proj_inv.RdCalculates projected inventories and coverages and perform an analysis vs stocks targets
proj_inv(dataset, DFU, Period, Demand, Opening, Supply, Min.Cov, Max.Cov)a dataframe with the demand and supply features for an item per period
name of an item, a SKU, or a node like an item x location
a period of time monthly or weekly buckets for example
the quantity of an item planned to be consumed in units for a given period
the opening inventories of an item in units at the beginning of the horizon
the quantity of an item planned to be supplied in units for a given period
minimum stocks target of an item expressed in periods
maximum stocks target of an item expressed in periods
a dataframe with the calculated projected inventories and coverages and the related analysis
proj_inv(dataset = blueprint, DFU, Period, Demand, Opening, Supply, Min.Cov, Max.Cov)
#> Joining, by = c("DFU", "Period")
#> Joining, by = c("DFU", "Period")
#> # A tibble: 520 × 14
#> # Groups: DFU [10]
#> DFU Period Demand Opening Calcul…¹ Proje…² Supply Min.Cov Max.Cov
#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Item 000001 2022-07-03 364 6570 17 6206 0 4 8
#> 2 Item 000001 2022-07-10 364 0 16 5842 0 4 8
#> 3 Item 000001 2022-07-17 364 0 15 5478 0 4 8
#> 4 Item 000001 2022-07-24 260 0 14 5218 0 4 8
#> 5 Item 000001 2022-07-31 736 0 13 4482 0 4 8
#> 6 Item 000001 2022-08-07 859 0 12 3623 0 4 8
#> 7 Item 000001 2022-08-14 859 0 11 2764 0 4 8
#> 8 Item 000001 2022-08-21 859 0 10 1905 0 4 8
#> 9 Item 000001 2022-08-28 273 0 9 1632 0 4 8
#> 10 Item 000001 2022-09-04 349 0 8 1283 0 4 8
#> # … with 510 more rows, 5 more variables: Safety.Stocks <dbl>,
#> # Maximum.Stocks <dbl>, PI.Index <chr>, Ratio.PI.vs.min <dbl>,
#> # Ratio.PI.vs.Max <dbl>, and abbreviated variable names
#> # ¹Calculated.Coverage.in.Periods, ²Projected.Inventories.Qty