Bill Of Materials calculations in R - r

Question

I need to create a recursive function to iteratively calculate the accumulative costs of items in the bill of items given that each item belongs to a specific level, where the levels present the production levels from level n to level 0 (finished product). My data frame is as follows:
df <- data.frame(
item_id = c("i1", "i2", "i3", "i4", "i5", "i6", "i7", "i8", "i9"),
quantity = c(2, 2, 5, 1, 1, 1, 4,1, 1),
price = c(2, 5, 3, 7, 0, 10, 0, 4, 0),
itemtype = c("A", "A", "A", "A", "B", "A", "B","A", "C"),
productionlevel = c(3, 3, 3, 3, 2, 2, 1,1, 0)
)
I want to create a new column where the total prices will be calculated. The logic of my calculations is:
Level 3 =>i1 final_price= i1 price * i1 quantity
i2 final_price= i2 price * i2 quantity
i3 final_price= i3 price * i3 quantity
i4 final_price= i4 price * i4 quantity
Level 2 => i5 final_price= i5 quantity *{(i1 price * i1 quantity)+(i2 price * i2 quantity)+(i3 price * i3 quantity)+(i4 price * i4 quantity)}
Level 1 => i7 final_price= i7 quantity *{(i5 final_price)+(i6 price * i6 quantity)}
Level 0 => i9 final_price= i9 quantity *{(i7 final_price)+(i8 price * i8 quantity)}
my purpose is to find the accumulated values of price where price=0 and assign it to final_price after multiplying it by the quantity
I tried finding the solution using the accumulative method but I think it would be better to use a recursive function and call it to get the result.

Answer 1

Thank you very much!
I thought it would be the same if the order of "A" and "B" are as in my df for levels 2 and 1. Actually, A means row materials for which the prices are all assigned and B are the sub-assemblies that should be calculated. That's why I assigned price 0 to them.
Now I appreciate your help however the code you provided calculate only the first sub-assembly of the second level:
item_id quantity price itemtype productionlevel final_price
1 i1 2 2 A 3 4
2 i2 2 5 A 3 10
3 i3 5 3 A 3 15
4 i4 1 7 A 3 7
5 i5 1 10 A 2 36
6 i6 1 0 B 2 0
7 i7 4 4 A 1 144
8 i8 1 0 B 1 0
9 i9 1 0 C 0 144
Can you please help me adjust it. I was expecting a result as this (I got using the accumulation method for a different hierarchy):
item_id quantity price itemtype productionlevel final_price
1 i1 2 2 A 3 4
2 i2 2 5 A 3 10
3 i3 5 3 A 3 15
4 i4 1 7 A 3 7
5 i5 1 0 A 2 36
6 i6 1 10 B 2 10
7 i7 4 0 A 1 4
8 i8 1 4 B 1 184
9 i9 1 0 C 0 188
as the item types are corresponding to A(row materials), B(sub-assemblies) and C(finished good).

Answer 2

This is what I have tried in a very basic way where the number of levels are already known:
df <- data.frame(
item_id = c("i1", "i2", "i3", "i4", "i5", "i6", "i7", "i8", "i9"),
quantity = c(2, 2, 5, 1, 1, 2, 4,1, 1),
price = c(2, 5, 3, 7, 10, 0, 4, 0, 0),
itemtype = c("A", "A", "A", "A", "A", "B", "A","B", "C"),
productionlevel = c(3, 3, 3, 3, 2, 2, 1,1, 0),
stringsAsFactors=FALSE
)
df$final_price=0
maxLevel=max(df$productionlevel)
df[df$price != 0, 'final_price'] <- df[df$price != 0, 'quantity'] * df[df$price != 0, 'price']
df[df$productionlevel == 2 & df$itemtype != "A", 'final_price'] <- sum(df[df$productionlevel == 3, 'final_price']) * df[df$productionlevel == 2 & df$itemtype != "A", 'quantity']
df[df$productionlevel == 1 & df$itemtype != "A", 'final_price'] <- sum(df[df$productionlevel == 2, 'final_price']) * df[df$productionlevel == 1 & df$itemtype != "A", 'quantity']
df[df$productionlevel == 0 & df$itemtype != "A", 'final_price'] <- sum(df[df$productionlevel == 1, 'final_price']) * df[df$productionlevel == 0 & df$itemtype != "A", 'quantity']
The resulting data frame was:
item_id quantity price itemtype productionlevel final_price
1 i1 2 2 A 3 4
2 i2 2 5 A 3 10
3 i3 5 3 A 3 15
4 i4 1 7 A 3 7
5 i5 1 10 A 2 10
6 i6 2 0 B 2 72
7 i7 4 4 A 1 16
8 i8 1 0 B 1 82
9 i9 1 0 C 0 98
I need to make these calculations more generic without specifying the levels and item types.

Answer 3

With my background from manufacturing, I believe that there could be some typo in the dataframe. As it is urgent, I try my best to help. I modified the itemtype to fix the BOM hierarchy. My experiment tells me that it should be as below.
df <- data.frame(
item_id = c("i1", "i2", "i3", "i4", "i5", "i6", "i7", "i8", "i9"),
quantity = c(2, 2, 5, 1, 1, 1, 4,1, 1),
price = c(2, 5, 3, 7, 0, 10, 0, 4, 0),
itemtype = c("A", "A", "A", "A", "A", "B", "A","B", "C"),
productionlevel = c(3, 3, 3, 3, 2, 2, 1,1, 0),
stringsAsFactors=FALSE
)
df$final_price=0
maxLevel=max(df$productionlevel)
df[df$productionlevel==maxLevel,'final_price']=df[df$productionlevel==maxLevel,2]*df[df$productionlevel==maxLevel,3]
for (i in (maxLevel-1):1)
{
tmpdf=df[df$productionlevel==i, ]
for (itemtype in tmpdf$itemtype)
{
item_id=tmpdf[tmpdf$itemtype==itemtype, 'item_id']
cost=sum(df[df$itemtype==itemtype & df$productionlevel==(i+1), 'final_price'])
manufacturecost=ifelse(df[df$item_id==item_id, 3]==0, 1 , df[df$item_id==item_id, 3])
df[df$item_id==item_id, 'final_price']=df[df$item_id==item_id, 2]*manufacturecost*ifelse(cost==0,1,cost)
}
}
df[df$productionlevel==0,'final_price']=sum(df[df$productionlevel==1,'final_price'])
print(df)
Result:
item_id quantity price itemtype productionlevel final_price
1 i1 2 2 A 3 4
2 i2 2 5 A 3 10
3 i3 5 3 A 3 15
4 i4 1 7 A 3 7
5 i5 1 0 A 2 36
6 i6 1 10 B 2 10
7 i7 4 0 A 1 144
8 i8 1 4 B 1 40
9 i9 1 0 C 0 184

Answer 4

I changed the data frame to make sure it's making the right calculations (increased some quantity values):
df <- data.frame(
item_id = c("i1", "i2", "i3", "i4", "i5", "i6", "i7", "i8", "i9"),
quantity = c(2, 2, 5, 1, 1, 2, 4,1, 1),
price = c(2, 5, 3, 7, 10, 0, 4, 0, 0),
itemtype = c("A", "A", "A", "A", "A", "B", "A","B", "C"),
productionlevel = c(3, 3, 3, 3, 2, 2, 1,1, 0),
stringsAsFactors = FALSE
)
Then I used an iterative loop to calculate the final cost:
df$final_price = 0
maxLevel <- max(df$productionlevel)
df[df$price != 0, 'final_price'] <- df[df$price != 0, 'quantity'] * df[df$price != 0, 'price']
for (level in (maxLevel - 1):0) {
condition <- df$productionlevel == level & df$itemtype != "A"
if (any(condition)) {
higherLevel <- level + 1
df[condition, 'final_price'] <- sum(df[df$productionlevel == higherLevel, 'final_price']) * df[condition, 'quantity']
}
}
Till here I think it's perfectly working. Now can anyone help me find a way to create a recursive function doing the job instead of this loop?
Also, I was wondering if it's a good idea to use recursive functions when we can use loops, which approach is more effective?