Machinery & Energetics

The article proposes the task of deciding whether to repair vehicles or other technical equipment under uncertainty based on statistics. Any technical means from time to time require repair. Stopping repair equipment is associated with a loss of profit for the repair company. The entrepreneur must make the difficult decision to stop the equipment for repair. The article examines the classic criteria for decision making under uncertainty: Bayes-Laplace, Wald, Sevid, or Hurwitz. The use of these criteria is considered as an example of vehicles that are in three likely states: good, satisfactory or unsatisfactory. The application of classic criteria minimizes losses. With this accumulated statistics in the form of a matrix of transitional probabilities, you can earn monthly income or suffer losses. This allows you to forecast future monthly earnings. This approach can be used for various technical means.

transport, repair, decision making criteria, uncertainty, transition probabilities