I probably don't need to see the other VI's.
The problem with this one is that every time it is called (and putting data into the graphs) it is resetting the the X scale range, and setting a new time offset. You should really only be setting the offset once at the very beginning, and perhaps the x scale range once per day.
I'm not sure you really want to be using a waveform chart.
A waveform chart is designed for data that is equally spaced, and you feed it one or more points at a time and it holds a history of the data it previously received. Two key properties of the graph are the offset (point in time which the zeroth point is) and the scaling (time between data points.) If your data isn't coming in at precisely the same interval, (let's say every 3.1 seconds when your scaling is set for 3, or a point that is a few seconds late for some reason) your new data won't be at the time the chart thinks it is. Couple that with a offset that is constantly getting updated every time it is called. Zero point is now and the offset is now. Okay. next point is 3 seconds later. You reset the offset to now. So the zeroth point looks like now (3 seconds after you really got it) and the next point (the one you just got) looks like it is 3 seconds from now.
A waveform graph is like a chart, equally spaced data, but it doesn't maintain a history. You feed it all the data at once and it clears itself everytime you write new data to it. For point by point applications, you need to maintain your own buffer of data.
I think you really want an XY graph. It is the most flexible. The X points don't have to be equally spaced. It doesn't have a history, so you'll have to create your own by building arrays with new data or using the Build XY graph express VI. Here, every point that comes in, you store an X value (the time) and the Y value (the data). You should only need to set the Xscale range once, or perhaps once per day. Look up all 3 types of charts/graphs in LabVIEW help. Especially the XY graph as it as several different ways of building the data in arrays or clusters for different situations.
