R中縮進的物料清單乘法

我正在嘗試確定對縮進的物料清單 (BOM) 進行預測所需的數量，以進行一些庫存控制。BOM 對子裝配有多個級別，因此父項所需的數量需要乘以每個級別。例如：

有沒有辦法通過將頂層數量引入到成品中來計算 R 中每行 BOM 所需的數量？

uj5u.com熱心網友回復：

預先：這是脆弱的：如果行順序發生變化，它會破壞......靜默。如果您有更好的方法來識別組和子組，最好使用它們。

但是，試試這個

dplyr

library(dplyr)
dat %>%
  group_by(Parent.Item) %>%
  group_by(L1 = cumsum(Level == 1), .add = TRUE) %>%
  mutate(
    Qty = Parent.Qty.Forecast * sapply(Level, \(lvl) prod(Quantity.Per[Level <= lvl]))
  ) %>%
  ungroup()
# # A tibble: 6 x 7
#   Item                                  Level Quantity.Per Parent.Item   Parent.Qty.Forecast    L1   Qty
#   <chr>                                 <int>        <int> <chr>                       <int> <int> <dbl>
# 1 Finished Item                             0            1 Finished Item                  10     0    10
# 2 Subassembly 1                             1            2 Finished Item                  10     1    20
# 3 Component 1 Subassembly 1                 2            5 Finished Item                  10     1   100
# 4 Subassembly 2                             1            4 Finished Item                  10     2    40
# 5 Component 1 Subassembly 2                 2            2 Finished Item                  10     2    80
# 6 Component 1 Component 1 Subassembly 2     3            2 Finished Item                  10     2   160

基數R

dat$L1 <- with(dat, ave(Level == 1, Parent.Item, FUN = cumsum))
dat$Qty <- with(dat, ave(seq_len(nrow(dat)), list(Parent.Item, L1), FUN = \(rn) {
  Parent.Qty.Forecast[rn] * sapply(Level[rn], \(lvl) prod(Quantity.Per[rn][Level[rn] <= lvl]))
}))

資料表

library(data.table)
# should use setDT(dat) instead
as.data.table(dat
  )[, L1 := cumsum(Level == 1), by = .(Parent.Item) 
    ][, Qty := Parent.Qty.Forecast * sapply(Level, \(lvl) prod(Quantity.Per[Level <= lvl])),
      by = .(Parent.Item, L1) ]

資料

### without 'Qty.Needed'
dat <- structure(list(Item = c("Finished Item", "Subassembly 1", "Component 1 Subassembly 1", "Subassembly 2", "Component 1 Subassembly 2", "Component 1 Component 1 Subassembly 2"), Level = c(0L, 1L, 2L, 1L, 2L, 3L), Quantity.Per = c(1L, 2L, 5L, 4L, 2L, 2L), Parent.Item = c("Finished Item", "Finished Item", "Finished Item", "Finished Item", "Finished Item", "Finished Item"), Parent.Qty.Forecast = c(10L, 10L, 10L, 10L, 10L, 10L)), row.names = c(NA, -6L), class = "data.frame")
### with 'Qty.Needed`
dat <- structure(list(Item = c("Finished Item", "Subassembly 1", "Component 1 Subassembly 1", "Subassembly 2", "Component 1 Subassembly 2", "Component 1 Component 1 Subassembly 2"), Level = c(0L, 1L, 2L, 1L, 2L, 3L), Quantity.Per = c(1L, 2L, 5L, 4L, 2L, 2L), Parent.Item = c("Finished Item", "Finished Item", "Finished Item", "Finished Item", "Finished Item", "Finished Item"), Parent.Qty.Forecast = c(10L, 10L, 10L, 10L, 10L, 10L), Qty.Needed = c("(1x10) = 10", "(1x2x10)=20", "(1 x 2 x 5 x 10) = 100", "(1 x 4 x 10 ) = 40",  "(1 x 4 x 2 x 10 ) = 80", "(1 x 4 x 2 x 2 x 10 ) = 160")), row.names = c(NA, -6L), class = "data.frame")

標籤：

上一篇：為什么英語函式在RStudio的ifelse中不起作用？

下一篇：六個月前的總和數值變數