Digital Twin Engineer (Manufacturing Simulation)
Position summary
The Manufacturing Digital Twin Engineer will own and develop the plant-level Digital Twin for an IATF-certified automotive manufacturing facility (~375 employees) specializing in Heavy Duty and Industrial Air and Liquid Filtration. This role will build the plant’s Digital Twin capability from the ground up—leveraging AutoCAD and FlexSim—to model end-to-end production and logistics, run mixed-method simulations, and deliver data-driven recommendations that improve throughput, robustness, and investment decisions. The site will serve as a global lighthouse, establishing scalable methods and reusable standards for future deployments.
Reporting & work conditions
- Reports to: Senior Manager, Manufacturing Engineering
- Work location: 100% onsite (day shift)
- Travel: Occasional global travel to support other sites (initial focus is single plant)
Key responsibilities
1) Plant-level ownership of the Digital Twin
- Serve as the single point of accountability for the plant Digital Twin within AutoCAD and FlexSim environments.
- Establish and maintain a governed model structure (assets, routing, constraints, assumptions, and versioning) to ensure consistency and usability.
- Ensure the Digital Twin remains aligned with real production conditions, including high-mix/low-volume realities and operational constraints.
2) Model maintenance & continuous update (daily/weekly cadence)
- Maintain and continuously update simulation and system models reflecting:
- Production flows, routings, and process steps (end-to-end)
- Capacities, cycle times, changeovers, uptime/downtime assumptions
- Labor/shift patterns (as applicable), buffers/WIP rules, and constraints
- Internal logistics and material movement (warehouse, supermarkets, tugger/forklift routes, replenishment logic)
- Partner with stakeholders to validate assumptions and keep models current using MES and SAP inputs.
3) Simulation, optimization & scenario analysis (mixed methods)
- Develop and execute simulation scenarios to evaluate:
- Bottlenecks and constraint behavior
- Line balancing and rate changes
- Buffer sizing/WIP strategies and material flow improvements
- Staffing concepts and operational policies
- Investment and expansion scenarios (new lines, automation, warehouse redesign)
- Apply both scenario comparison and optimization approaches (e.g., DOE/parameter sweeps, heuristic optimization, structured experimentation) to quantify tradeoffs and risks.
4) Use case development & continuous improvement enablement
- Identify and develop new Digital Twin use cases in collaboration with:
- Manufacturing Engineering
- Supply Chain
- Continuous Improvement / Lean
- Translate operational problems into simulation questions, define inputs/outputs, and build repeatable analysis templates.
5) Decision support for operations & engineering
- Provide data-based insights and simulation-driven recommendations to support:
- Capex justification and investment prioritization
- Process improvements and throughput increase
- Robustness improvements (sensitivity to mix, downtime, variability)
- Communicate results clearly to plant leadership and cross-functional teams using structured outputs (assumptions, scenarios, findings, recommendations).
6) Support to layout & engineering projects (simulation validation)
- Support layout and engineering projects through simulation-based validation and scenario comparison (e.g., alternative layouts, logistics concepts, capacity changes)
- Collaborate closely with engineering teams while maintaining focus on Digital Twin ownership and simulation integrity
7) Collaboration with Global Digital Twin Lead (scalability)
- Closely collaborate with the Global Digital Twin Program Lead to align standards, methodologies, and best practices
- Package learnings into reusable approaches (templates, modeling conventions, scenario libraries) to enable scalability across global plants
Required qualifications (must-have)
- 3–5 years of experience in manufacturing engineering, industrial engineering, simulation engineering, or related roles in a manufacturing environment
Hands-on experience with
- FlexSim (or comparable discrete-event simulation tool) and building reusable model components (required
- AutoCAD (plant layouts, manufacturing/industrial context
- Discrete-event simulation (required)
- Manufacturing systems understanding (flows, constraints, variability, bottlenecks)
- Ability to build credible models from ambiguous inputs and validate them with stakeholders
- Strong analytical and communication skills—able to explain assumptions, results, and recommendations to non-simulation audiences
- English proficiency (written and verbal)
Preferred qualifications (nice-to-have)
- Experience modeling high-mix/low-volume manufacturing and internal logistics
- Familiarity working with MES and SAP data for operational analysis
- Exposure to optimization methods (DOE, parameter sweeps, heuristic optimization) and basic scripting/data analysis (e.g., SQL/Python/Power BI)
- Experience with SolidWorks to model and simulate internal equipment mechanisms (motion, kinematics, interferences) to support cycle-time analysis, process optimization, and enhanced Digital Twin accuracy
Key interface
- Primary: Manufacturing Engineering, Supply Chain, Continuous Improvement
- Frequent collaboration: Production/Operations, Quality, Maintenance, Finance/Controlling (as needed for scenarios and capex cases
- Global: Global Digital Twin Program Lead (standards, reuse, scalability
What success looks like (6–12 months)
- Digital Twin foundation: End-to-end plant + logistics baseline model established, documented assumptions, and repeatable update process
- Model credibility: Model outputs validated with stakeholders using MES/SAP-informed inputs; trusted for decision support
- Scenario throughput: Regular scenario execution cadence supporting active projects (new line/automation/expansion/warehouse
- Business impact: Clear recommendations that influence capex, staffing, line rates, buffer sizing, and material flow decisions
- Lighthouse scalability: Reusable templates/standards created and shared with the global program for replication at other sites
