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OpenPLC vs Paid PLC Software: Honest Comparison

Compare OpenPLC with paid PLC software by runtime, editor, hardware support, simulation, learning workflow and cost to choose the right fit.

PLC Simulation Software9 min read

OpenPLC vs paid alternatives — when each wins

OpenPLC is an open-source IEC 61131-3 runtime created by Thiago Alves and maintained by a community of industrial automation researchers and practitioners. It's genuinely excellent at what it does: executing standard IEC code on cheap hardware (Raspberry Pi, Arduino, ESP32, x86 Linux) with full source-code transparency.

It's also not a complete learning platform on its own. If you're trying to decide between OpenPLC and a paid simulator, the honest answer is: they solve different problems. This post explains which problem is yours.

What OpenPLC actually is

OpenPLC has two main pieces:

  1. OpenPLC Runtime — a soft PLC. Install on a Pi, Arduino, or Linux box. It executes compiled IEC 61131-3 programs (ladder, ST, SFC, FBD, IL) with real scan-cycle semantics.
  2. OpenPLC Editor — the IDE. Desktop application, free, supports the IEC 61131-3 languages, compiles to the runtime.

There's a third piece — OpenPLC Simulator — which is the runtime running in your browser for demonstration purposes. It's modest in scope.

What OpenPLC does not include:

  • Machine physics models (traffic lights, conveyors, tank systems)
  • Automated test cases with grading
  • Interview prep tracks
  • Per-scenario solution programs
  • Portfolio PDF generation
  • Multi-dialect editor (you use IEC only)
  • Cohort management for instructors

Those aren't criticisms. They're scope. OpenPLC is a runtime; curriculum-led simulators are a learning platform.

OpenPLC's biggest strength: deployment

Once your code works in OpenPLC, you can deploy it to a USD 50 Raspberry Pi wired to real sensors and see your ladder control real things. That's the single biggest thing OpenPLC does that browser simulators can't.

If your goal is "I want to automate my home workshop" or "I want to deploy my code on cheap hardware for a hobbyist project," OpenPLC is the answer. No paid simulator deploys to real hardware.

OpenPLC's biggest limitation: no guided curriculum

If you're starting from zero and don't already know ladder logic, OpenPLC won't teach you. There's no sequenced curriculum, no graded scenarios, no "here's what to learn next." You're on your own for structure.

Self-motivated experienced programmers treat this as freedom. Beginners usually treat it as frustration.

OpenPLC vs our paid simulator, head-to-head

OpenPLC vs paid simulators — what each is good at

Reference tableSwipe
DimensionOpenPLCOur Pro plan
CostFreeUSD 249/year
RuntimeReal IEC 61131-3Real IEC 61131-3
DialectsIEC onlyIEC + A-B + Siemens + Delta
Machine scenariosNone (build your own)40 built-in
Graded testsNoneAuto-graded, pass/fail
Solutions visibleN/AYes, per scenario
Interview prepNone6 tracks with certificates
Deploys to hardwareYes, Pi / ArduinoNo
Install requiredYesNo (browser-only)
CurriculumNone18 lessons + 12 quizzes
Portfolio PDFNoYes

OpenPLC wins on deployment and cost. Our simulator wins on everything curriculum-related. They're complementary, not competitive.

The hybrid stack most people should use

The hybrid stack that uses both

Five-step path that combines both tools:

  1. Learn on our simulator. Start with the free tier, move to Basic or Pro if you're serious. Build the ladder-logic and IEC fluency.
  2. Build portfolio with graded tests. Complete a focused scenario set, then use Pro portfolio export for the work you want employers to review.
  3. Deploy code to OpenPLC on a Pi. Install the runtime, compile one of your scenarios' solution programs against it, see it run on real hardware.
  4. Wire the Pi to sensors. Buttons, LEDs, a motor driver, a temperature sensor. The I/O stack is standard GPIO plus some cheap expansion boards.
  5. Show an end-to-end demo. A working physical project driven by your code. Record a video. Paste it into your CV.

Total cost: USD 99–249/year for the simulator + USD 80–150 for a Pi and basic components. Outperforms every vendor classroom on skill-per-dollar.

Who should skip the paid simulator

Who should pick OpenPLC-only

Five scenarios where OpenPLC alone is enough:

  • You already know ladder logic and just want a runtime to deploy code on.
  • You're a hobbyist building home-automation or maker projects.
  • You're at an institution with literally zero software budget, and have an experienced instructor to supply the curriculum.
  • Your end target is Pi / Arduino / ESP32 deployment rather than employment at a traditional plant.
  • You prefer tinkering to structured learning — some people genuinely learn better by debugging OpenPLC than by passing auto-graded tests.

If any two of those are true, OpenPLC alone works. Otherwise, pair it with a structured simulator for the curriculum half.

Who should skip OpenPLC

  • Complete beginners. Without the machine physics and graded tests, OpenPLC is an empty room with an excellent PA system. Not useful until you know the concepts.
  • People targeting employment in traditional plants. The paid route (simulator + vendor classroom later) is faster.
  • Cohorts that need admin tracking. OpenPLC has no teacher dashboard.

Other open-source alternatives

  • Beremiz — the predecessor to OpenPLC's editor. Still maintained independently. Solid for serious open-source work.
  • MatIEC — the IEC 61131-3 compiler that OpenPLC uses under the hood. Library, not an IDE.
  • Mosaic (CDX Automation) — commercial but with a free community edition. Less polished than OpenPLC.

None of these are better choices than OpenPLC for most use cases. Stick with OpenPLC as the open-source reference.

How serious is the OpenPLC community

Active, international, and professional. The project is used in research papers, industrial cybersecurity tooling, and small-scale commercial deployments. The book "Introduction to Programmable Logic Controllers" and several university courses reference OpenPLC. If you contribute meaningful code, it's a resume line.

FAQ

Is OpenPLC really free?

Yes. Apache 2.0 licence. Commercial use permitted. No hidden tiers.

Is OpenPLC as good as a commercial PLC runtime?

For learning and hobbyist use: yes. For production deployments in safety-critical or regulated industries: not certified, so no. Use commercial runtimes there.

Can OpenPLC replace Codesys?

Not directly. Codesys is a mature ecosystem with vendor partnerships (WAGO, Beckhoff) that ship Codesys-based hardware. OpenPLC is a runtime you deploy to commodity hardware. Different markets.

Does OpenPLC support Allen-Bradley or Siemens syntax?

No. OpenPLC is strictly IEC 61131-3. For A-B or Siemens syntax practice, use our dialect toggle.

Can I run a business on OpenPLC?

Technically yes. Practically, you'll want commercial support contracts for any real deployment — which OpenPLC doesn't directly sell, though consultants in the ecosystem do.

Where to start

  1. If you're new to PLCs: run the guided first program, then use the free tier and finish two beginner scenarios before comparing larger toolchains.
  2. If you're already fluent: install OpenPLC Editor and OpenPLC Runtime on a Pi. Compile the solution program from one of our scenarios. Deploy. Celebrate.
  3. Either way: combine the two. The simulator for curriculum, OpenPLC for deployment.

The two tools make each other more useful. Pick the entry point that matches your current level.

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Software evaluation field guide

OpenPLC versus paid PLC software: implementation, evidence and troubleshooting

Direct answer

OpenPLC versus paid PLC software becomes useful when it connects whether the requirement is iec learning, low-cost deployment, machine simulation, vendor hardware or structured assessment with editor, compiler, runtime, target hardware, i/o, protocol, curriculum, support and licence responsibilities, then proves one iec program compiled or executed with equivalent acceptance behavior under normal, boundary, fault and recovery conditions. The objective is a repeatable engineering or learning result, not merely activity inside a page or tool.

This guide is written for learners, makers, educators and controls teams deciding between an open runtime, a guided simulator and a commercial vendor toolchain. The intended result is specific: the evaluator can separate runtime deployment, engineering workflow, machine simulation, curriculum, target support and commercial responsibility before choosing.

System map / 02

Six concepts that control the result

Treat these as connected checkpoints. Each checkpoint has an expected state, an observable state and a boundary to the next part of the system. That structure prevents a software indication from being mistaken for physical proof.

NODE 01observable

Define the operating contract

whether the requirement is IEC learning, low-cost deployment, machine simulation, vendor hardware or structured assessment. For OpenPLC and commercial PLC software, record the initial condition, actor, requested change, observable result and stopping condition before selecting a tool or implementation.

NODE 02observable

Map the evidence path

editor, compiler, runtime, target hardware, I/O, protocol, curriculum, support and licence responsibilities. Separate request, internal state, output or service, physical or user-visible result and independent feedback so each boundary can be inspected.

NODE 03observable

Prove normal operation

one IEC program compiled or executed with equivalent acceptance behavior. Run more than one cycle from a known state and retain the values, timings or artifacts that demonstrate repeatability.

NODE 04observable

Exercise a boundary case

library, device, operating-system, maintenance, security, documentation and deployment limits. Choose minimum, maximum, simultaneous, delayed or restart conditions that reveal assumptions hidden by the happy path.

NODE 05observable

Diagnose a controlled fault

a compile, target, I/O, runtime or support gap revealed by the representative case. Preserve the first symptom, divide the system at a measurable boundary and change one condition only after predicting the result.

NODE 06observable

Transfer and hand over

a hybrid or single-tool decision recorded with owner, evidence, total cost and production validation. Restore normal state, remove temporary changes, repeat affected checks and document which claims remain limited to the learning environment.

Procedure / 03

A six-step practice and commissioning workflow

Run the steps in order the first time. Later, the same structure becomes a diagnostic loop: define the expected condition, observe the boundary, interpret the difference and choose one proving action.

  1. 01

    Write the acceptance case

    Convert whether the requirement is iec learning, low-cost deployment, machine simulation, vendor hardware or structured assessment into initial conditions, one stimulus and observable pass criteria.

    Evidence: Another person can repeat the case without guessing the intended result.

    Avoid: Using page completion or an animation as the acceptance criterion.

  2. 02

    Build the map

    Document editor, compiler, runtime, target hardware, i/o, protocol, curriculum, support and licence responsibilities and name who owns each state or decision.

    Evidence: Every request and result has a source, destination and useful inspection point.

    Avoid: Using the same value as command, status and independent feedback.

  3. 03

    Run the baseline

    Apply one iec program compiled or executed with equivalent acceptance behavior from a clean start and record the expected evidence.

    Evidence: Repeated runs produce the same bounded result.

    Avoid: Changing several parameters before a baseline exists.

  4. 04

    Challenge assumptions

    Test library, device, operating-system, maintenance, security, documentation and deployment limits without changing the acceptance contract.

    Evidence: Limits, timing and restart behavior reach defined states.

    Avoid: Testing only one ideal sequence.

  5. 05

    Isolate one failure

    Introduce or analyse a compile, target, i/o, runtime or support gap revealed by the representative case and locate the first disagreement.

    Evidence: The proving action distinguishes the leading hypotheses.

    Avoid: Resetting, forcing or replacing before evidence is retained.

  6. 06

    Close the evidence loop

    Complete a hybrid or single-tool decision recorded with owner, evidence, total cost and production validation and repeat the affected regression cases.

    Evidence: An evaluation is complete when the same representative job is tested in each candidate and differences are recorded as evidence rather than inferred from feature labels.

    Avoid: Treating an acknowledged message or one successful rerun as handover.

Diagnostic matrix / 04

Symptoms, proving points and next actions

The table is a reasoning aid, not a parts-replacement chart. Preserve the initial symptom, inspect the named boundary and use the interpretation to choose the next controlled test. Site safety procedures and equipment manuals remain authoritative.

Diagnostic symptoms, inspection points, interpretations and next actions for OpenPLC versus paid PLC software: implementation, evidence and troubleshooting
Observed symptomInspectInterpretationNext proving action
The expected result is unclearRequirement, initial state, actor, stimulus, units and pass conditionThe evaluator, instructor and technical buyer may be solving different versions of the task.Rewrite one observable acceptance case before continuing.
Internal state changes but the outcome does notRequest, final owner, output or service boundary and independent feedbackA software or interface indication proves intent at one layer, not the complete outcome.Trace the first boundary after the changing state.
Normal case passes but an edge case failsLimits, timing, simultaneous events, reset and restart assumptionsThe implementation contains a hidden assumption exposed by the changed condition.Add the failed boundary as a permanent regression case.
The failure disappears after resetOriginal symptom, histories, diagnostics, timestamps and active causeReset changed evidence or state without proving the initiating cause.Reproduce under a controlled condition and preserve pre/post-event data.
Simulator and target disagreeModel boundary, software version, task timing, I/O behavior, data types and configurationA learning model and the intended target do not share one of the recorded assumptions.Reduce the case and verify against current target documentation.
The result cannot be explainedPrediction, observation, proving action, alternative hypotheses and limitationsActivity occurred but the evidence is not yet transferable or reviewable.Have the learner defend the signal path and repeat a changed case.

Product evidence / 05

What the browser practice can actually demonstrate

The public product surface exposes runnable examples, capability boundaries, pricing context and test-harness behavior that can be checked before a purchasing decision.

Where simulation stops

Open-source and commercial capabilities change. Verify current releases, licences, supported hardware and safety or production requirements with primary sources.

Commissioning notebook / 06

Six cases that turn the concepts into evidence

Use these as written briefs rather than click-through instructions. For every case, state the expected condition before acting, retain the first useful observation and explain why the final result proves the requirement. A different program or component choice can still be correct when it produces the same bounded behavior and evidence.

Case 01

predict → observe → prove

Prove define the operating contract

Engineering context. whether the requirement is IEC learning, low-cost deployment, machine simulation, vendor hardware or structured assessment. For OpenPLC and commercial PLC software, record the initial condition, actor, requested change, observable result and stopping condition before selecting a tool or implementation. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.

Controlled setup. Use the “Write the acceptance case” stage of the workflow: convert whether the requirement is iec learning, low-cost deployment, machine simulation, vendor hardware or structured assessment into initial conditions, one stimulus and observable pass criteria. The acceptance record should show this result: another person can repeat the case without guessing the intended result. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.

Fault challenge. Introduce or analyse “The expected result is unclear” as one bounded deviation. Inspect requirement, initial state, actor, stimulus, units and pass condition The working interpretation is that the evaluator, instructor and technical buyer may be solving different versions of the task. The next proving action is to rewrite one observable acceptance case before continuing. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.

Review and recovery. The most common trap here is using page completion or an animation as the acceptance criterion. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.

Explain it aloud: What should I learn first about OpenPLC and commercial PLC software? A defensible short answer is: Start with the operating contract and evidence path: whether the requirement is iec learning, low-cost deployment, machine simulation, vendor hardware or structured assessment, followed by editor, compiler, runtime, target hardware, i/o, protocol, curriculum, support and licence responsibilities. Add advanced features only after the baseline is predictable.

Case 02

predict → observe → prove

Prove map the evidence path

Engineering context. editor, compiler, runtime, target hardware, I/O, protocol, curriculum, support and licence responsibilities. Separate request, internal state, output or service, physical or user-visible result and independent feedback so each boundary can be inspected. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.

Controlled setup. Use the “Build the map” stage of the workflow: document editor, compiler, runtime, target hardware, i/o, protocol, curriculum, support and licence responsibilities and name who owns each state or decision. The acceptance record should show this result: every request and result has a source, destination and useful inspection point. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.

Fault challenge. Introduce or analyse “Internal state changes but the outcome does not” as one bounded deviation. Inspect request, final owner, output or service boundary and independent feedback The working interpretation is that a software or interface indication proves intent at one layer, not the complete outcome. The next proving action is to trace the first boundary after the changing state. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.

Review and recovery. The most common trap here is using the same value as command, status and independent feedback. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.

Explain it aloud: How do I practise OpenPLC and commercial PLC software effectively? A defensible short answer is: Use short cases with known initial conditions, a written prediction, one action and an observable result. Then alter a boundary or fault and explain why the evidence changed.

Case 03

predict → observe → prove

Prove prove normal operation

Engineering context. one IEC program compiled or executed with equivalent acceptance behavior. Run more than one cycle from a known state and retain the values, timings or artifacts that demonstrate repeatability. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.

Controlled setup. Use the “Run the baseline” stage of the workflow: apply one iec program compiled or executed with equivalent acceptance behavior from a clean start and record the expected evidence. The acceptance record should show this result: repeated runs produce the same bounded result. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.

Fault challenge. Introduce or analyse “Normal case passes but an edge case fails” as one bounded deviation. Inspect limits, timing, simultaneous events, reset and restart assumptions The working interpretation is that the implementation contains a hidden assumption exposed by the changed condition. The next proving action is to add the failed boundary as a permanent regression case. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.

Review and recovery. The most common trap here is changing several parameters before a baseline exists. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.

Explain it aloud: What counts as proof of competence? A defensible short answer is: A repeatable artifact or system result plus an explanation of the signal path is stronger than time spent, screenshots or a copied answer. Physical competence requires separate supervised evidence.

Case 04

predict → observe → prove

Prove exercise a boundary case

Engineering context. library, device, operating-system, maintenance, security, documentation and deployment limits. Choose minimum, maximum, simultaneous, delayed or restart conditions that reveal assumptions hidden by the happy path. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.

Controlled setup. Use the “Challenge assumptions” stage of the workflow: test library, device, operating-system, maintenance, security, documentation and deployment limits without changing the acceptance contract. The acceptance record should show this result: limits, timing and restart behavior reach defined states. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.

Fault challenge. Introduce or analyse “The failure disappears after reset” as one bounded deviation. Inspect original symptom, histories, diagnostics, timestamps and active cause The working interpretation is that reset changed evidence or state without proving the initiating cause. The next proving action is to reproduce under a controlled condition and preserve pre/post-event data. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.

Review and recovery. The most common trap here is testing only one ideal sequence. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.

Explain it aloud: Why test faults and restart behavior? A defensible short answer is: Because a compile, target, i/o, runtime or support gap revealed by the representative case or library, device, operating-system, maintenance, security, documentation and deployment limits can expose assumptions that never appear during ideal startup and steady operation.

Case 05

predict → observe → prove

Prove diagnose a controlled fault

Engineering context. a compile, target, I/O, runtime or support gap revealed by the representative case. Preserve the first symptom, divide the system at a measurable boundary and change one condition only after predicting the result. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.

Controlled setup. Use the “Isolate one failure” stage of the workflow: introduce or analyse a compile, target, i/o, runtime or support gap revealed by the representative case and locate the first disagreement. The acceptance record should show this result: the proving action distinguishes the leading hypotheses. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.

Fault challenge. Introduce or analyse “Simulator and target disagree” as one bounded deviation. Inspect model boundary, software version, task timing, I/O behavior, data types and configuration The working interpretation is that a learning model and the intended target do not share one of the recorded assumptions. The next proving action is to reduce the case and verify against current target documentation. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.

Review and recovery. The most common trap here is resetting, forcing or replacing before evidence is retained. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.

Explain it aloud: Can browser practice replace official software or hardware? A defensible short answer is: No. It can build concepts and diagnostic reasoning. Exact firmware, I/O electrical behavior, networking, safety and commissioning require current official tools, documentation and target equipment.

Case 06

predict → observe → prove

Prove transfer and hand over

Engineering context. a hybrid or single-tool decision recorded with owner, evidence, total cost and production validation. Restore normal state, remove temporary changes, repeat affected checks and document which claims remain limited to the learning environment. Begin with a written normal condition and identify which request, state, physical result or communication value will provide independent confirmation. Do not begin by changing the configuration; the initial state is part of the evidence and should remain reproducible.

Controlled setup. Use the “Close the evidence loop” stage of the workflow: complete a hybrid or single-tool decision recorded with owner, evidence, total cost and production validation and repeat the affected regression cases. The acceptance record should show this result: an evaluation is complete when the same representative job is tested in each candidate and differences are recorded as evidence rather than inferred from feature labels. Record initial conditions, the exact stimulus and the observation point so another learner can repeat the case without relying on your memory.

Fault challenge. Introduce or analyse “The result cannot be explained” as one bounded deviation. Inspect prediction, observation, proving action, alternative hypotheses and limitations The working interpretation is that activity occurred but the evidence is not yet transferable or reviewable. The next proving action is to have the learner defend the signal path and repeat a changed case. Change only one condition before observing the result, and preserve timestamps or measurements where timing matters.

Review and recovery. The most common trap here is treating an acknowledged message or one successful rerun as handover. After restoring the cause, repeat the normal case and at least one stop, timeout, disconnect or restart boundary relevant to this topic. Remove temporary forces and bypasses, return the model to a known state and retain the evidence that both operation and recovery are deliberate.

Explain it aloud: How should progress be documented? A defensible short answer is: Keep the requirement, initial state, program or configuration, observed values, fault hypothesis, proving action, recovery result and a concise limitations statement.

Answer surface / 07

Questions people ask about OpenPLC versus paid PLC software

These concise answers define the operating, training and product boundaries most often missed in broad summaries. The full workflow and diagnostic table above provide the evidence behind them.

What should I learn first about OpenPLC and commercial PLC software?

Start with the operating contract and evidence path: whether the requirement is iec learning, low-cost deployment, machine simulation, vendor hardware or structured assessment, followed by editor, compiler, runtime, target hardware, i/o, protocol, curriculum, support and licence responsibilities. Add advanced features only after the baseline is predictable.

How do I practise OpenPLC and commercial PLC software effectively?

Use short cases with known initial conditions, a written prediction, one action and an observable result. Then alter a boundary or fault and explain why the evidence changed.

What counts as proof of competence?

A repeatable artifact or system result plus an explanation of the signal path is stronger than time spent, screenshots or a copied answer. Physical competence requires separate supervised evidence.

Why test faults and restart behavior?

Because a compile, target, i/o, runtime or support gap revealed by the representative case or library, device, operating-system, maintenance, security, documentation and deployment limits can expose assumptions that never appear during ideal startup and steady operation.

Can browser practice replace official software or hardware?

No. It can build concepts and diagnostic reasoning. Exact firmware, I/O electrical behavior, networking, safety and commissioning require current official tools, documentation and target equipment.

How should progress be documented?

Keep the requirement, initial state, program or configuration, observed values, fault hypothesis, proving action, recovery result and a concise limitations statement.

What should I do when the answer differs from a guide?

Check assumptions, version, units and initial state first. Reduce the case, compare one boundary at a time and prefer current primary documentation for target-specific behavior.

When is a OpenPLC and commercial PLC software exercise finished?

An evaluation is complete when the same representative job is tested in each candidate and differences are recorded as evidence rather than inferred from feature labels.