series plots for various cases by considering multiple variables from multiple tables

I'm trying to generate all possible number of plots from two different data frames (df1 anf df2) based on their individual cases (rows) using ggplotpreferably with Loop/facet_wrap/facet_grid. But I need some clues specifically on using multiple variables for facet_. I tried grid.arrange which works for only one type of category in df1 as the following cases

I have plenty of data where the category in df1 and items in df2 have multiple groups (e.g., items & category). My aim is to plot for each possibilities based on category and items from df1 and df2 considering multiple groups. For example, from items I may choose "net"or "web" or both and fromcategoryI can select only "OM"or/and "NH" etc.

OR series of

A hint/solution would be appreciated. Following are the sample df1 and df2.

df1 <- structure(list(W = c(15550L, 13450L, 12300L, 11590L, 10516L, 
10201L, 9050L, 8025L, 29550L, 23450L, 21590L, 20270L, 19516L, 
19201L, 19050L, 18025L, 1550L, 1450L, 1290L, 1170L, 951L, 801L, 
750L, 625L, 555L, 425L), X = c(1000L, 2000L, 2000L, 2000L, 4000L, 
4000L, 6000L, 6000L, 1500L, 2500L, 2500L, 2500L, 4500L, 4500L, 
6700L, 6700L, 900L, 1200L, 1200L, 1280L, 1346L, 1346L, 1420L, 
1420L, 1490L, 1550L), Y = c(90L, 90L, 80L, 70L, 70L, 60L, 60L, 
50L, 110L, 110L, 100L, 90L, 90L, 80L, 80L, 70L, 130L, 130L, 120L, 
120L, 120L, 110L, 110L, 100L, 100L, 100L), items = structure(c(3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("eml", "net", 
"web"), class = "factor")), class = "data.frame", row.names = c(NA, 
-26L))

df2 <-  structure(list(a_max = c(23.6, 25.6, 27.9, 19.6, 27.76, 29.53, 
16.99, 17.68, 21, 18.2, 19.26, 16.1, 35.72, 21.43, 27.56, 18.88, 
29.17, 28.82, 26.89, 17.26), a_min = c(17.6, 19.3, 20.4, 11.5, 
25.18, 26.44, 13.72, 13.24, 18, 15.2, 16.08, 11.3, 31.76, 16.84, 
21.68, 12.64, 26.26, 25.76, 22.12, 12.58), b_max = c(55.83, 48.08, 
56.5, 48.42, 50.9, 70.9, 45.74, 66.6, 54.85, 62.09, 49.29, 84.36, 
44.83, 47.37, 45.87, 54.33, 62.5, 52.9, 49.25, 65.39), b_min = c(50.64, 
43.64, 50.5, 39.36, 48.8, 68.8, 43.52, 60.6, 49.3, 57.02, 43.32, 
73.38, 41.74, 44.16, 42.06, 47.34, 60.1, 49.6, 44.9, 56.72), 
    category = structure(c(19L, 14L, 4L, 9L, 18L, 13L, 3L, 8L, 
    20L, 15L, 5L, 10L, 16L, 11L, 1L, 6L, 17L, 12L, 2L, 7L), .Label = c("A > BC", 
    "A > CW", "A > NH", "A > NJ", "A > OM", "S > BC", "S > CW", 
    "S > NH", "S > NJ", "S > OM", "T > BC", "T > CW", "T > NH", 
    "T > NJ", "T > OM", "V > BC", "V > CW", "V > NH", "V > NJ", 
    "V > OM"), class = "factor")), class = "data.frame", row.names = c(NA, 
-20L))