The location of smart sustainable city multi-floor manufacturing (CMFM) directly in the residential area of a megapolis reduces the delivery time of goods to consumers, has a favorable effect on urban traffic and the environment, and contributes to the rational use of land resources. An important factor in the transformation of a smart city is the development of CMFM clusters and their city logistics nodes (CLNs); the key elements of the logistics system of a megapolis. The primary goal of this study was to examine the role of the CLN4.0, as a lead sustainability and smart service provider of a CMFM cluster within the Industry 4.0 paradigm, as well as its value in the system of logistics facilities and networks of a megalopolis. This paper presents an innovative model of a CLN4.0 under supply uncertainty using a material flow analysis (MFA) methodology, which allows for specific parameters of throughput capacity within the CMFM cluster and the management of supply chains (SCs) under uncertainty. The model was verified based on a case study (7th scenario) for various frameworks of a multi-floor CLN4.0. The validity of using a group of virtual CLNs4.0 to support the balanced operation of these framework operations under uncertainty, due to an uneven production workload of CMFM clusters, is discussed. The results may be useful for the decision-making and planning processes associated with supply chain management (SCM) within CMFM clusters in a megapolis.

The development of smart sustainable megapolises is associated with the formation of city multifloor manufacturing clusters (CMFMCs) in them directly in the residential area in order to reduce the supply chain from the manufacturer to consumers. Additive technologies (ATs) belong to green technologies because they are considered environmentally sustainable due to less production waste and the ability to reuse of product materials within the circular economy concept. Sustainable development of ATs and additive manufacturing management has become a priority sphere for scientific research, and the use of ATs in the city manufacturing has become any daily reality. Nevertheless, the issues of additive manufacturing management within the CMFMCs have not yet been sufficiently studied. The primary goal of this study was to examine the possibilities of additive manufacturing management in the CMFMCs of the megapolis due to the rational facilities multi-floor layout in production buildings, considering the structure of city manufacturing and business process reengineering related to the needs of the production services market. This paper presents a novel model of facilities multi-floor layout in the production buildings of the CMFMCs, considering the structure of city manufacturing, morphological analysis of the additive manufacturing equipment (AME) used, the balance of material and energy flows under infrastructure capacity limitations of megapolis. The model was verified based on a case study for various options of the floor-by-floor grouping of AME in a building of the CMFMCs. Management solutions for maintaining the flow balance of material, energy and water resources in the CMFMCs are discussed. The results may be useful for additive manufacturing management in an urban environment, taking into account the needs of the production services market in the megapolis.

The development of green production types such as personalized production and shared manufacturing, which use additive technologies in city multifloor manufacturing clusters (CMFMCs), has led to an increase in last-mile parcel delivery (LMPD) activity. This study investigates the integration of electric vehicles and crowdshipping systems into smart CMMCs to improve urban logistics operations related to the distribution of products to consumers. The aim of this study is to improve the LMPD performance of these integrated systems and to provide alternative solutions for sustainable city logistics using the potential of crowdshipping and vehicle sharing fleets (VSFs) in the city logistics nodes (CLNs) of CMFMCs. The issues presented by the loading–unloading operations and sustainable crowdshipping scenarios for LMPD in CMFMCs are considered. This paper presents a new performance evaluation model for crowdshipping LMPD in CMFMCs using VSFs. The case study shows that the proposed model enables the analysis of LMPD performance in CMFMCs, taking into account their finite production capacity, and that it facilitates the planning of cargo turnover and the structure of VSFs consisting of e-bicycles, e-cars, and e-light commercial vehicles (e-LCVs). The model is verified based on a case study for sustainable LMPD scenarios using VSFs. The proposed model enables the planning of both short- and long-term logistics operations with the specified performance indicator of VSF usage in CMFMCs. The validity of using the integrated potential of crowdshipping and vehicle sharing services for LMPD under demand uncertainty in CMFMCs is discussed. This study should prove useful for decision-making and planning processes related to LMPD in CMFMCs and large cities.

The article deals with the problems, disadvantages and advantages of using adaptive learning systems in interactive monitoring and assessment of knowledge. Methodical and technical aspects of interactive monitoring and assessment of knowledge based on the adaptive learning system are defined. The schemes of the algorithms based on which the learning process with simultaneous interactive monitoring and assessment of knowledge is realized is offered. Recommendations on the use of software products for the implementation of interactive monitoring and assessment of knowledge based on an adaptive learning system are proposed.

The development of smart sustainable cities is closely linked to the advancement of city manufacturing, which aims to meet local demand while maintaining economic, social, and environmental balance. This concept is realised in large cities through City Multifloor Manufacturing Clusters (CMFMCs) equipped with City Logistics Nodes (CLNs) that manage intra- and extra-cluster logistics. These flows depend on supplies arriving via Intermodal Logistics Nodes (ILNs) located on city outskirts, where disruptions caused by intermodal supply chain uncertainty can significantly affect production continuity and urban sustainability. This study aims to develop a stochastic inventory management model for city manufacturing clusters operating under intermodal supply chain uncertainty. The model is designed to ensure stable and resilient material supply to city manufacturers by optimising buffer stock (BS) levels, reducing delivery delays, and improving transport and storage efficiency. Based on the Multi-Layer Bayesian Network Method (MLBNM), the model integrates probabilistic reasoning and resilience principles to support decision-making under uncertainty. A simulation-based case study of a representative CMFMC system was used for model verification and validation. The results show that the MLBNM-based approach enhances Sustainable Supply Chain Resilience (SSCR), improves inventory flexibility, and reduces environmental impacts. The study contributes to theory and practice by providing a quantitative framework for ensuring resilient and sustainable inventory management in city manufacturing systems.

The article deals with the issues of engineering knowledge management for the formation of information and educational environment of the transport enterprise. The possibilities of transformation of information, experience and competence of engineering personnel into knowledge used for its group and individual training based on adaptive training system are analyzed.