Treatment effect on categorical dependent variable

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I conducted an experiment where I tested the effect of copper on irrigation dripper blockage. I had dripper types "copper" and "normal" and once a week I measured whether they are working (1) or not (0). All the drippers started working (1) and all of them were blocked (0) by the end of the experiment. I need to analyze if there was a significant effect of the type and when. I also suspect that some type of debris might block the drippers based on their proximity to the water source so I added their position to the data. A sample of the data:

> head(data)
# A tibble: 6 × 6
  Date                Lateral Position `Distance (m)` Type   Working
  <dttm>              <fct>   <fct>             <dbl> <fct>  <fct>  
1 2022-08-10 00:00:00 1       1                   0.7 Normal 1      
2 2022-08-10 00:00:00 1       2                   1.2 Normal 1      
3 2022-08-10 00:00:00 1       3                   1.7 Copper 1      
4 2022-08-10 00:00:00 1       4                   2.2 Copper 1      
5 2022-08-10 00:00:00 1       5                   2.7 Copper 1      
6 2022-08-10 00:00:00 2       1                   0.9 Normal 1  
> dput(head(data))
structure(list(Date = structure(c(1660089600, 1660089600, 1660089600, 
1660089600, 1660089600, 1660089600), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), Lateral = structure(c(1L, 1L, 1L, 1L, 1L, 2L), levels = c("1", 
"2", "3", "4"), class = "factor"), Position = structure(c(1L, 
2L, 3L, 4L, 5L, 1L), levels = c("1", "2", "3", "4", "5", "6"), class = "factor"), 
    `Distance (m)` = c(0.7, 1.2, 1.7, 2.2, 2.7, 0.9), Type = structure(c(2L, 
    2L, 1L, 1L, 1L, 2L), levels = c("Copper", "Normal"), class = "factor"), 
    Working = structure(c(2L, 2L, 2L, 2L, 2L, 2L), levels = c("0", 
    "1"), class = "factor")), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame"))

Any pointers as to what to read or how to solve this will be much appreciated. Thanks

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