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#' Create R MR chart for statistical process control
#'
#' @description
#' Generate a moving range chart chart from a set of consecutive measurements.
#'
#' @details
#' This type of chart is typically applied in product manufacturing to monitor
#' deviations from the target value over time. It is usually accompanied by
#' the \code{\link{chart_IMR}}
#'
#' @references
#' For a complete case study application refer to \url{https://j-ramalho.github.io/industRial/}
#'
#' @param data
#' A dataset generated by the function \code{\link{process_stats}}
#'
#' @return
#' This function returns an object of class ggplot
#' @export
#' @importFrom magrittr %>%
chart_IMR <- function(data) {
data %>%
ggplot2::ggplot(ggplot2::aes(x = data$part_id, y = data$weight_MR)) +
ggplot2::geom_line() +
ggplot2::geom_point() +
ggplot2::geom_hline(ggplot2::aes(yintercept = data$MR_max), color = "deepskyblue4", linetype = 3) +
ggplot2::geom_hline(ggplot2::aes(yintercept = 0), color = "red", linetype = 2) +
ggplot2::geom_point(ggplot2::aes(x = data$part_id, y = data$R_out_limits), color = "red") +
ggplot2::theme_light() +
ggplot2::theme(axis.text.x = ggplot2::element_text(size = 8)) +
ggplot2::labs(
title = "Weight SPC",
subtitle = "MR-chart",
x = "Part id",
y = "Weight Moving Range [g]",
caption = "data source: Line1"
) +
industRial::theme_qcc()
}
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