Clarification of operational costs taking into account container handling system and equipment characteristics

Abstract

A method for evaluating the performance distribution of transshipment equipment performing operations in a container terminal stack is considered. It is proved that the productivity of operations is the most significant indicator for assessing the economic efficiency of a marine or dry container terminal. Performance evaluation is carried out on the assumption that the technological task for reloading equipment is a sequence of containers with random coordinates in a stack. To complete this technological task, the reloading equipment must move from the position of the last task to the position of the new one. For each movement in operation, the speed is calculated taking into account the acceleration and braking of the mechanisms. As an example of performance evaluation, a warehouse container crane with pneumatic wheels, related to overhead handling equipment, is considered. This type of equipment is the most common in modern container terminals. A description of the simulation model that is used to perform the assessment is provided. The initial data of the model on the execution time of individual movements, as well as on the parameters of the stack, were collected at Russian container terminals. A description of the simulation model that is used to perform the assessment is provided. The initial data of the model on the execution time of individual movements, as well as on the parameters of the stack, were collected at Russian container terminals. The results of the simulation model are the probability distribution of the performance of transshipment equipment during the selection and stacking of containers in the stack of the container site. It is established that the results obtained agree with the actual data on the operation of Russian container terminals. The proposed method makes it possible to more accurately assess the performance of reloading equipment. It is noted that the developed approach should be supplemented taking into account container warehousing strategies, as well as methods of algebraic estimation of the complexity of container sampling.