The contemporary market creates a demand for continuous improvement of production, service, and management processes. Increasingly advanced IT technologies help designers to meet this demand, as they allow them to abandon classic design and design-testing methods in favor of techniques that do not require the use of real-life systems and thus significantly reduce the costs and time of implementing new solutions. This is particularly important when re-engineering production and logistics processes in existing production companies, where physical testing is often infeasible as it would require suspension of production for the testing period. In this article, we showed how the Digital Twin technology can be used to test the operating environment of an autonomous mobile robot (AMR). In particular, the concept of the Digital Twin was used to assess the correctness of the design assumptions adopted for the early phase of the implementation of an AMR vehicle in a company’s production hall. This was done by testing and improving the case of a selected intralogistics task in a potentially “problematic” part of the shop floor with narrow communication routes. Three test scenarios were analyzed. The results confirmed that the use of digital twins could accelerate the implementation of automated intralogistics systems and reduce its costs.

The human–machine relationship was dictated by human needs and what technology was available at the time. Changes within this relationship are illustrated by successive industrial revolutions as well as changes in manufacturing paradigms. The change in the relationship occurred in line with advances in technology. Machines in each successive century have gained new functions, capabilities, and even abilities that are only appropriate for humans—vision, inference, or classification. Therefore, the human–machine relationship is evolving, but the question is what the perspective of these changes is and what developmental path accompanies them. This question represents a research gap that the following article aims to fill. The article aims to identify the status of change and to indicate the direction of change in the human–machine relationship. Within the framework of the article, a literature review has been carried out on the issue of the human–machine relationship from the perspective of Industry 5.0. The fifth industrial revolution is restoring the importance of the human aspect in production, and this is in addition to the developments in the field of technology developed within Industry 4.0. Therefore, a broad spectrum of publications has been analyzed within the framework of this paper, considering both specialist articles and review articles presenting the overall issue under consideration. To demonstrate the relationships between the issues that formed the basis for the formulation of the development path.

The matrix profile processing is considered for the implementation of production maintenance tasks in the context of data acquisition by industrial Internet of Things solutions. The prospective implementation of the matrix profile data structure is verified through a dedicated case study, presenting the method of processing non-labelled data registered by sensors. The case study demonstrates the functionality of the profile and indicates the prospects of their applications in the field of production maintenance.

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The following paper presents a key role and potential of Industrial Internet of Things (IIoT) in industrial applications as a solution for monitoring and maintaining manufacturing assets. IIoT is particularly important due to progressing computerisation of hardware resources leading to development of a virtualised model of autonomous real-time production management. Adequately article presents case study of IIoT use in production environment – both methodical and analytic approach is presented.

The purpose of this research is to deepen the study of the influence of cognitive proximity has on the innovative performance of firms, as well as the mediating effect of potential and realized absorptive capacity in this relationship. For this purpose, an empirical analysis has been carried out. The primary data have been analyzed by means of PLS-SEM technique. The results show that the cognitive proximity of firms has both a direct and an indirect impact on their innovative performance, through their potential and realized absorptive capacity. We conclude that cognitive proximity matters for the innovation performance of firms, as it facilitates the understanding and establishment of positive reciprocity agreements between the companies, especially in terms of knowledge. Nevertheless, firms must develop a great capability to absorb new knowledge to exploit the advantages derived from its cognitive proximity to its stakeholders and leverage all the knowledge within their reach.