Abstract
The automotive industry sector, made up of the assembly activities of all types of vehicles and the production of auto parts, has a wide variety of companies that contribute to the dynamics of the world economy, therefore, in this project It is sought by simulating discrete events to create a digital twin where faults in the motorcycle assembly process can be identified, in this way it will be possible to detect any observed nonconformity and thus reduce pertinently all the faults presented, taking into account the exogenous factors that can increase operational costs and delay the assembly process, on this case, we want to implement an optimal model by simulating the process without assembly failures in times of pandemic, this in order to analyze and propose improvements in the process whose objective is strengthen decision-making in favor of customer satisfaction. At the end of this study, it was found that the assembly problems were more related to the reduction of personnel due to preventive isolation and delays in the preparation process, due to this it was recommended to reduce preparation times from 5 to 3.5 hours in order to start the assembly in less time and have the safety stock immediately in case of damage to the auto parts.
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