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Generate Control Chart

Source: R/control-limits.R
measure_control_chart.Rd

Creates a control chart with optional multi-rule (Westgard) violation detection.

Usage

measure_control_chart(
  data,
  response_col,
  order_col,
  limits = NULL,
  rules = c("1_3s", "2_2s", "R_4s", "4_1s", "10x"),
  group_col = NULL
)

Arguments

data

A data frame containing QC measurements.

response_col

Name of the column containing QC values.

order_col

Name of the column containing run order/sequence.

limits

Optional measure_control_limits object. If NULL, calculated from the data.

rules

Character vector of Westgard rules to apply. Default is c("1_3s", "2_2s", "R_4s", "4_1s", "10x").

group_col

Optional grouping column.

Value

A measure_control_chart object containing:

  • data: The input data with added violation flags

  • limits: The control limits used

  • violations: Summary of rule violations

  • rules_applied: Which rules were checked

Details

Westgard Rules

The function supports common Westgard multi-rules:

  • 1:3s: One point beyond 3 sigma (action required)

  • 2:2s: Two consecutive points beyond 2 sigma (warning)

  • R:4s: Range of two consecutive points > 4 sigma

  • 4:1s: Four consecutive points beyond 1 sigma (same side)

  • 10x: Ten consecutive points on same side of mean

Interpretation

  • Violations are flagged with the specific rule that was triggered

  • Multiple rules can be triggered by the same point

  • A run is considered "in control" if no violations are detected

See also

measure_control_limits(), autoplot.measure_control_chart()

Other control-charts: measure_control_limits(), measure_system_suitability()

Examples

# Generate control chart with Westgard rules
set.seed(123)
qc_data <- data.frame(
  run_order = 1:50,
  qc_value = c(rnorm(45, 100, 2), rnorm(5, 106, 2))  # Last 5 shifted
)
chart <- measure_control_chart(qc_data, "qc_value", "run_order")
print(chart)
#> measure_control_chart
#> ──────────────────────────────────────────────────────────────────────────────── 
#> 
#> Observations: 50 
#> Rules applied: 1_3s, 2_2s, R_4s, 4_1s, 10x 
#> Violations detected: 5 
#> 
#> Status: OUT OF CONTROL
#> 
#> Violation summary:
#> # A tibble: 5 × 3
#>   run_order qc_value violation     
#>       <int>    <dbl> <chr>         
#> 1        46     104. 4:1s          
#> 2        47     105. 4:1s 4:1s     
#> 3        48     105. 4:1s 4:1s     
#> 4        49     108. 2:2s 4:1s 4:1s
#> 5        50     106. 2:2s 4:1s