The paper presents a general concept of smart design and production control as key elements for efficient operation of a smart factory. The authors present various techniques that aid the design process of individualized products and organization of their production in the context of realization of the mass customization strategy, which allows a shortened time of development for a new product. Particular attention was paid to integration of additive manufacturing technologies and virtual reality techniques, which are a base of the so-called hybrid prototyping.

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The thesis describes the research conducted on the effectiveness of purposed Augmented Reality solutions for material identification in the production system. The research was carried out at the Smart Factory laboratory of the Poznan University of Technology and was divided into two stages. In the first stage, the research has been conducted to identify both of the best variants of application and the AR smart glasses which were used in second stage. The time of identification and completion of production parts obtained using the AR technique and the traditional technique were compared during the second stage of the research. The results of the second experiment show that the AR method is efficacious for identifying materials in a production system; however, the traditional method time is shorter. This proves that the traditional method is more effective and therefore AR solutions need to be improved.

The article presents the results of research on the impact of virtual reality on the effectiveness of training employees performing production tasks. The research was carried out in the Smart Factory laboratory, which is a model of a smart factory functioning in accordance with the concept of Industry 4.0. A prototype VR system and its building process were presented, starting with the digitization of the laboratory, through logical programming and connecting peripheral devices. The subject, scope and plan of conducting comparative studies of operator training at both real production stations and in a virtual environment were presented. As a criterion for comparing the results achieved by individual groups subject to the study, the following were adopted: the time to complete the production task and the number of non-compliant products achieved in real conditions.