If I'm understanding what you want... Trapezoidal integration will probably be easiest and here's a first pass at a solution that I came up with. I'll note that I'm assuming Value is rate in seconds since that's the units of _time, you'll need a conversion if it's a rate for a different time unit.
sensor | table _time Value | reverse
| streamstats last(Value) as lastValue last(_time) as lastTime current=f window=1
| eval area=(_time - lastTime)*(Value+lastValue)/2
| streamstats sum(area) as total
| timechart span=5m max(total) as total
First line is your search, we use table to remove all of the fields other than Value and _time as we need no others (we could use fields which would be able to be distributed and would be faster, but at the cost of a more verbose search here), and we reverse the results to be oldest to newest.
On the second line, we use streamstats to gather the point immediately previous to the current point.
Using this data on the third line we can now calculate the area of each trapezoid to get the estimated number produced in between each sensor sampling.
Now that we have the areas, we can use streamstats again (4th line) to sum the areas to get the running total of how many produced during our time period and finally we use timechart to make a regular graph of rates.
