1. Arrowhead Task 1.6: Case: Mining industry condition monitoring
Mika Karaila, D.Sc. (Tech.)
Research Manager

2. 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

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

4. WP 1.6 Demonstration condition monitoring data (from the Kemi mine)
Grinding mill (Kemi)
Wear part monitoring
Hoisting rope damage
Fine concentrate machine vision
STAVANGER
TAMPERE
KEMI
ESPOO
OULU
Condition monitoring
Condition and stress indexes
Vibration analysis
Automation System
Metso DNA
Beckhoff
OPC UA Server
Beaglebone Black
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)
process and control data
(e.g. from/to the Kemi mine)
condition monitoring data
(from the Kemi mine)
VAASA
OPC UA process and control data
(e.g. from/to the Kemi mine)
Information Services for Condition Monitoring and Maintenance
Data Aggregation and Unified Access
Information Model and Interoperability
Events and Notifications
OPC UA Client/Server Architecture
VTT Node (Acceleration Sensor)
Acceleration Data
MIMOSA
OPC UA process and control data
(e.g. from/to the Kemi mine)
Enterprise Applications and Mobile Clients
OPC UA (alarms & events)
Generic Information Model
OPC UA Server
OPC UA Clients
Generic Data Model
TAMPERE UNIVERSITY OF TECHNOLOGY

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

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

7. Demo session: Tampere University of Technology
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
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
OPC UA information modeling for declaring data relations and semantics as well as views for different purposes

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

9. Preliminary results from the first test
Change of natural frequency (1050 -> 710 Hz) of a wear plate during a 2 month period 19.4–

10. Demo session: VTT Technical Research Centre of Finland
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

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

12. Thank you!