(1) Background: A current trend observed in the logistics sector is the use of Industry 4.0 tools to improve and enhance the efficiency of cargo handling processes. One of the popular solutions is an augmented reality system that supports operators in everyday tasks. The article aims to present design assumptions for implementing an augmented reality system to support air cargo handling at the warehouse. (2) Methods: Research was carried out based on a five-stage analytical procedure, aiming to analyze the current state and identify the potential for implementing the AR system. The following methods were used to collect data: co-participant observations, process analysis, direct interviews, analysis of internal documentation, and applicable legal regulations. (3) Results: The conducted research allowed for identifying information flows accompanying cargo flows and developing a project to automate selected information flows. The obtained results made it possible to identify operations for which the AR system’s implementation will increase their effectiveness and efficiency. (4) Conclusions: The obtained results identified the need to develop a hybrid algorithm for arranging cargo in the warehouse and to build a system supporting self-verification of markings on air cargo.

(1) Background: This paper presents the results of a study on developing a hybrid evaluation model for air cargo handling systems, combining fuzzy logic and reliability theory. (2) Methods: The research methodology consisted of two stages: the first used reliability analysis to calculate the performance of individual processes in the cargo handling system. In contrast, the second used fuzzy logic to integrate these metrics and generate an overall system evaluation. Statistical metrics, including mean and standard deviation, were used to construct adaptable membership functions for the fuzzy logic model. (3) Results: 27 test scenarios were built, in which the impact of individual compositions of operator teams (depending on their experience) implementing individual air cargo handling processes on the final assessment of the entire system was examined. Configurations with experienced operators consistently achieved the highest performance evaluations, although the strategic integration of less experienced personnel in noncritical roles was shown to maintain system functionality. (4) Conclusions: The results confirm that the proposed model is a practical decision-support tool for air cargo terminal management. It enables precise process evaluation, supports resource optimization and increases air cargo operations’ overall reliability and efficiency.

(1) Background: The article presents the results of research carried out as part of one of the project’s tasks, aiming to develop training scenarios for selected workstations related to the operation of passenger rail transport. The article aims to present the results of a training experiment to verify the effectiveness of the developed training scenario for conductors regarding lift operations for people with disabilities. (2) Methods: The study used an analysis of the execution times of individual training tasks, accompanying observation, face-to-face interviews, and a comparative analysis of the effectiveness of various training strategies. The research was carried out following the developed five-stage research procedure. (3) Results: The obtained research results confirm the benefits of using virtual reality in training conductors and allow for determining the most effective training strategy. The measurements of the execution times of individual training operations made it possible to identify the tasks in the training program that were the most time-consuming or characterized by highly diversified execution times. (4) Conclusions: Based on the research, it was possible to develop recommendations regarding the changes that should be introduced in the training tool to better adapt to the real conditions of service operations. The effectiveness of using this form of training in relation to the improvement of a selected group of employees was confirmed.

Background: The paper aims at answering cognitive questions which let one draw conclusions on AR usability in terms of supporting the dangerous goods acceptance (DGA) process before air transportation, including (1) which operations of the DGA process in airports reveal the highest potential in terms of being supported by AR solutions? (2) Which parameters of the DGA process can be improved by the use of AR solutions? (3) What benefits and drawbacks of solutions derived from the use of AR technology have been noticed in practical experiments? Research method: The study has been conducted by analysing the DGA process while considering the support of AR technology, the development of AR applications for AR goggles and a mobile phone, and their practical testing. Results: There has been a model of the DGA process has been developed in the paper as well as decision algorithms, helping operators controlling DGs before a flight, have been identified. Following these foundations, the design of functions supporting the DG acceptance process has been indicated and their expected influence on DGA results has been evaluated. Conclusions: The potential for AR support in DGA has been very positively assessed by experts; however, there have also been observed differences between functions that indicate the most promising and less promising aspects. Operators especially appreciate AR goggles when their goal is to show a virtual picture of data and related law regulations regarding controlled DGs, while interactions with AR goggles are assessed less positively. The results also prove that, at the present stage of technology development, AR tools can assist an operator and neither of the operations can be carried out automatically.

Although one can presently observe great development in the methods for diagnosing conditions of technical systems, inspections which are not 100% accurate are still common in industry. If there are multiple available inspection methods which differ in accuracy of diagnosis, cost, or testing time, the answer for the question: which inspection method should be chosen is not a simple task. This paper addresses the problem and proposes a two-stage inspection policy model whose aim is to combine inspection methods that differ in their accuracy and cost features. The two-stage policy models that have been used so far in the literature assume that the second stage of an inspection is perfect, which is not always possible or profitable. For this reason, the mathematical model of the two-stage inspection policy with not-necessarily-perfect second stage is developed here, and its results are presented for the case study of diagnosing sealing in a hydraulic cylinder. The example proved that the application of mixed imperfect inspections could decrease maintenance cost, compared to the one-stage perfect inspection policy, by up to 35%. The paper also formulates a set of rules that support decision making while searching for cost-effective parameters of the two-stage policy. Their application is confirmed by a numerical example, which shows their potential in suboptimization of the proposed policy.