Learn how to develop, deploy, and operationalise digital twin models for physical assets, enabling predictive maintenance, optimisation, and remote monitoring across energy infrastructure.
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About this programme
Learn how to develop, deploy, and operationalise digital twin models for physical assets, enabling predictive maintenance, optimisation, and remote monitoring across energy infrastructure.
Equip professionals with the knowledge, skills, and frameworks required to excel in Digital Twin Technology - Applications in Energy & Engineering, driving measurable improvement in Engineering & Technical performance and delivering tangible value to their organisations.
11 key learning outcomes
Apply engineering standards and codes relevant to Digital Engineering in the oil, gas, and energy sectors
Analyse failure modes, root causes, and risk profiles for critical equipment and systems
Design or evaluate engineering solutions that meet functional, safety, and regulatory requirements
Interpret technical data, inspection findings, and performance metrics to support informed decisions
Apply integrity management principles to assess and extend the safe operating life of assets
Utilise industry codes (API, ASME, ISO, NACE) applicable to Digital Engineering disciplines
Develop inspection and maintenance strategies based on risk-based methodologies
Assess the impact of material selection, operating conditions, and degradation mechanisms on asset life
Communicate engineering findings and recommendations to technical and non-technical stakeholders
Apply lessons learned from industry incidents to improve engineering design and operational practices
Integrate HSE considerations into engineering decisions throughout the asset lifecycle
3 training days · 9 modules · hands-on workshops
Establish the core chemical engineering principles and equipment types used in oil and gas processing.
Process mass balance exercise: groups complete a steady-state mass balance around a three-phase separator and gas compression train to verify stream compositions and flow rates.
Apply systematic methods to optimise plant performance and resolve process upsets.
Process troubleshooting case study: given a set of plant data showing off-spec product and production shortfall, teams diagnose the root cause and propose corrective actions.
Apply P&ID standards, simulation tools, and digital process engineering concepts.
Process design review: teams evaluate a provided preliminary P&ID and process simulation model, identify operability and safety issues, and present a structured design review report.
This programme is designed for professionals across these roles
Engineers responsible for equipment design, selection, and performance management
Professionals managing inspection programmes, FFS assessments, and regulatory compliance
Supervisors planning and executing maintenance activities on critical process equipment
Field operations staff responsible for day-to-day plant running and first-line fault response
Safety professionals requiring engineering depth for risk assessment and incident investigation
Early-career engineers building technical competency in their chosen engineering discipline
Upcoming public dates — enrol anytime
This course carries internationally recognised professional credits
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