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Survey on functions, competencies and training needs
Role: Predictive Maintenance & Digital-Twin Engineer (Offshore / Shipping)
Sectors: Ocean Renewables · Shipping & Repair
General information
Primary sector
OceanRenewables (offshore wind, wave, tidal)
Shipping& Repair (fleet management, shipyards, dry docks)
Other
Type of organisation
Research Center / Technology or R&D centre
Small Company (<50 employees)
Medium Company (50–250 employees)
Large Company (>250 employees)
Port Authority
Country
Ireland
France
Portugal
Spain
Years of experience
0-2 years
3-5 years
6-10 years
> 10 years
Main functions of the role
Rate each function and indicate whether a competency gap exists in yourorganisation. Rating scale— 1 = Very low · 2 = Low · 3 = Medium · 4 =High · 5 = Very high | Gap: Yes / No
*
Rows
Importance
GAP
Gap description (free text)
Develop digital twin models of
offshore and marine renewable energy assets (wind turbines, wave/tidal devices)
1
2
3
4
5
Yes
No
Implement IoT-based structural
health monitoring (SHM) systems on offshore structures and vessels
1
2
3
4
5
Yes
No
Build and validate predictive
maintenance ML models for marine and offshore equipment
1
2
3
4
5
Yes
No
Analyse time-series sensor
data (vibration, temperature, pressure, strain) for fault detection
1
2
3
4
5
Yes
No
Integrate simulation / CAE
tools (FEA, CFD) with real-time sensor data and digital twin platforms
1
2
3
4
5
Yes
No
Design corrosion, biofouling
and fatigue prediction systems for marine structures
1
2
3
4
5
Yes
No
Develop condition-based and risk-based
maintenance strategies for offshore assets
1
2
3
4
5
Yes
No
Monitor offshore wind turbine
and array performance; detect early fault signatures
1
2
3
4
5
Yes
No
Manage asset lifecycle data,
maintenance records and performance KPIs
1
2
3
4
5
Yes
No
Support Carbon Intensity
Indicator (CII) and EEXI compliance monitoring for shipping assets
1
2
3
4
5
Yes
No
Other functions not listed above:
Technical competencies
Current level . Required future level . Gap. Training need
For each technical competency, indicate your current level, the level you considernecessary in the next 3 years, whether a gap exists and whether you needtraining. Scale — 1 = Beginner · 2 = Basic · 3 = Intermediate · 4 = Advanced · 5 = Expert
*
Rows
Current level (1–5)
Required future level (1–5)
GAP?
Training needed?
Digital twin platforms (Siemens Xcelerator, ANSYS Twin
Builder, Eclipse Ditto, NVIDIA Omniverse)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
IoT / sensor integration — vibration, strain,
temperature, pressure, acoustic emission (MQTT, OPC-UA)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
ML for time-series — anomaly
detection, LSTM, transformer models, survival analysis
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
SCADA systems and OT/IT
integration (Modbus, DNP3, IEC 61850)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
CAE / FEA / CFD tools (ANSYS,
Abaqus, OpenFOAM, SIMPACK)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Structural Health Monitoring
(SHM) — methods, standards and software
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Data engineering for
time-series (InfluxDB, TimescaleDB, Apache Kafka, Spark)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Cloud platforms for industrial
IoT (Azure IoT Hub, AWS IoT, GCP)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Reliability engineering
methods (RCM, FMEA, RBI, Weibull analysis)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Corrosion and fatigue
modelling — fracture mechanics, S-N curves, cathodic protection
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Marine and offshore standards (DNV-RP-0487,
ISO 13374, ISO 55000, Lloyd's ShipRight)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
CII / EEXI / MARPOL compliance
frameworks and monitoring tools
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Condition Monitoring Systems
(CMS) and CMMS integration (SAP PM, Maximo)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
3D point cloud / LiDAR data
processing for offshore inspection
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Cybersecurity for OT/SCADA
systems in maritime environments (IEC 62443, IACS E26/E27)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Additional technical competencies not included
Transversal competencies
ESCO classification · Current level · Required future level · Gap
Rate your level in the key transversal competencies identified in the ESCO frameworkfor this role. Scale — 1 = Beginner · 2 = Basic · 3 = Intermediate · 4 = Advanced · 5 = Expert
*
Rows
Current level (1–5)
Required future level (1–5)
GAP?
Training needed?
Technical communication
(reports, dashboards, briefings for non-specialists)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Interdisciplinary
collaboration (engineers, operators, naval architects, asset owners)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Project and maintenance programme management
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Technical leadership in
data-driven maintenance transformation
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Adaptability to new digital
tools and evolving offshore/shipping regulations
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Innovation and creative
thinking applied to asset integrity management
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Data-driven decision making
for maintenance planning
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Safety, sustainability and
environmental awareness in offshore/shipping operations
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Additional transversal competencies
Technologies and tools
Current use · Training need
Indicate whether you currently use each technology and/or whether you would like to receive training in it.
*
Rows
Currently in use
Would like training
Siemens Xcelerator / Mindsphere (industrial digital
twin)
ANSYS Twin Builder /
Mechanical (simulation and digital twin)
Eclipse Ditto / Apache PLC4X
(open-source IoT and digital twin)
NVIDIA Omniverse (real-time 3D digital twin
visualisation)
OSIsoft PI / AVEVA PI System
(operational data historian)
InfluxDB / TimescaleDB
(time-series database)
Apache Kafka / Spark Streaming
(real-time data pipelines)
Azure IoT Hub / AWS IoT / GCP
IoT Core (cloud IoT platforms)
ANSYS / Abaqus / OpenFOAM (CAE
/ FEA / CFD simulation)
SAP PM / IBM Maximo (CMMS — asset and maintenance
management)
Python (Pandas, Scikit-learn,
TensorFlow for predictive models)
SCADA platforms (Wonderware,
Ignition, WinCC)
DNV Sesam / SACS (offshore
structural analysis)
3D scanning / LiDAR / drone inspection tools
Cybersecurity tools for OT
environments (Claroty, Dragos, Nozomi)
Other relevant technologies or tools you use or consider important for this role
Training needs
Priority . Format . Duration
Adierazi hurrengo 2 urteetan zure garapen profesionalerako prestakuntza-arlo bakoitzarenlehentasuna (1 = lehentasunik gabe · 5 = oso altua / premiazkoa). 1 = Lehentasunik gabe · 2 = Txikia · 3 = Ertaina · 4 = Handia · 5 = Oso altua / Larrialdikoa
*
Rows
1
2
3
4
5
Digital twin development and management for offshore / marine assets
AI / ML for predictive
maintenance and condition monitoring
Structural Health Monitoring
(SHM) — methods, standards and tools
Real-time data pipelines and
time-series data engineering
SCADA / OT / IT integration in
marine and offshore environments
Offshore and marine standards
for digital integrity management (DNV, Lloyd's, ABS)
CII / EEXI / decarbonisation
monitoring for shipping
Reliability engineering (RCM,
FMEA, RBI) applied to offshore assets
Corrosion and fatigue
modelling for marine structures
Cloud platforms and industrial
IoT for offshore applications
Ciberseguridad para IoT y robótica marina (IEC
62443, IACS E26/E27)
Aplicaciones de la Economía Azul: monitoreo de la
acuicultura, automatización portuaria, inspección en alta mar.
Other training needs, accesss barriers (cost, time, language) o comments
Final remarks
Open space — your expertopinion is especially valuable
Specific gaps or barriers inyour sector (Ocean Renewables or Shipping & Repair) not captured in the survey:
Send
Should be Empty: