Metodología de adaptación de distribución de probabilidades en teoría de colas aplicados a la industria

Abstract

The main objective of this degree project is to develop a methodology for the adaptation of probabilities in queueing theory applied to industry for queue identification and time reduction. Data collection and research on machinery, surveys of operators in the field, as well as data entry analysis were performed. Once the data was collected, an exhaustive analysis was carried out by generating random data in the software based on a significant average of each process, previously a mathematical algorithm was created in which important and relevant data was entered for the execution of this. To achieve this, three types of distribution "normal, exponential, Poisson" were considered, and software such as Matlab and Minitab were used to carry out the different simulations which yielded the data and statistical graphs. The results obtained reflect the type of distribution that best suits each process, arguing that it generates the least number of elements waiting to receive a service.