GENETIC ALGORITHM-BASED OPTIMIZATION OF INTER-MACHINE DELAYS IN AUTOMATIVE MANUFACTURING

Considering the many situations in which the industrial sector is involved, it is known that industrial innovations should be emphasized especially for the obstacles in front of product development. In every situation where production is involved, undesirable situations may occur due to human-induced errors and errors in the operation of machines and automation systems. There are many products that are lacking in terms of both time wastage and quality in the product to be produced. Various artificial intelligence programs have been used to prevent this situation. In this study, a permutation order was created between the machines by including the automotive sector, which has delays in actual production and takes into account the inter-machine times. In this study, the automotive sector, which has delays in actual production, is included in the process. In addition, permutation ordering between the machines is provided based on the inter-machine times. Used R program makes the comparison of selected models has used. In the program, some machines in the genetic algorithm structure are kept constant during the permutation order. This study is an example of what kind of way should be followed for the sequence to be applied in cases where a production process is dominant in the industrial sector and what conditions should be created for effective optimization. Furthermore, the importance of time-based strategic planning in production sectors is stressed.