher-order operational optimization and real-timedecision-making in the proactive maintenance journey of miners
More than 60% of the leading 20 miners(early adopters) have already started their journey with site-wide CM systems

Adoption (% respondents)

40% Stillthinking

60% implemented
or evaluating

Incorporation of AI/ML% of companies surveyed
Currently
Implemented

45%

5%

Early-Stage
Implementation

30%

Evaluating

20%

Considering
Evaluation

Benefits of using AI/ML-embedded CM Systems
20% increase inefficiency andoptimized production
processes$30 million USD savings

coupled with a 7% expansion
in mining yield*AI - Artificial Intelligence, ML - Machine Learning

Enhancedmine safety

Lowerequipment
replacement
and repair
cost

ROI

Decreased
downtime andproductivity
loss

Higherminingyield

Please contact us at

Bently.com

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more about Mining

80% reduction in data processing time. About 30% of miners

are evaluating AI and ML functionalities and about 45% of themajor miners have implemented IoT-based systems tooptimize their operations.