Within Industry 4.0, ergonomics and active adjusting of the manual assembly place are very important, but quite often overlooked segments. To adjust the manual assembly place, the worker needs to be identified, which is most often done with an RFID card or by entering of a worker’s ID code. However, these systems have shortcomings such as time wasting, always having an RFID card present etc. That is why in the final task, we developed a facial recognition system that will be used in the future to adjust the manual assembly place in the smart factory, which is the main idea of an industry 4.0. At the beginning of the final paper we presented the basics of Industry 4.0, the ergonomics of the manual assembly place, RFID and a few other systems for face recognition that are important for understanding the 4.0 concept. Then we developed an algorithm for face recognition using the OpenMV module. By using OpenCV libraries, we developed a program that compares captured photos with an internal data base. Depending on the matching results, it selects the best approximation and displays the name of the chosen person. In the end, we tested the developed algorithm with five different individuals and five repetitions, which confirmed the functioning of the system.