R/manufacture.R

In pid: Process Improvement using Data

# (c) Kevin Dunn, 2018.

manufacture <- function(P=0.75, T=325){
  # Simulates a manufacturing facility where there are 2 factors that affect the outcome.
  #
  #   P = selling price of the product, measured in dollars and cents
  #   T = throughput (production rate) of the process, measured in parts per hour
  #
  # Typical values for P = $0.75 and T = 325 parts per hour.
  #
  # The outcome is: profit made per hour [dollars/hour]. The aim is to maximize this.

  if ( (length(P) > 1) | (length(T) > 1)) {
    stop("Running the manufacturing experiments in parallel is (intentionally) not allowed.")
  }
  if (!all(is.finite(P)) | !all(is.finite(T))){
    stop("All function inputs must be finite numbers.")
  } else if (P < 0) {
    stop("Please provide a positive sales price, P.")
  } else if (T < 0) {
    stop("The throughput (parts per hour) must be a positive value.")

  } else{

    p_coded <- (P - 1.5) / 1.0
    t_coded <- (T - 320.0) / 20.0
    y <- (18.0 * t_coded + 10 * p_coded - 5 * t_coded * p_coded - 7 * t_coded * t_coded
          - 24 * p_coded * p_coded + 50) * 12 + 2 * sin(T) + 2 * cos(P) + rnorm(1) * 2
    y <- round(y)
  }
  return(y)
}