The paper discusses the subject of logistics in ambulance transport based on the example of an ambulance service. When discussing this subject, it is worth noting that an interesting issue related to its functioning is that relating to its relationship with transport logistics regarding travel time to the patient. Discussing this topic will be the subject of this paper. A logistics process will be presented on the example of logistics in the transport of ambulances.

Railway signalling devices are used to ensure the safety of trains running on the railroad network. With the passage of time, the technical state of railway signalling devices deteriorates. During the exploitation of these devices, processes dependent on changes in technical states and changes in exploitation states occur. Achieving the maximum efficiency in the operation of a railway signalling system requires a shift from traditional corrective servicing to preventive service based on ongoing diagnosis of the technical state of the devices involved in train movements. An even greater opportunity is provided by the introduction of mathematical modelling methods into the exploitation testing of railway signalling devices and the prediction of their basic reliability indices well in advance. The proposed method allows the exploitation strategies for the signalling systems to be changed from a service-life-based strategy to a current-technical-state-based strategy while ensuring the required safety level.

The article presents the optimisation of the production process proposed by the authors on the basis of the production process of the RHR-95 type drive optimised according to LEAN standards. This is a safety infrastructure element which is part of the system for securing railway and road crossings manufactured by ZA KOMBUD S.A. The final result is a presentation of the tangible benefits of optimising the production line according to LEAN assumptions and the impact on product quality after making changes to the production process.

A particularly important activity carried out by railway infrastructure managers to maintain railway devices in full working order is the diagnostic process. It increases the level of railway safety. The diagnostic process involves collecting information about the equipment through inspections, tests, functional trials, parameter measurements, and analysis of the working environment, followed by comparing the obtained information with the required parameters or permissible conditions. This activity also enables the formulation of a technical diagnosis regarding the current ability of the devices to perform its intended functions, taking into account the impact of its technical condition on railway traffic safety. This is especially important in the case of railway traffic control devices, as these devices are largely responsible for ensuring railway traffic safety. The collection of data on the condition of railway traffic control devices in the form of Big Data sets and diagnostic inference is an effective factor in making operational decisions for such devices. It enables the acquisition of complete information about the actual course of the exploitation process and allows for obtaining reliable information necessary to manage this process, particularly in the areas of diagnostics forecasting of devices conditions, renewal, and organization of maintenance and repair facilities. To support this, a service data acquisition and analysis system for railway traffic control devices (SADEK) was developed. This system can serve as a software platform for maintenance needs in the railway sector.