Dear Readers, We are pleased to announce the third 2021 issue (No. 67) of the Scientific Journals of the Maritime University of Szczecin. This issue features novel findings and perspectives in the following areas: Civil Engineering and Transport, Environmental Engineering, Mining and Energy, Material and Mechanical Engineering, Economics, Management and Quality Science, and Information and Communication Technology. The Civil Engineering and Transport section features two articles. The main research objective in the first study was to identify and propose new risk assessment tools. A maritime accident involving a Cosco Busan container ship that struck the base of the Delta Tower of the San Francisco-Oakland Bay Bridge in November 2007 was chosen as an example. An analysis of the factors that led to the accident was conducted, and the effects of the accident were outlined. On that basis, a risk analysis using mathematical and tabular values related to navigational risk in a specific navigation region was performed. Drones and their potential uses in the maritime sector by various entities, including ship classification societies, shipyards, and search and rescue (SAR) missions, was the subject of the second study. The benefits and limitations of drone implementation were highlighted, and a plan for the use of drones in shipping was presented. Projections of drone applications in the maritime sector in Poland, in the West Pomeranian Voivodeship and Pomeranian Voivodeship, were also made. The Environmental Engineering, Mining, and Energy section contains an article discussing waste treatment methods to identify the best method to reprocess (recycle) polyurethane (PUR). Glycolysis was concluded to be the most promising process for polyurethane waste management. The research material was produced by the glycolysis of scrap polyurethane foam. Based on the research, analysis, and testing, it was concluded that the most suitable reaction conditions for the recovery of polyols from scrap were: a temperature range of 170–190°C, alkaline pH, and an air atmosphere, which were the same for all samples. The Material and Mechanical Engineering section contains two articles. In the first study, the influence of the stern wedge length and height on hull drag and trim to glide in calm water was examined. For this purpose, liquid flow was simulated with Star-CCM+ software using a shifted mesh model and a turbulent k-ε model. The stern wedge sat below and near the stern perpendicular to the hull to facilitate moderate spread. To evaluate the hydrodynamic properties of the hull at different speeds, different wedge lengths of 0.2 B, 0.5 B, and B were investigated at two different heights of 5 mm and 10 mm. The trim angle, resistance, water surface elevation, porpoising, roster tail, and the stern and bow were computed and analyzed. The results showed that as the length of the wedge increased, the drag and trim decreased. It was also found that the best wedge for a vessel with the desired wake generation was one with a length of 0.2 B and a height of 5 mm. The author of the second study argued that the good quality of composite castings can be mainly attested by their user. In his research, he presented the casting defect porosity, with particular emphasis on the porosity in suspensions and saturated metal composites. The purpose of the study was to detect and analyze the porosity in composites using microscopic and sub-microscopic methods. Three articles are featured in the Economics, Management, and Quality Science section. The author of the first study shows that the increasing unpredictability of socioeconomic or biological changes (e.g., the SARSCoV-2/COVID 19 pandemic), the multidirectional nature of their impact, the variability of their intensity, and the uncertainty in estimating their potential impacts, made it difficult for supply chains to stably operate. This reality demonstrates the great unreliability of the classical economic measuring instruments and methodologies used in management and quality sciences. This observation sparked an attempt to produce a sample set of expectations for contemporary supply chains that are particularly appropriate for emerging market challenges in the form of threat and condition megatrends, including those illuminated during the SARS-CoV-2/ COVID-19 pandemic. The author suggests a holistic perspective on the nature of the supply chain system and its processes. The proposed approach, based on an interpretive (qualitative) research method enhanced by an idiographic nomothetic approach, is treated as a creative alternative that does not exclude other ways of perceiving the supply chain. The research subject of the second study was the relationship between the characteristics of consumer product demand and the profitability of the purchasing strategy, considering both the supply source and the transportation technology. A model was developed for two demand distributions (Gaussian and gamma), varying sales fluctuations, and changes in demand during delivery. Then, Monte Carlo simulations were performed by considering transportation costs, warehousing costs, capital costs associated with maintaining inventory, and lost sales costs. The simulation results showed that the higher the fluctuation and the lower the demand predictability, the more profitable the air freight and local deliveries. The calculated results further indicated that the strategy of outsourcing production in low-cost countries will, in many cases, become unprofitable if the production costs in such countries grow even marginally. Team coaching was the research problem in the third study. The goal was to present a team development process using the High Performance Team Coaching Model. The first part of the article characterized the theoretical essence of team coaching and the specifics of the team coaching process, along with the specific tools at each stage. In the second section of the article, the author explains the process for implementing the High Performance Team Coaching Model in business practice. The Information and Communication Technology section features a study on the use of artificial neural networks (ANNs) to solve image classification problems. SHREC (Automatic Ship Recognition and Identification) projects were used to classify and identify ships based on images obtained from CCTV cameras. The authors collected an image dataset of ships during the 2018, 2019, and 2020 video survey campaigns and utilized three pre-trained neural networks, GoogLeNet, AlexNet, and SqeezeNet, to explore the classification feasibility and then assess their quality. About 8,000 ship images were used, which were divided into seven categories: barges, special-purpose service vessels, motor yachts with motorboats, passenger ships, sailing yachts, canoes, and others. The authors compared the results obtained using neural networks to classify floating inland vessels. The articles in this issue show the continuous theoretical and practical inspiration of the authors, contributing to important and current scientific investigations. I encourage you to read these articles in the hopes that they will be of interest to you and that they will stimulate debate and inspire you to undertake research, not only in the discussed areas but also on an interdisciplinary level.

This study discusses the marine accident involving the Cosco Busan, the container ship that hit the base of the Delta Tower of the San Francisco-Oakland Bay Bridge in November 2007. An analysis of the elements resulting in the accident and its consequences has been carried out, followed by an analysis of the navigational risk using mathematical and tabular values. Mathematical values refer to the navigational risk in a specific sailing area, while tabular values refer to the navigational risk using a risk assessment. The main goal of this research was to identify and propose new measures that are correlated with a risk assessment. These measures should be applied in areas where an accident takes place so that future marine accidents can be reduced.

Drones are entering the maritime sector and have successfully increased safety and security. They can effectively replace humans, and where life and health are at risk during operations such as tank or hull inspections, they can be used in a fully remote capacity. They are used to transport spare parts, documents, medicine, etc. between land and ships at sea or on the roadstead, which may increase safety during the COVID-19 pandemic. Drones can control traffic and the emission of pollutants from ships, detect pirates, monitor areas, and support operations. They are used in search and rescue missions and also provide modern technologies like 5G and others. Drones are reliable and effective, and their use minimizes costs and reduces time. This paper presents a current review of the state of knowledge on the use of drones in the maritime sector. It takes into consideration the opportunities of their utilisation and presents possibilities and examples of successful drone exploitation by various entities such as classification societies, shipyards, search and rescue (SAR) missions, and others. The benefits and limitations and a roadmap for drones in shipping are also analysed. An application forecast for the Polish maritime sector in the West Pomeranian and Pomeranian Regions is also delivered in the paper. Desk research methodology was used to review the literature to identify the set goals by analysing literature reports, articles, and materials published by beneficiaries using drones successfully, as well as inquiries and market offers.

The main objective of this article was to provide an overview of the polyurethane industry and waste treatment methods to identify the best method for polyurethane (PUR) reprocessing (recycling). To understand the need for recycling, existing knowledge will be referenced. Many literature studies discuss the role of recyclates in the polyurethane industry. According to these, the best available options to recapture value, for example, from raw materials, are polyurethane recycling and energy recovery. The research material was created via the glycolysis of polyurethane foam scrap. The experiments in this work include the glycolysis of polyurethane foam with a complex discussion of materials (polyurethane foam, glycols, catalysts, and properties of the obtained recyclate). Based on the research, analyses, and tests carried out related to glycolysis, the most appropriate conditions to recover polyols from scrap were the following reaction conditions: temperature 170–190°C; pH – basic; and atmosphere (air), which was the same for all samples. A total of 14 samples were tested. Two samples GL:12 [6:1] and GL 13 [8:1] were futher investigated. The numbers presented in brackets [6:1] mean that a ratio of 180 g of polyurethane foam and 30 g 1-3-propyleneglycol was used. The outstanding properties of glycolysate samples called GL:12 [6:1] and GL 13 [8:1] were achieved thanks to the ranges of the basic parameters (dosage time, time after dosage). The sample GL:12 [6:1] – dosage time 20 min and time after dosage 15 min and the GL 13 [8:1] sample – dosage time 22 min and time after dosage 15 min. The apparatus used for glycolysis included: reactor +heater, stirrer, feeder, reflux condenser, thermocouple, and temperature regulator. By analyzing the obtained results, it can be concluded that the most promising polyurethane waste management process is glycolysis.

This paper examines the effect of the stern wedge length and height on the drag and trim of a chine-planing hull in calm water. To this end, fluid flow was simulated by Star-CCM+ software by applying an overset mesh and k-ε turbulent model. The finite volume method was used to discretize the fluid domain, and the fluid volume was utilized to capture the generated free surface. The considered model is a prismatic planing hull with a deadrise angle of 24°, a mass of 86 kg, a length (L) of 2.64 m, and a beam (B) of 0.55 m. For validation, the numerical results of drag and trim were compared against experimental data, which displayed good compliance. Subsequently, the hydrodynamic performance of the planing hull was investigated, and the wedge effect was assessed. The stern wedge was located at the bottom and near the aft perpendicular to the hull to facilitate a moderate distribution. Various wedge lengths of 0.2B, 0.5B, and B at two different heights of 5 mm and 10 mm were examined to assess the hydrodynamic performance of the hull at various speeds. The trim angle, resistance, water surface elevation, porpoising, roster tail, and the stern and bow were computed and analyzed. Based on the numerical results, it was concluded that when the wedge length increased, the drag and trim were reduced. It was also concluded that the best wedge for a vessel with desirable wake generation is one with a length of 0.2B and a height of 5 mm.

Good quality in composite castings can be confirmed primarily by their user. The producer is obliged to create a good product that meets the user’s needs that should undergo quality control. Omission of technological procedures and improper quality control may result in various defects like porosity. This paper presents the characteristics of the casting defect, namely porosity, with a particular focus on porosity in suspension and saturated metal composites. This defect is different, specific to composite castings, making its identification very difficult. The aim of the study is to detect and describe porosity in composites with the use of microscopic and submicroscopic examinations. The assessment of the porosity of the microstructure of composite castings allowed for the formulation of the following conclusions: in addition to the porosity that occurs in castings of classic materials (cast steel, cast iron, and non-ferrous metal alloys), metal composites also distinguish between primary and secondary agglomerates, leaving the reinforcement space not filled, occluded bubbles, and separated gas bubbles.

The progressive unpredictability of socio-economic or biological changes (e.g. the SARS-CoV-2/COVID 19 pandemic), the multi-directional nature of their impact, the variability of intensity, and the uncertainty in estimating potential effects hinders the stable and planned operation of modern supply chains. This irreversible situation proves the high unreliability of existing traditional measuring instruments of classical economics and the methods used so far in the field of management and quality sciences. This article aims to present an exemplary set of expectations towards contemporary supply chains that are particularly relevant to the emerging market challenges in the form of mega-trends of threats and conditions, also those particularly emphasized during the SARS-CoV-2/COVID-19 pandemic. It is primarily a pandemic (taken as a critical exogenous factor) resulting in severe “disorders” in supply chains. The actual level of supply chain resilience depends on its inherent characteristics and is termed “vulnerabilities”, while an active supply chain response to emerging “disorders” is treated as its “resilience”. For these reasons, the author proposes a holistic view of the nature of the supply chain system and its processes. The proposed approach, based on the method of interpretative (qualitative) research enriched with the idiographic nomothetic approach, is treated as a creative alternative that does not exclude other possibilities of perception of the supply chain, but, in its intellectual diversity, complements other methods of understanding its system, processes, and logistics management. Such an approach with a dominant hypothetical-inductive The progressive unpredictability of socio-economic or biological changes (e.g. the SARS-CoV-2/COVID 19 pandemic), the multi-directional nature of their impact, the variability of intensity, and the uncertainty in estimating potential effects hinders the stable and planned operation of modern supply chains. This irreversible situation proves the high unreliability of existing traditional measuring instruments of classical economics and the methods used so far in the field of management and quality sciences. This article aims to present an exemplary set of expectations towards contemporary supply chains that are particularly relevant to the emerging market challenges in the form of mega-trends of threats and conditions, also those particularly emphasized during the SARS-CoV-2/COVID-19 pandemic. It is primarily a pandemic (taken as a critical exogenous factor) resulting in severe “disorders” in supply chains. The actual level of supply chain resilience depends on its inherent characteristics and is termed “vulnerabilities”, while an active supply chain response to emerging “disorders” is treated as its “resilience”. For these reasons, the author proposes a holistic view of the nature of the supply chain system and its processes. The proposed approach, based on the method of interpretative (qualitative) research enriched with the idiographic nomothetic approach, is treated as a creative alternative that does not exclude other possibilities of perception of the supply chain, but, in its intellectual diversity, complements other methods of understanding its system, processes, and logistics management. Such an approach with a dominant hypothetical-inductive character allows for creating a platform for broader scientific discussions, positioning itself in the sphere of simplifying reality or creating a theoretical construct for the possibility of formulating the foundations of the preliminary theory. These considerations lead to the conclusion that such an attempt at a new, broader perspective, both at the emerging threats and vulnerability, is related to the level of risk, demonstrating that the Supply Chain Critical Functionality is a consequence of many different factors, including time, costs, and delays in deliveries. Such a view allows for a more comprehensive systematization of the epistemological layer in the area of directional perception and application of logistics, showing many similarities but also significant differences with phenomena that are characteristic of other areas of logistics application and the perception of the conditions for the functioning of modern supply chains. character allows for creating a platform for broader scientific discussions, positioning itself in the sphere of simplifying reality or creating a theoretical construct for the possibility of formulating the foundations of the preliminary theory. These considerations lead to the conclusion that such an attempt at a new, broader perspective, both at the emerging threats and vulnerability, is related to the level of risk, demonstrating that the Supply Chain Critical Functionality is a consequence of many different factors, including time, costs, and delays in deliveries. Such a view allows for a more comprehensive systematization of the epistemological layer in the area of directional perception and application of logistics, showing many similarities but also significant differences with phenomena that are characteristic of other areas of logistics application and the perception of the conditions for the functioning of modern supply chains.

The problem presented in this article concerns the impact of demand characteristics for consumer goods on the profitability of purchasing strategy, including the choice of both the source of supply and transport technology (deliveries in containers by sea, rail, air, and road transport). To assess the profitability of applying a specific strategy, the author developed a model to conduct simulations using the Monte Carlo approach for two demand distributions (Gaussian and Gamma), various sales fluctuations, and changes in demand during the delivery time. Calculations were carried out considering the costs of transport, storage, capital costs related to maintaining stocks, and costs of lost sales. The simulation results show that the greater the fluctuations and the lower the predictability of the demand, the greater the profitability of deliveries using air transport and local deliveries. However, concrete decisions depend on knowledge of the consequences of making these decisions and whether appropriate cost accounting is used in enterprises. The results of the calculations also indicate that the strategy of outsourcing production in low-cost countries will, in many cases, become unprofitable if production costs in these countries increase even slightly.

Team coaching is currently used as a tool to help businesses cope with the process of managing team maturity. This article aims to present a team development process based on the High Performance Team Coaching Model. In the first part of the article, the theoretical essence of team coaching and the specificity of the team coaching process is characterized, together with detailing specific tools at each stage. In the second part of the article, the author describes the implementation process of the High Performance Team Coaching Model in business practice. The main research methods used in the article include literature studies and a case study based on the author’s observations and experience working as a coach/trainer in a project team.

Artificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained networks already available. The aim of the SHREC projects (automatic ship recognition and identification) is to classify and identify the vessels based on images obtained from closed-circuit television (CCTV) cameras. For this purpose, a dataset of vessel images was collected during 2018, 2019, and 2020 video measurement campaigns. The authors of this article used three pre-trained neural networks, GoogLeNet, AlexNet, and SqeezeNet, to examine the classification possibility and assess its quality. About 8000 vessel images were used, which were categorized into seven categories: barge, special-purpose service ships, motor yachts with a motorboat, passenger ships, sailing yachts, kayaks, and others. A comparison of the results using neural networks to classify floating inland units is presented.