---
title: "Using drasR with Real Inspection Data"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Using drasR with Real Inspection Data}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, message=FALSE}
library(drasR)
```

## Overview

This vignette demonstrates how `drasR` can be used with lot-level inspection data.

In real manufacturing or pharmaceutical inspection settings, users may not know the true defect probability. Instead, they usually observe the number of inspected units and the number of defects found in each lot.

## Example inspection data

```{r}
raw_data <- data.frame(
  lot_id = paste0("L", 1:12),
  date = as.Date("2026-01-01") + 0:11,
  supplier = c(rep("Supplier_A", 6), rep("Supplier_B", 6)),
  lot_size = rep(1000, 12),
  sample_size = rep(100, 12),
  defects_found = c(1, 0, 1, 2, 1, 2, 4, 5, 6, 4, 7, 8)
)

raw_data
```

## Prepare the data

```{r}
prepared <- prepare_lot_data(
  raw_data,
  lot_id = "lot_id",
  sample_size = "sample_size",
  defects = "defects_found",
  lot_size = "lot_size",
  date = "date",
  supplier = "supplier"
)

prepared
```

## Find a baseline acceptance sampling plan

```{r}
plan <- find_plan(
  aql = 0.01,
  ltpd = 0.05,
  alpha = 0.05,
  beta = 0.10
)

plan
```

## Apply DRAS monitoring

```{r}
monitored <- dras_monitor(
  prepared,
  baseline_sample_size = plan$n,
  acceptance_number = plan$c,
  lambda = 0.40,
  warning_threshold = 0.02,
  tighten_factor = 2.00
)

monitored
```

## Summarise monitoring results

```{r}
summarise_dras_monitor(monitored)
```

## Supplier-level summary

```{r}
summarise_dras_monitor(monitored, by_supplier = TRUE)
```

## Write an audit report

```{r}
temp_dir <- tempfile("dras_report_")
files <- write_dras_report(monitored, output_dir = temp_dir)
files
```

## Interpretation

The DRAS workflow provides an audit-oriented way to monitor whether observed defect rates are drifting upward. When the EWMA statistic exceeds the warning threshold, the system recommends tightened inspection for subsequent lots.