I took a while. Here is tidyverse approach:

library(dplyr)
library(tidyr)

df %>% 
  separate(sni, c("x", "y")) %>% 
  as_tibble() %>% 
  mutate(y = ifelse(as.numeric(y)<=9, paste0(substr(x, 1, nchar(x)-1), y),
                                 y)) %>% 
  mutate(id = row_number()) %>% 
  pivot_longer(c(x,y)) %>% 
  mutate(value = as.numeric(value)) %>% 
  group_by(col2 =as.integer(gl(n(),2,n()))) %>% 
  fill(value, .direction = "down") %>% 
  complete(value = seq(first(value), last(value), by=1)) %>% 
  fill(bransch, .direction = "down") %>% 
  select(bransch, sni=value) %>% 
  group_by(col2, sni) %>% 
  slice(1)

   col2 bransch         sni
   <int> <chr>         <dbl>
 1     1 name             15
 2     2 name             15
 3     3 name             16
 4     3 name             17
 5     3 name             18
 6     4 somename         16
 7     4 somename         17
 8     4 somename         18
 9     5 name            241
10     5 name            242
11     5 name            243
12     6 someothername   241
13     6 someothername   242
14     6 someothername   243

Let's try this.

Assume only three digits interval would have the pattern of 123-5 instead of 123-125, therefore in the ifelse, we modify this special pattern (e.g. 123-5) of interval into more regular one (123-125). Then separate the interval to individual integer using separate_rows.

We can then use complete to fill in the missing sequence in the interval.

library(tidyverse)

df %>% 
  group_by(sni,bransch) %>% 
  mutate(sni2 = ifelse(grepl("-", sni) & nchar(sub("-.*$", "", sni)) >= 3, 
                       sub("^(\\d\\d)(.)-", "\\1\\2-\\1", sni), 
                       sni)) %>% 
  separate_rows(sni2, convert = T) %>%
  complete(sni2 = min(sni2):max(sni2)) %>% 
  ungroup() %>% 
  select(-sni)

# A tibble: 14 × 2
   bransch        sni2
   <chr>         <int>
 1 name             15
 2 name             15
 3 name             16
 4 name             17
 5 name             18
 6 somename         16
 7 somename         17
 8 somename         18
 9 name            241
10 name            242
11 name            243
12 someothername   241
13 someothername   242
14 someothername   243

If I understood correctly

tmp=setNames(strsplit(df$sni,"-"),df$bransch)
tmp=unlist(
  lapply(tmp,function(x){
    x=as.numeric(x)
    if (length(x)>1) {
      if (x[1]<x[2]) {
        seq(x[1],x[2],1)
      } else {
        seq(x[1],x[1]+x[2]-1,1)
      }
    } else {
      x
    }
  })
)

data.frame(
  "bransch"=names(tmp),
  "sni"=tmp
)

          bransch sni
1            name  15
2            name  15
3           name1  16
4           name2  17
5           name3  18
6       somename1  16
7       somename2  17
8       somename3  18
9           name1 241
10          name2 242
11          name3 243
12 someothername1 241
13 someothername2 242
14 someothername3 243

Using separate to get the start and end of the sequence, the we can map and unnest to get the result.

library (tidyverse) 
 data %>%
        separate(
        sni, 
        into = c("from", "to"),
        fill = "right",
        convert = TRUE) %>%
        mutate(to = if_else(is.na(to), from, to)) %>%
        transmute(
        bransch,
        sni = map2(from, to, `:`)) %>%
        unnest_longer(sni)

# A tibble: 14 x 2
   bransch         sni
   <chr>         <int>
 1 name             15
 2 name             15
 3 name             16
 4 name             17
 5 name             18
 6 some name        16
 7 some name        17
 8 some name        18
 9 name            241
10 name            242
11 name            243
12 someothername   241
13 someothername   242
14 someothername   243

Data

data <- tibble(
bransch = c("name","name","name","some name","name","someothername"),
sni =c("15","15","16-18","16-18","241-243","241-243"))