When our simulator fits
You need browser-based PLC and HMI learning, dynamic machine feedback, reusable 3D factory components, faults and objective scenario grading.
Category map
Match each tool to the question it can answer
| Software category | Primary decision | Model underneath | Best fit |
|---|---|---|---|
| Discrete-event flow | Capacity, queues, buffers, labor and throughput | Statistical events and resources | Factory planning before controls detail |
| PLC and machine simulation | Sequence, interlocks, I/O, alarms and recovery | Scan-based controller plus dynamic equipment | Controls learning and machine behavior |
| Virtual commissioning | Will production PLC/HMI/robot interfaces work before site? | High-fidelity controller and equipment interfaces | Engineering acceptance and integration |
| Process simulation | How do mass, energy, fluids or chemistry behave? | Equations, balances and physical properties | Process design and operating studies |
| Robot-cell simulation | Reach, collisions, cycle time and offline programs | Kinematics, tooling and robot controllers | Robotic cell engineering |
| Operator training simulator | Can operators recognize and recover from plant conditions? | Process dynamics plus operational interfaces | Procedure and abnormal-situation practice |
A defensible selection process
Write acceptance criteria before shortlisting vendors. The right evidence differs across training, planning and production engineering.
- 01
Define the decision
Name the decision, owner, date and cost of being wrong.
- 02
Set the fidelity boundary
List which physical, controller, timing and human behaviors must be represented.
- 03
Specify interfaces
Identify PLCs, HMI, robots, data sources, CAD and reporting that truly need integration.
- 04
Run a representative pilot
Use one real sequence, fault or planning problem—not the vendor’s polished demo.
- 05
Measure evidence
Compare setup time, model validity, repeatability, learner or engineering outcomes and total cost.
- 06
Plan model ownership
Decide who maintains logic, assets, licenses and validation after the first project.
When it does not
Use specialist DES, CFD/process, robot offline-programming or commissioning software when the production decision requires those engineering models.
A practical hybrid
Teach sequences and diagnosis here, then expose advanced learners to the production engineering tools used by their employer or discipline.
Evaluation questions worth asking every supplier
- Can the model reproduce the decision-critical failure states?
- Which behaviors are physical, emulated, scripted or visual only?
- How are model assumptions documented and validated?
- Can our team create and maintain scenarios without vendor services?
- What is included in licensing, deployment and content ownership?
- Which outcome proves the pilot succeeded?
