General simulation model for logistics operation in a randomly damaged system

The logistics operation considered is imbedded in a system that is subject to damage. Natural attrition and induced attrition can both occur. This system is concerned with the availability and/or use of several different types of items during a specified period of time. The purpose of logistics is to furnish transportation, reduce natural attrition through maintenance, and return damaged items to operational condition. The capability of the logistics operation is examined by simulating the operation of the entire system for the specified time period. The damage received by the various parts of the system depends on the situation at the start of the time period, the use made of the items, the nature of the induced attrition, and the maintenance procedures, etc. Attrition occurs on a probability distribution basis and is introduced by a Monte Carlo procedure. The time required to return a damaged item to operational condition depends on the type of damage, the damage received by other items, the characteristics of the logistics operation, the damage received by the logistics part of the system, etc. To obtain the simulation model, the over‐all system is divided into subsystems on the basis of the use and location of the items, the properties of the logistics operation, etc. The time scale used is discrete; i.e., all important effects are considered to occur during one of a specified finite set of time intervals. The same form of simulation model is used for representing the operation of each subsystem for each time interval. That is, the mathematical model has the same functional form, but the variables in this functional form can differ with the subsystem and time interval. These subsystems can interact in many ways, e.g., items can be transferred between subsystems, damage received in one subsystem can affect the logistics operations in other subsystems, etc. By using time as the basis for coordination among subsystems, the mathematical model and random assignments for attrition can be programmed on a high‐speed computer. The simulation is performed by obtaining first the operational results for all subsystems at the first time considered; then, by using the first‐time results, the second‐time results are obtained, etc. Examination of the subsystem results for each time interval should furnish a good indication of the capabilities of the logistics operation. Repetitions of this simulation furnish an indication of the effects of statistical variation.