In this exercise you will be writing code to analyze the production of an assembly line in a car factory.
The assembly line's speed can range from 0 (off) to 10 (maximum).
At its lowest speed (1), 221 cars are produced each hour.
The production increases linearly with the speed.
So with the speed set to 4, it should produce 4 * 221 = 884 cars per hour.
However, higher speeds increase the likelihood that faulty cars are produced, which then have to be discarded.
You have three tasks. Each of the required functions takes a single integer parameter, the speed of the assembly line.
Implement the success_rate() method to calculate the probability of an item being created without error for a given speed.
The following table shows how speed influences the success rate:
0: 0% success rate.1 to 4: 100% success rate.5 to 8: 90% success rate.9: 80% success rate.10: 77% success rate.julia> success_rate(10)
0.77Implement the production_rate_per_hour() method to calculate the assembly line's production rate per hour, taking into account its success rate.
julia> production_rate_per_hour(6)
1193.4Note that the value returned is floating-point.
Implement the working_items_per_minute() method to calculate how many working cars are produced per minute:
julia> working_items_per_minute(6)
19Note that the value returned is an integer: incomplete items are not included.
In this exercise you will be writing code to analyze the production of an assembly line in a car factory.
The assembly line's speed can range from 0 (off) to 10 (maximum).
At its lowest speed (1), 221 cars are produced each hour.
The production increases linearly with the speed.
So with the speed set to 4, it should produce 4 * 221 = 884 cars per hour.
However, higher speeds increase the likelihood that faulty cars are produced, which then have to be discarded.
You have three tasks. Each of the required functions takes a single integer parameter, the speed of the assembly line.
Implement the success_rate() method to calculate the probability of an item being created without error for a given speed.
The following table shows how speed influences the success rate:
0: 0% success rate.1 to 4: 100% success rate.5 to 8: 90% success rate.9: 80% success rate.10: 77% success rate.julia> success_rate(10)
0.77Implement the production_rate_per_hour() method to calculate the assembly line's production rate per hour, taking into account its success rate.
julia> production_rate_per_hour(6)
1193.4Note that the value returned is floating-point.
Implement the working_items_per_minute() method to calculate how many working cars are produced per minute:
julia> working_items_per_minute(6)
19Note that the value returned is an integer: incomplete items are not included.