Laboratory Control Charts (Shewhart, CUSUM, EWMA)

Statistical process control charts for laboratory quality monitoring. Implements Shewhart charts, CUSUM (Cumulative Sum), and EWMA (Exponentially Weighted Moving Average) charts for detecting systematic errors, shifts, and trends in laboratory measurements. Essential for ISO 15189 compliance and quality assurance programs.

Usage

labcontrolcharts(
  data,
  measurement,
  run_number,
  batch_id,
  control_level,
  chart_type = "shewhart",
  control_limits = "3sigma",
  target_mean = 0,
  target_sd = 0,
  cusum_k = 0.5,
  cusum_h = 4,
  ewma_lambda = 0.2,
  westgard_rules = "13s,22s,R4s",
  baseline_runs = 20,
  violation_detection = TRUE,
  trend_analysis = TRUE,
  shift_detection = TRUE,
  performance_metrics = TRUE,
  corrective_actions = TRUE,
  qc_summary = TRUE,
  export_violations = FALSE,
  control_plots = TRUE,
  histogram_plot = TRUE,
  trend_plot = TRUE
)

Arguments

data: the data as a data frame
measurement: Laboratory measurement values to monitor
run_number: Sequential run number or time point identifier
batch_id: Batch or lot identifier for stratified analysis
control_level: Control material level (e.g., Level 1, Level 2, Level 3)
chart_type: Type of control chart to generate
control_limits: Method for calculating control limits
target_mean: Target or expected mean value (0 = calculate from data)
target_sd: Target or expected standard deviation (0 = calculate from data)
cusum_k: CUSUM reference value (typically 0.5σ)
cusum_h: CUSUM decision interval (typically 4-5σ)
ewma_lambda: EWMA smoothing parameter (0.05-0.25 typical)
westgard_rules: Comma-separated Westgard rules (e.g., "13s,22s,R4s,41s,10x")
baseline_runs: Number of initial runs to establish baseline
violation_detection: Identify and mark control rule violations
trend_analysis: Perform trend detection and analysis
shift_detection: Detect systematic shifts in measurements
performance_metrics: Calculate ARL, power, and false alarm rates
corrective_actions: Provide corrective action recommendations
qc_summary: Calculate comprehensive QC statistics
export_violations: Export detailed list of violations
control_plots: Generate control chart visualizations
histogram_plot: Create measurement distribution histogram
trend_plot: Generate trend analysis visualization

Value

A results object containing:

`results$instructions`					a html
`results$dataInfo`					a table
`results$controlLimits`					a table
`results$violationSummary`					a table
`results$violationDetails`					a table
`results$trendAnalysis`					a table
`results$shiftDetection`					a table
`results$performanceMetrics`					a table
`results$qcStatistics`					a table
`results$correctiveActions`					a table
`results$westgardInterpretation`					a table
`results$shewhartChart`					an image
`results$cusumChart`					an image
`results$ewmaChart`					an image
`results$distributionPlot`					an image
`results$trendPlot`					an image
`results$methodExplanation`					a html

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$dataInfo$asDF

as.data.frame(results$dataInfo)

Usage

Arguments

Value

Examples