Identify the variables in the presented model and their types. The variables studied are: machine speed, old or new layout, number of employees gr...

Identify the variables in the presented model and their types.

The variables studied are: machine speed, old or new layout, number of employees greater than or equal, and production volume.
x1 = machine speed - quantitative - unit of measurement "rpm"; x2 = layout - qualitative - class 1 "new" or class 0 "old"; x3 = number of employees - qualitative - class 0 "current", class 1 "greater"; Y = production volume - quantitative - unit of measurement "pieces/hour".
The objective of the model is to find the best scenario in which more pieces/hour are produced. For this, the various variables are correlated in the linear regression model, providing the result of pieces/hour. Thus, it is possible for those working with the model to make simulations by increasing or maintaining the same number of employees, modifying machine speed, or changing the layout. Each of these will provide a simulated result until the desired scenario is reached to be implemented later.
In the company where I work, a very important item that I correlated with the presented problem is the production of steam in ton/h from a boiler. We always seek the highest production according to the fuel used.
In this case, the variable Y would be the ton of steam produced per hour (ton/h) - being a quantitative variable; x1 - would be the amount of fuel that feeds the boiler - quantitative variable - measured in "ton"; x2 - would be the humidity of the fuel - qualitative variable in which the classes would be 0 = "<50% humidity" and 1 = ">= 50% humidity"; and x3 would be the use of the additive with the fuel, a qualitative variable in which the classes would be 1 = "use of additive" and 0 = "without additive".