I made a number of assumptions to make this analysis. These assumptions were:

- Science pack assemblers are adequately supplied.
- Science pack assemblers are efficiently loaded and unloaded.
- Laboratories are efficiently loaded.
- The transportation of the packs to the labs is relatively short.
- Research is constantly being done without significant gaps between topics.
- Modules are not being used.

The first sheet of the workbook contains a table of research topics and their costs, research times, and number of cycles needed. It also contains a table of total research packs needed per topic (as well as a total of each type of pack on the top row) as well as a table of packs per second per lab for each topic (with the maximums on the top row). The last table is total time in seconds to research a topic with either five or ten labs. The "Weighting" column was placed in anticipation of needing to tone down the effects of outliers, but was not used.

The sheet is hard coded in many places assuming that the player is using either five or ten laboratories at any one time. This was done because it seemed to be the general consensus that they are the "correct" numbers of labs to have.

The second sheet has the production analysis. While the maximum packs per second per lab on the previous sheet was interesting, it is complicated by the fact that there are some large outliers and also by the different production speeds of different assemblers. The bottom table compiles a calculated number of assemblers needed for each type of assembler, subdivided by the number of laboratories, and then subdivided again for each science pack type. The results were then sorted from high to low with the bias going Purple > Blue > Green > Red.

The first set of results tables at the top list the maximum number of science pack producing assemblers based on the pack being produced, assembler type, and the number of labs. The second set of results tables takes the average of the necessary factories and adds an adjustable number of standard deviations. I used two standard deviations in order to capture as much data as possible while excluding the total effects of the outliers. For the second set of tables I omitted almost all topics that certain packs were not necessary for, i.e. the average and standard deviation for blue science packs does not include the 0's from Oil Processing, Fluid Handling, etc.

There are some notable outliers in the consumption data that are noted here, but were not omitted from or altered in the analysis. These being:

- Steel Processing (red packs)
- Armor 1 (red packs)
- Logistics 3 (blue packs)
- Power Armor 2 (purple packs)

I welcome any and all comment and criticism. I doubt very much that I didn't make any mistakes. I'm also aware that I've made a lot of assumptions (perhaps to the point of naivete) that may invalidate everything I've done.

EDIT: Put the tables into a spoiler, since they're wildly wrong.