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This study aims to present a novel methodology for the evaluation of tribological properties of new nanocomposites with the A356 alloy matrix reinforced with aluminium oxide (Al₂O₃) nanoparticles.

Metal matrix nanocomposites (MMnCs) with varying amounts and sizes of Al₂O₃ particles were produced using a compocasting process. The influence of four factors, with different levels, on the wear rate, was analysed with the help of the design of experiments (DoE). A regression model was developed by using the response surface methodology (RSM) to establish a relationship between the observed factors and the wear rate. An artificial neural network was also applied to predict the value of wear rate. Adequacy of models was compared with experimental values. The extreme values of wear rate were determined with a genetic algorithm and particle swarm optimization using the RSM model.

The combination of optimization methods determined the values of the factors which provide the highest wear resistance, namely, reinforcement content of 0.44 wt.% Al₂O₃, sliding speed of 1 m/s, normal load of 100 N and particle size of 100 nm. Used methods proved as effective tools for modelling and predicting of the behaviour of aluminium matrix nanocomposites.

The specific combinations of the optimization methods has not been applied up to now in the investigation of MMnCs. In addition, using of small content of ceramic nanoparticles as reinforcement has been poorly investigated. It can be stated that the presented approach for testing and prediction of the wear rate of nanocomposites is a very good base for their future research.

This research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.

Since the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.

A novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.

By building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.

The purpose of the study is to examine the research problem that represents an attempt to approximate the importance of quality costing in managing a modern enterprise using the selected enterprises from small and medium-sized enterprises (SMEs) in Poland.

The primary goal of the research is a need to acquire knowledge about the use of quality cost accounts in enterprises operating in Poland. The research has been conducted in the SMEs of production and services. From October 2018 to December 2018, survey-based research was carried out in the selected SMEs of production and service in Poland. The targeted participants of the study are from the medium-sized enterprises, employing 50–250 people.

The pilot studies conducted in companies indicate that modern enterprises are focused on quality. Many enterprises declare to be continuously improving quality system and quality costing. However, generally, these are large companies that have implemented ISO standards, often part of international corporations. The survey result of the study shows that medium-sized enterprises still make little use of modern cost accounting variants. Based on the study, only 9.75% (39 enterprises) from a representative group of 400 companies from the sectors of manufacturing, services and production as well as service companies apply quality costing. Some of the other enterprises are only taking measures to implement quality cost accounting.

The research has been conducted in randomly selected SMEs in the form of a questionnaire interview. In order to further analyze the construction of quality cost management (QCM) systems and the use of information from QCM by enterprises, case study method should be used more widely.

The results of the study provide useful help for companies that are quality-oriented and want to implement quality costing. The survey has been conducted in 400 enterprises, and the survey results of considered SMEs reveal the most important aspects of the application of quality costing.

The questionnaire used, the answers provided and the resulting conclusions fill the identified research gap. In the author's opinion, findings of research are relevant and useful, not only for accounting practice but also for theory. They show that although TQM and quality costing have been very popular in the literature since the 1990s, the degree of application of quality costing in practice (except for large, often international companies) is too low. So, the suitability of QCM in managing a modern enterprise from the SMEs should be promoted.

This study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.

In this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).

The optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.

The MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.

Most studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.

The purpose of this paper is to analyze the individual steps during the printing of capacitor structures. The method of substrate preparation, the obtained roughness of conductive and dielectric layers are examined. Moreover, the capacitances of the obtained capacitors were examined.

Surface roughness and microscopic analysis were used to assess the quality of printed conductive structures. Two criteria were used to assess the quality of printed dielectric structures: the necessary lack of discontinuity of layers and minimal roughness. To determine the importance of printing parameters, a draft experimental method was proposed.

The optimal way to clean the substrate has been determined. The most important parameters for the dielectric layer (i.e. drop-space, table temperature, curing time and temperature) were found.

If dielectric layers are printed correctly, most problems with printing complex electronic structures (transistors, capacitors) will be eliminated.

The tests performed identified the most important factors for dielectric layers. Using them, capacitors of repeatable capacity were printed.

In the literature on this subject, no factors were found which were responsible for obtaining homogeneous dielectric layers.

This study aims to help nonprofit organizations (NPOs) implement business excellence models (BEMs). The authors identify and rank critical success factors and barriers to implementing BEMs among NPOs in Saudi Arabia and investigate the impact of human resources availability on BEM implementation in these organizations.

Based on the review of relevant literature, the authors designed a questionnaire completed by 138 NPOs. Factor analysis was used to measure and rank the criticality of success factors and barriers to BEM implementation. A Kruskal–Wallis nonparametric test was conducted to compare answers across groups classified by the number of full-time employees in the organization.

The study identifies the five most critical success factors for implementing BEMs in Saudi NPOs: data analysis and reporting capabilities, effective organizational communication, implementation strategy and approach, use of benchmarking and adoption of a clear governance framework. The five most critical barriers to implementing BEMs are the lack of a culture of continuous improvement, organizational strategy, qualified employees, customer orientation and clear organizational roles and responsibilities. The number of full-time employees in Saudi NPOs does not significantly impact the success or failure of implementing BEMs.

This paper is a continuation of research that aims to increase BEM adoption among NPOs, including micro-NPOs, in Saudi Arabia and, by extension, other countries.