Search

(1) Background: Industry 4.0 and the COVID-19 pandemic have resulted in an acceleration of digital transformation, primarily in production systems and logistics. This raises the need to assess where a company is in its digital transformation today and what measures must be taken to improve logistics processes. This article aims to present the results of a study assessing the digital maturity of logistics processes in a group of selected enterprises located in Poland. The research was conducted among companies that are business partners of the Poznan School of Logistics. (2) Methods: The DMM-OP digital process maturity assessment model was used in the study. Digital maturity was assessed on a five-point scale in four areas of company activity: process management, performance measurement, employee support, and technology. The research procedure included four stages. (3) Results: The results indicate that companies in the process management and performance measurement dimensions achieved the highest level of digital maturity. In commercial enterprises, the level of digital transformation is at the lowest level. Large enterprises achieved the best results, but there were also very good results in the group of small enterprises. (4) Conclusions: The results presented in the article can be used by industry and academia. The research was not statistical but can form the basis for benchmarking analyses.

(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.

This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning of the research, conducting a systematic review of the literature, proposing a classification framework corresponding to contemporary research trends related to the risk of drone applications, and compiling the characteristics of the publications assigned to each of the highlighted thematic groups. This systematic literature review used the PRISMA method. A total of 257 documents comprising articles and conference proceedings were analysed. On this basis, eight thematic categories related to the use of drones and the risks associated with their operation were distinguished. Due to the high content within two of these categories, a further division into subcategories was proposed to illustrate the research topics better. The conducted investigation made it possible to identify the current research trends related to the risk of drone use and pointed out the existing research gaps, both in the area of risk assessment methodology and in its application areas. The results obtained from the analysis can provide interesting material for both industry and academia.

(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.

Transport plays an important role in the economy of a given country or region [...]

The development of Industry 4.0 (I4.0) and the digitization and automation of manufacturing processes have created a demand for designing smart warehouses to support manufacturing processes. Warehousing is one of the fundamental processes in the supply chain, and is responsible for handling inventory. Efficient execution of warehouse operations often determines the effectiveness of realized goods flows. Therefore, digitization and its use in exchanging information between partners, especially real-time inventory levels, is critical. For this reason, the digital solutions of Industry 4.0 have quickly found application in internal logistics processes and enabled the design of smart warehouses, also known as Warehouse 4.0. The purpose of this article is to present the results of the conducted review of publications on the design and operation of warehouses using the concepts of Industry 4.0. A total of 249 documents from the last 5 years were accepted for analysis. Publications were searched for in the Web of Science database using the PRISMA method. The article presents in detail the research methodology and the results of the biometric analysis. Based on the results, a two-level classification framework was proposed, which includes 10 primary categories and 24 subcategories. Each of the distinguished categories was characterized based on the analyzed publications. It should be noted that in most of these studies, the authors’ attention primarily focused on the implementation of (1) Industry 4.0 technological solutions, such as IoT, augmented reality, RFID, visual technology, and other emerging technologies; and (2) autonomous and automated vehicles in warehouse operations processes. Critical analysis of the literature also allowed us to identify the current research gaps, which will be the subject of further research by the authors.

AGV systems are considered a necessary element of the recently created cyber-physical systems whose task is to support material flows in intelligent factories. The implementation of AGV systems in cyber-physical systems generates new types of threats, and the level of risk of adverse events related to the operation of these systems is changing. This article aims to present the results of an open-access literature review, the purpose of which was to identify issues addressed in studies of the analysis and risk management of AGV systems, to group publications according to the proposed topical framework, and to identify gaps in the current research. We used the PRISMA concept to review the literature. After completing all stages of the procedure, 153 publications on risk in AGV systems were selected for analysis. To ensure the high quality of the analysis, access to the full texts of the selected documents was necessary. For this reason, we have limited the collection to open-access publications. The results of the analysis allowed us to distinguish 12 primary categories and 26 additional subcategories within the literature. These categories are characterized by different numbers of publications and cover different AGV systems operation areas. The simultaneous assignment of documents to several subcategories indicates the need for a holistic view of issues related to the risk of AGV operation in operating environments with varying degrees of automation. An essential scientific contribution of our analysis is the identification of a research gap. The analyzed publications lacked studies on methods of risk identification and assessment that take into account the specificity of AGV operation, especially in the cyber-physical systems of Logistics 4.0.

The implementation of Industry 4.0 currently concerns mainly large enterprises. However, the economy of most European countries is based on the activities of small and medium-sized enterprises (SMEs). For this reason, the further development of the I4.0 concept and the technology of Logistics 4.0 depends on adjusting its assumptions to the needs of SMEs. The article aims to identify research areas regarding the adaptation of Industry 4.0 and Logistics 4.0 solutions to the needs of the SME sector, based on a review of the literature. The PRISMA method, one of the popular analytical methods used in a literature review, was used for the research. The selection of publications for the analysis was based on the Web of Science database, an important interdisciplinary research platform. Ninety-five publications were accepted for the final analysis, which concerned only the application of Industry 4.0 in SMEs and 10 publications on Logistics 4.0. The conducted studies of the literature allowed to identify the scope of research on the implementation of the concept of Industry 4.0 and Logistics 4.0 in the SME sector. The research allowed us to distinguish five thematic groups in total, which have been characterized. One of the identified groups concerns the adaptation of Logistics 4.0 systems to the needs of SMEs. The number of publications on this group of studies is minimal, therefore this area has been recognized as the currently existing research gap.

There has been growing interest in fuel supply chains regarding transport safety and LNG reloading. This is due to the increasing consumption of this gas in the economy to create sustainable transport systems. Poland is in the phase of energy transformation, which increases the demand for this type of alternative fuel. For this reason, the number of logistic operations carried out by Polish sea terminals handling LNG deliveries is increasing. This article aims to present a method for assessing the risk of adverse events occurring during the logistic handling of LNG deliveries at a port terminal and its implementation for a selected LNG terminal in Poland. Fuzzy logic methodology was used to assess the risk due to the lack of access to specific historical data on identified events. The conducted analysis considers the guidelines applicable at the LNG terminal, described in the Terminal Operation Manual, and the specific reloading conditions occurring in the tested Polish gas terminal. Based on the analysis conducted in cooperation with experts, scenarios of possible adverse events were identified and subjected to a risk assessment. Based on the conducted analysis, those events were distinguished and their risk of occurrence.

Services, unlike products, are intangible, and their production and consumption take place simultaneously. The latter feature plays a crucial role in mitigating the identified risk. This article presents the new approach to risk assessment, which considers the first phase of introducing the service to the market and the specificity of UAV systems in warehouse operations. The fuzzy logic concept was used in the risk analysis model. The described risk assessment method was developed based on a literature review, historical data of a service company, observations of development team members, and the knowledge and experience of experts’ teams. Thanks to this, the proposed approach considers the current knowledge in studies and practical experiences related to the implementation of drones in warehouse operations. The proposed methodology was verified on the example of the selected service for drones in the magazine inventory. The conducted risk analysis allowed us to identify ten scenarios of adverse events registered in the drone service in warehouse operations. Thanks to the proposed classification of events, priorities were assigned to activities requiring risk mitigation. The proposed method is universal. It can be implemented to analyze logistics services and support the decision-making process in the first service life phase.

The article focuses on research on the functioning of liquid fuel supply chains, supplying troops carrying out peacekeeping and stabilisation operations in a foreign territory. Timely and complete supplies of fuels in war conditions determine the achievement of the assumed goals of a military operation. They often determine the health and life of soldiers. For this reason, the role of building the resilience of supply chains to disruptions, the type and frequency of which is entirely different from the undesirable events occurring in civil goods flows, is increasing. Therefore, the critical concept supporting building the resilience of fuel supply chains is risk management in these chains. The authors have developed a risk analysis method that integrates the Kaplan and Garrick approach and the fuzzy theory. The analysis identifies the existing disturbances and assigns them to the individual phases of the supply process. To illustrate the applicability of the proposed method, the authors analyse nine scenarios for the three most important stages of the procurement process in terms of building the resilience of the entire chain: Planning, delivery and storage. The fuzzy theory estimates the risk level for the analysed scenarios of adverse events. The proposed method is universal. It can be implemented to analyse the resistance of supply chains of other materials. It can also support the decision-making process for those responsible for planning, organisation and proper functioning of supply systems in all high-risk conditions, not only in the zone of war and stabilisation operations.

The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan’s and Garrick’s approach and fuzzy theory. The proposed approach takes into account the level of automation of the operating mining processes. Moreover, it follows five main steps, including identifying the automation level in a selected mine, definition of cyber-attack targets, identification of cyber-attack techniques, definition of cyber-attack consequences, and risk ratio assessment. The proposed risk assessment procedure was performed according to three cyber-attack targets (databases, internal networks, machinery) and seven selected types of cyber-attack techniques. The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry. To illustrate the given method’s applicability, seven scenarios for three levels of mine automation are analyzed. The proposed method may be used to reveal the current cybersecurity status of the mine. Moreover, it will be a valuable guide for mines in which automation is planned in the near future.

The new generation Manufacturing Executions System (MES) is considered as one of the most important solutions supporting the idea of Industry 4.0. This is confirmed by research conducted among companies interested in the implementation of the Industry 4.0 concept, as well as the publications of researchers who study this issue. However, if MES software is a link that connects the world of machines and business systems, it must take into account the specifics of the supported production systems. This is especially true in case of production systems with a high level of automation, which are characterised by flexibility and agility at the operational level. Therefore, personalization of the MES software is proposed for this class of production systems. The aim of the article is to present the MES system personalization method for a selected production system. The proposed approach uses the rules of Bayesian inference and the area of customisation is the technological structure of production, taking into account the required flexibility of the processes. As part of the developed approach, the variability index was proposed as a parameter evaluating the effectiveness of the production system. Then, the results of evaluation of the current system effectiveness by use of this index are presented. The authors also present the assumptions for the developed MES personalization algorithm. The algorithm uses the rules of Bayesian inference, which enable multiple adjustments of the model to the existing environmental conditions without the need to formulate a new description of reality. The application of the presented solution in a real facility allowed for determining production areas which are the determinants of system instability. The implementation of the developed algorithm enabled control of the generated variability in real time. The proposed approach to personalization of MES software for a selected class of production systems is the main novelty of the presented research and contributes to the development of the described area of research.

Enterprises today are increasingly seeking maintenance management strategies to ensure that their machines run faultlessly. This problem is particularly relevant in the mining sector, due to the demanding working conditions of underground mines and machines and equipment-operating regimes. Therefore, in this article, the authors proposed a new approach to mining machinery maintenance management, based on the concept of risk-based maintenance (RBM) and taking into account safety issues. The proposed method includes five levels of analysis, of which the first level focuses on hazard analysis, while the next three are connected with a risk evaluation. The final level relates to determining the RBM recommendations. The recommendations are defined in relation to the three main improvement areas: maintenance, safety, and resource availability/allocation. The proposed approach is based on the use of fuzzy logic. To present the possibilities of implementing our method, a case study covering the operation of selected mining machinery in a selected Polish underground mine is presented. In the case of mining machinery, fourteen adverse-event scenarios were identified and investigated; general recommendations were also given. The authors have also indicated further directions of research work to optimize system maintenance strategies, based on the concept of risk-based maintenance. Additionally, the discussion about the implementation possibilities of the approach developed herein is provided.