optimal_replacement_time(cost_PM, cost_CM, weibull_alpha, weibull_beta, show_plot=True, print_results=True, q=0, **kwargs)¶
Calculates the cost model to determine how cost varies with replacement time. The cost model may be HPP (good as new replacement) or NHPP (as good as old replacement). Default is HPP.
Inputs: Cost_PM - cost of preventative maintenance (must be smaller than Cost_CM) Cost_CM - cost of corrective maintenance (must be larger than Cost_PM) weibull_alpha - scale parameter of the underlying Weibull distribution weibull_beta - shape parameter of the underlying Weibull distribution. Should be greater than 1 otherwise conducting PM is not economical. q - restoration factor. q=1 is Power Law NHPP (as good as old), q=0 is HPP (as good as new). Default is q=0 (as good as new). show_plot - True/False. Defaults to True. Other plotting keywords are also accepted and used. print_results - True/False. Defaults to True
Outputs: ORT - the optimal replacement time min_cost - the minimum cost per unit time Plot of cost model if show_plot is set to True. Use plt.show() to display it. Printed results if print_results is set to True.