Mining condition monitoring made possible using cloud automation and the Arrowhead Framework

Arrowhead Task 1.6:
Case: Mining industry condition monitoring
www.arrowhead.eu
1
Mika Karaila, D.Sc. (Tech.)
Research Manager
mika.karaila@metso.com, +358 40 761 2563

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WP 1.6 Participants (FINLAND)
- Metso Automation (task leader)
 Mika Karaila, Yiqing Liang
- Outokumpu
 Petri Vuolukka, Pasi Lassuri
- VTT Technical Research Centre of Finland
 Erkki Jantunen, Ventä Olli, Määttä Kalle
- Wapice Ltd.
 Laurentiu Barna, Veli-Pekka Salo, Pasi Tuominen
- Tampere University of Technology
 David Hästbacka, Seppo Kuikka
- University of Oulu
 Esko Juuso, Antti Koistinen, Jouni Laurila

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Outokumpu
Multiple challenges in mining:
 Optimal and correct system operation
o Reduced risks
o Remote control
 Large number of devices from different vendors
o Cost-effective on-time maintenance
o Maintenance strategy
o Condition monitoring of devices and equipment
 ERP integration
Kemi Mine

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WP 1.6 Demonstration
STAVANGER
Information Services for Condition Monitoring
and Maintenance
 Data Aggregation and Unified Access
 Information Model and Interoperability
 Events and Notifications
 OPC UA Client/Server Architecture
WAPICE REMOTE MANAGEMENT (WRM)
 OPC UA Servers / Clients
 Generic Data Model & Databases
 Terminal Communication
 REST API
 VPN, Security Gateway
WRM TERMINAL (WRM247+)
 Data Acquisition
 Device Control
 Accelerometer, GPS
 RS-232, RS-485, USB
 Digital I/O, Analog Output
 1-Wire, CAN
 Ethernet, GPRS, 3G
WRM Desktop
 User Interface (web based)
Automation System
 Metso DNA
Beckhoff
 OPC UA Server
Beaglebone Black
 OPC UA Server
OPC UA (alarms & events)
Generic Information Model
process and control data
(e.g. from/to the Kemi mine)
OPC UA process and control data
OPC UA process and control data
condition monitoring
data (from the Kemi mine)
KEMI
TAMPERE
OULU
ESPOO
 VTT Node (Acceleration Sensor)
 Acceleration Data
 MIMOSA
condition monitoring data
VAASA (from the Kemi mine)
Enterprise Applications and
Mobile Clients
 Condition monitoring
 Condition and stress indexes
 Vibration analysis
 Grinding mill (Kemi)
 Wear part monitoring
 Hoisting rope damage
 Fine concentrate machine vision

Demo session: Metso
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BeagleBone Black:
OPC UA server
Node-red:
Sensortag
OPC UA client
Raspberry PI:
Camera
Node-red:
Cloud storage
Windows:
OPC UA client
Cloud:
Big Data
Beckhoff PLC:
OPC UA server

Demo session: Wapice
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Wapice Remote Management (WRM) System, OPC UA

Demo session: Tampere University of Technology
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OPC UA based aggregation of
heterogeneous device data for
maintenance information systems
Dynamic system structure enables
scalability to data gathering and
propagation of event notifications
from a multitude of devices
OPC UA information modeling for
declaring data relations and semantics
as well as views for different purposes
Consolidating
information model e.g.
for device, segment or
site level services (i.e.
Arrowhead framework)
Adaptation of legacy
system structures for
improved
interoperability
Built-in support for
information security for
a multi-vendor
environment

Demo session: VTT Technical Research Centre of Finland
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CMMS:
Registry
Work management
VTT Little Node:
Vibration acceleration
data
Wear plate monitoring
Windows:
Mimosa
Cloud:
Big Data
Maintenance
centre:
Wear plate
diagnosis

Preliminary results from the first test
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NaturalFrequencyOF_AveragedFTT
kHz
1.08
1.06
1.04
1.02
1.00
0.98
0.96
0.94
0.92
0.90
0.88
0.86
0.84
0.82
0.80
0.78
0.76
0.74
0.72
0.70
0.68
0.0 0.5 1.0 1.5 2.0 2.5
10^3
Change of natural frequency (1050 -> 710 Hz) of a wear plate during a
2 month period 19.4–24.5.2014

Demo session: VTT Technical Research Centre of Finland
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• Wireless data acquisition system using BT-LE sensor nodes, smartphones and
gateway units.
• Intelligent distribution of data pre-processing in node, in phone and in gateway-nodes
to optimize energy, bandwidth and capacity usage
• Use case/next steps: Implementation of distributed data analyzing system for wear
plate analysis utilizing distributed WSN architecture
Distributed analysis in WSN Smartphone data analysis

Demo session: University of Oulu, Overview
• On-site data processing
• FFTDerivationIFFTNorms and describing indices
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Location and setup Matlab demonstration Finding the degrees

www.arrowhead.eu
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Thank you!

Mining condition monitoring made possible using cloud automation and the Arrowhead Framework

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Mining condition monitoring made possible using cloud automation and the Arrowhead Framework