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How to Use PLC Scan-Cycle Highlight to Debug Ladder Logic Faster

A practical guide to using scan-cycle highlight in PLC programming — what it shows you, how to enable slow mode, and how to use it to diagnose timer bugs, rung order problems, and latch coil issues.

PLC Simulation Software8 min read

Professional PLC programmers debug faster than beginners for one reason: they do not guess. They observe the exact state of every bit, every contact, and every coil at the exact moment the logic fails. Scan-cycle highlight is the tool that makes this possible.

This guide explains what scan-cycle highlight shows you and, more importantly, how to use it systematically to find bugs — not just notice them.

PLC scan-cycle highlight used to debug ladder logic faster with slow mode

What Scan-Cycle Highlight Shows You

When the scan-cycle highlight is active, the simulator overlays each rung with live state information as the virtual processor evaluates it:

  • Contact state — each contact is marked TRUE (conducting) or FALSE (blocking), updated to the input image table snapshot taken at the start of this scan
  • Rung result — whether the complete input condition on the rung evaluated to TRUE or FALSE
  • Coil state — whether the output coil was energised (TRUE) or de-energised (FALSE) this scan
  • Timer/counter values — the accumulator and done bit of any timer or counter on the rung

In slow mode, the processor pauses after evaluating each rung and waits for you to advance manually. This gives you unlimited time to inspect the state of every element before the next rung executes.

The highlighter steps through the same four phases the processor runs on every scan, so it helps to know which phase you are watching.

Flowchart of the four PLC scan-cycle phases the highlighter steps through

Logic only runs in the second phase, and outputs only physically change in the third. That ordering is what produces most of the bugs below.

Architecture diagram of the input image table feeding ladder logic and the output image table highlighted during the scan

Because the input image is latched at the very start of the scan and the coil is only written to the output image partway through the logic phase, a coil energises within a single scan like this:

Timing diagram showing how a coil energises within one PLC scan from the latched input image

This is exactly what each highlighted rung is showing you in miniature. A typical seal-in rung — a Start contact, a normally-closed Stop, and a Motor coil — is marked true or false as the processor reaches it:

Ladder rung with Start, normally-closed Stop and Motor coil as highlighted during the scan cycle

Enabling Slow Mode

  1. Open any scenario or curriculum lesson in the simulator
  2. In the toolbar at the top of the editor, click the Scan button (or use the keyboard shortcut Shift+S)
  3. Choose Slow from the mode selector
  4. Click Run — the scan begins and pauses after the first rung
  5. Click Step to advance one rung at a time, or Continue to run to the next scan

The current rung is highlighted in yellow as it executes. After evaluation, it turns green (result TRUE) or stays dimmed (result FALSE).

Case Study 1: Diagnosing a Rung-Order Bug

Symptom: Y0 (motor output) does not respond immediately when X0 (start button) goes TRUE. It activates one scan later.

How to find it with slow mode:

  1. Press start, then step through the scan rung by rung
  2. Find the rung that sets M0 (the seal-in bit): LD X0 → OUT M0
  3. Note which rung number this is — say, rung 7
  4. Now look for the rung that reads M0 to energise Y0: LD M0 → OUT Y0
  5. If the Y0 rung is numbered above (before) the M0 rung — say, rung 3 — then rung 3 runs before rung 7. In the current scan, M0 is still FALSE when rung 3 evaluates it. Y0 only turns on in the next scan.

Fix: Move the M0 consumer rung (Y0 coil) to a rung after the rung that sets M0. Now in the same scan where X0 goes TRUE, M0 is set on rung 7, and rung 8 (the Y0 coil) reads it as TRUE in the same scan.

This is documented in Top 5 PLC Programming Mistakes as Mistake #2.

Case Study 2: Diagnosing a Timer Bug

Symptom: The motor starts 500ms after the start button is pressed instead of 5 seconds.

How to find it with slow mode:

  1. Enable slow mode and step through until you find the timer rung
  2. Watch the timer accumulator value in the overlay — it counts in display units, not real time
  3. Check what units the preset is in: is it K50 (50 × 100ms = 5s) or K50 on a 10ms resolution timer (50 × 10ms = 500ms)?

In Mitsubishi dialect, T0–T199 are 100ms resolution; T200–T255 are 10ms resolution. If you used T200 instead of T0 with K50, your timer runs in 500ms instead of 5 seconds.

Fix: Change the timer device number to the correct resolution range, or recalculate the preset: for a 5-second delay on a 10ms timer, use K500 (500 × 10ms = 5s).

For IEC/AB timers, verify the preset format: T#5S means 5 seconds; T#5000MS also means 5 seconds. But PRE: 5 on a legacy SLC timer means 5 × 10ms = 50ms, not 5 seconds.

Case Study 3: Diagnosing a Latch Coil That Will Not Reset

Symptom: The motor stays running after the stop button is pressed.

How to find it with slow mode:

  1. Step through the scan, looking for the SET/OTL coil that energised the motor
  2. Check if there is a matching RST/OTU rung anywhere in the program
  3. If the RST rung exists, check its input condition: is Stop_PB being evaluated as XIC (normally-open) or XIO (normally-closed)?

A common bug: the stop button is wired normally-closed (NC), so it reads TRUE (24V present) when not pressed. The RST rung has XIC Stop_PB — which reads TRUE all the time the button is not pressed. But when you press the stop button, the circuit opens, the input reads FALSE, and the RST rung becomes FALSE — which means the RST coil de-energises. A de-energised RST coil does not reset; only a TRUE RST coil resets.

Fix: Change XIC Stop_PB to XIO Stop_PB on the reset rung. Now the RST rung is FALSE while the button is not pressed (no reset), and TRUE when the button is pressed (reset fires).

Case Study 4: Finding Which Rung Is Holding a Fault Latch

Symptom: The machine is in fault state and cannot be reset. Operator pressed the fault-reset button; nothing happened.

How to find it with slow mode:

  1. Look for the fault coil in the scan — it should be a latch coil (OTL or SET)
  2. Verify the reset coil (OTU or RST) exists and evaluate its rung condition
  3. Look for any additional interlock contacts that might be holding the fault state

In many programs, a fault can only be reset if: (a) the fault cause has cleared AND (b) the reset button is pressed. If the fault cause is still present (the sensor is still blocked, the pressure is still high), the reset will not work regardless of how many times the operator presses the button. The scan-cycle highlight will show you that the reset rung's input condition is FALSE because of the fault cause contact, not the reset button.

Systematic Debug Protocol

When a machine misbehaves and you cannot see why, use this protocol:

  1. Enable scan-cycle highlight in live mode — observe the output state of the failing element
  2. Find the output coil that should control the failing element — is it TRUE or FALSE?
  3. If coil is FALSE: step upstream. Find the input rung for that coil and look at each contact — which contact is blocking the rung?
  4. Trace that contact's source bit — is it driven by a field device? A timer? A latch coil? Another rung?
  5. If coil is TRUE but output not energised: the problem is outside the PLC program (wiring, output card, field device)

This is the same method field engineers use with connected hardware. The simulator lets you practise it risk-free.

Run through enough scans this way and you start recognising the same handful of problems on sight — these are what scan-cycle highlight trains you to spot:

Checklist of ladder logic problems scan-cycle highlight teaches you to spot

For a deeper dive into the scan cycle itself, read The PLC Scan Cycle Explained. To practise debugging with injected faults, try the fault diagnosis module.

Practise scan-cycle debugging in the simulator — free. Slow mode, step mode, and live highlight available on all plans including Free.

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PLC scan-cycle highlighting guide: implementation, evidence and troubleshooting

Direct answer

PLC scan-cycle highlighting guide becomes useful when it connects runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback with sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback, then proves the learner predicts and then explains the complete trace for repeated scans of a small program 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 pLC learners using animated rung state to understand program execution without mistaking green logic for a complete physical result. The intended result is specific: the reader can relate highlights to current contact truth and power flow, inspect stateful instructions and continue through output, actuator and feedback boundaries.

a PLC scan-cycle bench used to correlate physical inputs, program state, timer or counter execution, output indication and repeated timing evidence while studying interpreting rung highlights, instruction state and machine evidence
The field scene connects interpreting rung highlights, instruction state and machine evidence to declared initial conditions, observable boundaries, safe limits and repeatable acceptance evidence.

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

runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback. For interpreting rung highlights, instruction state and machine evidence, record the initial condition, actor, requested change, observable result and stopping condition before selecting a tool or implementation.

NODE 02observable

Map the evidence path

sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback. 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

the learner predicts and then explains the complete trace for repeated scans of a small program. 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

false branch, parallel path, duplicate output, latched state, timer threshold, counter edge, one-shot, restart and changing feedback. Choose minimum, maximum, simultaneous, delayed or restart conditions that reveal assumptions hidden by the happy path.

NODE 05observable

Diagnose a controlled fault

an input-image, contact-truth, order, branch, instruction-state, output-owner, update or feedback mismatch. 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

the reduced behavior recreated and monitored in the exact target software, task and controller. 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 runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback 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 sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback 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 the learner predicts and then explains the complete trace for repeated scans of a small program 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 false branch, parallel path, duplicate output, latched state, timer threshold, counter edge, one-shot, restart and changing feedback 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 an input-image, contact-truth, order, branch, instruction-state, output-owner, update or feedback mismatch 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 the reduced behavior recreated and monitored in the exact target software, task and controller and repeat the affected regression cases.

    Evidence: A learner completes the surface by explaining the result, passing a changed case and identifying what still requires supervised target-equipment practice.

    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 PLC scan-cycle highlighting guide: implementation, evidence and troubleshooting
Observed symptomInspectInterpretationNext proving action
The expected result is unclearRequirement, initial state, actor, stimulus, units and pass conditionThe learner, instructor and assessor 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 browser platform can retain programs, scenario results, attempts and observable machine state so practice is attached to evidence rather than seat time alone.

Where simulation stops

A browser highlight is an explanation of the learning runtime, not proof of target task scheduling, immediate I/O, firmware behavior or physical equipment state.

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. runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback. For interpreting rung highlights, instruction state and machine evidence, 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 runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback 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 learner, instructor and assessor 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 does a green PLC rung mean? A defensible short answer is: It generally indicates a true evaluated path in the current model; it does not by itself prove the final output, wiring, actuator or process result.

Case 02

predict → observe → prove

Prove map the evidence path

Engineering context. sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback. 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 sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback 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: Why can a highlighted rung change after another rung executes? A defensible short answer is: Programs are evaluated in order, so earlier writes and stateful instructions can affect later logic within the same scan depending on the platform model.

Case 03

predict → observe → prove

Prove prove normal operation

Engineering context. the learner predicts and then explains the complete trace for repeated scans of a small program. 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 the learner predicts and then explains the complete trace for repeated scans of a small program 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 should I learn first about interpreting rung highlights, instruction state and machine evidence? A defensible short answer is: Start with the operating contract and evidence path: runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback, followed by sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback. Add advanced features only after the baseline is predictable.

Case 04

predict → observe → prove

Prove exercise a boundary case

Engineering context. false branch, parallel path, duplicate output, latched state, timer threshold, counter edge, one-shot, restart and changing feedback. 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 false branch, parallel path, duplicate output, latched state, timer threshold, counter edge, one-shot, restart and changing feedback 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: How do I practise interpreting rung highlights, instruction state and machine evidence 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 05

predict → observe → prove

Prove diagnose a controlled fault

Engineering context. an input-image, contact-truth, order, branch, instruction-state, output-owner, update or feedback mismatch. 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 an input-image, contact-truth, order, branch, instruction-state, output-owner, update or feedback mismatch 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: 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 06

predict → observe → prove

Prove transfer and hand over

Engineering context. the reduced behavior recreated and monitored in the exact target software, task and controller. 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 the reduced behavior recreated and monitored in the exact target software, task and controller and repeat the affected regression cases. The acceptance record should show this result: a learner completes the surface by explaining the result, passing a changed case and identifying what still requires supervised target-equipment practice. 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: Why test faults and restart behavior? A defensible short answer is: Because an input-image, contact-truth, order, branch, instruction-state, output-owner, update or feedback mismatch or false branch, parallel path, duplicate output, latched state, timer threshold, counter edge, one-shot, restart and changing feedback can expose assumptions that never appear during ideal startup and steady operation.

Answer surface / 07

Questions people ask about PLC scan-cycle highlighting guide

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 does a green PLC rung mean?

It generally indicates a true evaluated path in the current model; it does not by itself prove the final output, wiring, actuator or process result.

Why can a highlighted rung change after another rung executes?

Programs are evaluated in order, so earlier writes and stateful instructions can affect later logic within the same scan depending on the platform model.

What should I learn first about interpreting rung highlights, instruction state and machine evidence?

Start with the operating contract and evidence path: runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback, followed by sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback. Add advanced features only after the baseline is predictable.

How do I practise interpreting rung highlights, instruction state and machine evidence 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 an input-image, contact-truth, order, branch, instruction-state, output-owner, update or feedback mismatch or false branch, parallel path, duplicate output, latched state, timer threshold, counter edge, one-shot, restart and changing feedback 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.

Continue the signal path / 08

Related practice and reference pages

PLC scan-cycle visualizerContinue from runtime version, dialect, input image, rung order, branch truth, stateful instruction instance, final output owner, update point, machine model and feedback.Scan-cycle highlight featureContinue from sampled inputs through contact truth and ordered instruction execution to highlighted path, output state, modeled action and next-cycle feedback.PLC scan cycle explainedContinue from the learner predicts and then explains the complete trace for repeated scans of a small program.PLC program testingContinue from false branch, parallel path, duplicate output, latched state, timer threshold, counter edge, one-shot, restart and changing feedback.Continue with safety-relay wiring lessonContinue from an input-image, contact-truth, order, branch, instruction-state, output-owner, update or feedback mismatch.Forward-reverse motor PLC scenario field guideContinue from the reduced behavior recreated and monitored in the exact target software, task and controller.