Dissecting a human cadaver is an irreplaceable practice in general training of medical students. Cadavers in anatomy laboratories are usually preserved in formalin, an embalming fluid whose basic component is formaldehyde (FA). The aim of this study is to assess the cancer risk of employees and students that are exposed to FA based on the results of three monitoring campaigns, as well as to suggest permanent solutions to the problem of FA exposure based on the results obtained. Three sampling campaigns of formaldehyde concentration in indoor environments were conducted at five different locations at the Anatomy Department of the Faculty of Medicine with the purpose of assessing permanent employees’ and medical faculty first year students’ exposure to FA. Indoor air was continuously sampled during 8 h of laboratory work and analyzed in accordance with the NIOSH Method 3500. Exceeding of the 8 h time-weighted average (8 h TWA) values recommended by Occupational Safety and Health Administration (OSHA) of 0.75 ppm was recorded in 37% of the samples during the three-month monitoring campaign. Cancer risk assessment levels for permanent employees were in the range from 6.43 × 10⁻³ to 8.77 × 10⁻⁴, while the cancer risk assessment levels for students ranged from 8.94 × 10⁻⁷ to 1.83 × 10⁻⁶. The results of the research show that cancer risk assessment for employees is several thousand times higher than the limit recommended by the EPA (10⁻⁶) and point to the importance of reducing exposure to formaldehyde through the reconstruction of the existing ventilation system, continual monitoring, the use of formaldehyde-free products, and plastination of anatomical specimens.

In the last decade, researchers have focused on digital technologies within Industry 4.0. However, it seems the Industry 4.0 hype did not fulfil industry expectations due to many implementation challenges. Today, Industry 5.0 proposes a human-centric approach to implement digital sustainable technologies for smart quality improvement. One important aspect of digital sustainability is reducing the energy consumption of digital technologies. This can be achieved through a variety of means, such as optimizing energy efficiency, and data centres power consumption. Complementing and extending features of Industry 4.0, this research develops a conceptual model to promote Industry 5.0. The aim of the model is to optimize data without losing significant information contained in big data. The model is empowered by edge computing, as the Industry 5.0 enabler, which provides timely, meaningful insights into the system, and the achievement of real-time decision-making. In this way, we aim to optimize data storage and create conditions for further power and processing resource rationalization. Additionally, the proposed model contributes to Industry 5.0 from a social aspect by considering the knowledge, not only of experienced engineers, but also of workers who work on machines. Finally, the industrial application was done through a proof-of-concept using manufacturing data from the process industry, where the amount of data was reduced by 99.73% without losing significant information contained in big data.

Nowadays every piece of working equipment and tools has to comply with safety standards and laws. This study investigated multi-criteria methods for selecting working equipment in order to optimize performance and occupational safety. The multi-criteria decision-making (MDCM) method was applied to the problem of selecting optimal working equipment using four different criterion weighting approaches (direct weighting, revised Simos procedure, Fuller’s triangle and analytic hierarchy process). Groups of economic, technical and safety criteria were defined and five weighting scenarios were developed. Although the four weighting methods produced similar results, in some situations they produced different criterion weighting factors. The final output of the MCDM method was the identification of the optimal forklift in the five weighting scenarios. Although we have applied the MCDM method to a forklift selection problem, it can be applied to all sorts of working equipment in contexts where economic, technical and safety selection criteria can be identified.

Even though Industry 4.0 is primarily focused on the implementation of advanced digital technologies, this is not the only aspect that should be considered. One of the aspects that calls for attention is the ability to create a sustainable and agile industrial environment. In this sense, the role of project management is crucial for achieving business excellence in a new industrial paradigm. The main goal of this paper was to determine the impact of different levels of project management maturity on business excellence in the context of Industry 4.0. The research in the paper was made using a sample of 124 organizations, differing in industry type and size, and recognized through the business excellence awards or recognitions given by European Foundation for Quality Management (EFQM). Using the Project Management Maturity Model (ProMMM), a significant connection was found between project management maturity and business excellence. Considering technology advances, these relationships were further examined in the context of Industry 4.0. Empirically based conclusions were drawn, which contribute to the literature on project management and business excellence in the context of Industry 4.0. Practitioners can implement them for more effective project management with the intention of bringing excellence into the organization’s operations and results. Additionally, they can be useful to help organizations better cope with changing technology trends.