diff --git a/CHANGELOG.md b/CHANGELOG.md
index 239b7f5e..e1fa07af 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -32,7 +32,7 @@ All notable changes to this project will be documented in this file.
    * [Full changelog: 1.4.1...1.5.0](https://github.com/ni/nidaqmx-python/compare/1.4.1...1.5.0)
 
 * ### Resolved Issues
-    * ...
+    * [936: New example voltage_acq_int_clk_plot_wfm.py does not behave as expected](https://github.com/ni/nidaqmx-python/issues/936)
 
 * ### Major Changes
    * ...
diff --git a/examples/analog_in/voltage_acq_int_clk_plot_wfm.py b/examples/analog_in/voltage_acq_int_clk_plot_wfm.py
index a87c6fc4..8874e628 100644
--- a/examples/analog_in/voltage_acq_int_clk_plot_wfm.py
+++ b/examples/analog_in/voltage_acq_int_clk_plot_wfm.py
@@ -6,22 +6,41 @@
 """
 
 import matplotlib.pyplot as plot
+import numpy as np
 
 import nidaqmx
 from nidaqmx.constants import READ_ALL_AVAILABLE, AcquisitionType
 
+
+def plot_analog_waveform(waveform, min_start_time=None):
+    """Plot a single analog waveform."""
+    # For multiplexed devices, each channel has a different time offset, based on the AI Convert
+    # Clock rate. Calculate the time offset for this channel by subtracting the minimum start time.
+    time_offset = 0.0
+    if min_start_time is not None:
+        time_offset = (waveform.timing.start_time - min_start_time).total_seconds()
+    duration = waveform.sample_count * waveform.timing.sample_interval.total_seconds()
+    time_data = np.linspace(
+        time_offset, time_offset + duration, waveform.sample_count, endpoint=False
+    )
+    plot.plot(time_data, waveform.scaled_data, label=waveform.channel_name)
+
+
 with nidaqmx.Task() as task:
     task.ai_channels.add_ai_voltage_chan("Dev1/ai0")
     task.timing.cfg_samp_clk_timing(1000.0, sample_mode=AcquisitionType.FINITE, samps_per_chan=50)
 
-    waveform = task.read_waveform(READ_ALL_AVAILABLE)
+    waveforms = task.read_waveform(READ_ALL_AVAILABLE)
+    if not isinstance(waveforms, list):
+        waveforms = [waveforms]
 
-    timestamps = list(waveform.timing.get_timestamps(0, waveform.sample_count))
-    time_offsets = [(ts - timestamps[0]).total_seconds() for ts in timestamps]
-    plot.plot(time_offsets, waveform.scaled_data)
+    min_start_time = min(waveform.timing.start_time for waveform in waveforms)
+    for waveform in waveforms:
+        plot_analog_waveform(waveform, min_start_time)
     plot.xlabel("Seconds")
-    plot.ylabel(waveform.units)
-    plot.title(waveform.channel_name)
+    plot.ylabel(waveforms[0].units)  # assume all channels have the same units
+    plot.title("Waveforms")
+    plot.legend()
     plot.grid(True)
 
     plot.show()