KREXX Engineering Academy
Practical, industry-focused training designed to help engineers master systems engineering, MBSE, simulation, digital twins, and modern digital engineering methods.
KREXX Engineering Academy
Practical, industry-focused training designed to help engineers master systems engineering, MBSE, simulation, digital twins, and modern digital engineering methods.
WHY IT EXISTS
The Capability Gap Is Structural.
The engineering workforce is facing a structural capability gap. Not a shortage of engineers. A shortage of engineers who can think across system boundaries, apply model-based methods to real programs, validate simulation work with rigour, and integrate AI and digital tools into their actual workflows.
The World Economic Forum Future of Jobs 2025 report projects that a significant share of engineering workers' core skills will require updating by 2030. Traditional training does not close this gap. Academic courses teach theory to people who already have jobs. Vendor training teaches tools without teaching the underlying method.
The KREXX Engineering Academy is built for the working engineer who needs the method to work on monday morning.
HOW IT WORKS-FORMAT
Cohort size
10–20 participants
Program length
8–16 weeks
Format
Online + optional in-person intensive
Instruction
Live sessions, structured problem-solving, capstone
Capstone
Applied to a real problem from your domain
Instructors
Practitioners from real industrial programs
WHY IT EXISTS
Four Structured Programs.
Applied Systems Engineering Fundamentals
Suitable for: Engineers, graduates, and project contributors entering systems roles.
YOU WILL BUILD
- Requirements decomposition and specification
- Interface definition and control
- Operational concepts and use-case models
- State behaviour and system dynamics
- Verification and validation plan
- Introductory SysML model
WHY IT EXISTS
Four Structured Programs.
Applied Systems Engineering Fundamentals
Engineers, graduates, and project contributors entering systems roles.
- Requirements decomposition and specification
- Interface definition and control
- Operational concepts and use-case models
- State behaviour and system dynamics
- Verification and validation plan
- Introductory SysML model
Applied MBSE For Engineering Teams
Teams using MBSE tools but not yet realizing the full engineering value.
- SysML model architecture beyond notation
- End-to-end requirements traceability
- Interface and configuration governance
- Model-to-simulation and test-data links
- Model evolution across programme phases
- MBSE adoption failure diagnosis
Simulation and Digital Twin Program
Engineers building, inheriting, or improving simulation and digital twin programmes.
- First-principles model development workflow
- Model validation against test and operational data
- Digital twin architecture and lifecycle logic
- Data pipeline and signal mapping
- Model update and health-state logic
- Diagnosis of digital twin initiative failures
AI for Engineering Decision
Engineers and teams evaluating AI or ML for technical decision support.
- Engineering use cases where AI is appropriate
- Supervised and unsupervised models for engineering data
- Uncertainty and confidence interpretation
- Model-in-the-loop and hardware-in-the-loop concepts
- AI-assisted engineering workflow prototype
- Governance and documentation for AI-supported decisions
FOR ORGANIZATIONS
Employer-Sponsored Cohorts.
Employer-sponsored cohorts for teams of 10 or more. Your team, your schedule, with case studies and capstone projects drawn from your program types and domain.
Curriculum licensing is available for engineering organizations that want to deliver programs internally through their own training function.
The Academy integrates directly with KREXX consulting engagements under the Build-Operate-Transfer model. When KREXX transfers a system or digital tool to your team, Academy training is what ensures your team can operate and evolve it.
Who KREXX Academy is built for
Four Distinct Groups.
KREXX Academy supports engineers at different career stages,
from graduates entering systems work to project and product leaders responsible for complex technical decisions.
The Graduate
Strong disciplinary foundation, limited industrial systems exposure
PAIN POINTS
- Strong academic knowledge, but limited exposure to real industrial systems
- Difficulty connecting theory to requirements, interfaces, V&V, simulation, and digital twin workflows
- No strong portfolio showing applied systems engineering capability
- Unclear path into systems engineering, integration, or digital engineering roles
WHAT YOU GET
- Applied introduction to systems engineering, MBSE, simulation, and digital thread thinking
- A portfolio-style capstone with real engineering artifacts
- Practical exposure to requirements, architecture, interfaces, V&V, and simulation logic
- A clearer pathway into systems engineering and digital engineering roles
The Engineer
Individual contributor working inside complex technical programmes
PAIN POINTS
- Strong in one discipline, but expected to contribute across system-level decisions
- Tools are available, but the method behind them is unclear
- Requirements, interfaces, simulations, and test evidence feel disconnected
- Career growth is limited by being seen only as a domain specialist
WHAT YOU GET
- Practical proficiency in systems thinking, MBSE, simulation, and traceability
- A structured workflow you can apply to real projects
- Capstone or sprint deliverables that demonstrate applied capability
- Stronger pathway toward senior engineer, systems engineer, or integration roles
The Project Lead
Accountable for delivery, coordination, integration risk, and technical outcomes
PAIN POINTS
- System complexity creates rework, delays, and late integration surprises
- Requirements, interfaces, and verification evidence are spread across teams and tools
- Technical decisions are difficult to defend because assumptions are not traceable
- The team has tools, but no consistent systems engineering operating method
WHAT YOU GET
- MBSE-led workflow for managing requirements, interfaces, risks, and evidence
- Better visibility into integration gaps before they become delivery problems
- Decision-grade artifacts that support technical reviews and stakeholder alignment
- A repeatable method your team can use across future programmes
The Product Lead
Bridging customer needs, market requirements, and engineering execution
PAIN POINTS
- Market needs do not always translate cleanly into engineering requirements
- Product decisions are made without enough visibility into technical constraints and trade-offs
- Engineering, software, data, and operations teams interpret requirements differently
- Product intent is not clearly connected to architecture, validation, and delivery evidence
WHAT YOU GET
- A systems-level method for translating needs into structured requirements and decision criteria
- Better alignment between product goals, engineering architecture, and verification logic
- Trade-study frameworks for comparing technical options
- Stronger communication with engineering teams, customers, and leadership
Ready To Build Future-Ready
Engineering Skills?
We combine consulting, digital engineering, and workforce development into one integrated engineering ecosystem.
