Due to globalization, jobs in the textile industry have undergone significant technological changes and complex human-machine interfaces. Among these changes, the design and printing of textile garments offered greater versatility and printing quality. However, human factors that influence the interaction of this technology are still unknown. Because of this, high levels of mental work and the presence of errors are frequent. In this sense, the use of techniques for the evaluation of the mental workload, as well as the identification of human errors, may improve the process efficiency, user interaction, and usability. By developing a case study, this work uses cognitive evaluation methods to determine the mental workload and human error in the operation of Digital Transfer Film (DTF) printing machines. Five users voluntarily participated in the study. The methodology is made up of three stages. First, the hierarchical task analysis (HTA) was developed, followed by the Task Analysis for Error Identification (TAFEI), and finally, the mental workload was evaluated through the Workload Profile (WP). As a result, 12 illegal transitions were identified and related to errors. Additionally, those tasks that require complex set-ups by human operators to improve printing quality results demand the highest mental workload. Based on the results, it is possible to provide conclusions and recommendations that facilitate the interaction between people and DTF printing machines. The results highlight the need to have defined procedures to improve human interaction, machine functioning and training.