Bulletin of the Polytechnic Institute of Iași. Materials Science and Engineering Section

METHODS AND TECHNIQUES USED IN THE DEVELOPMENT OF CERAMIC-REINFORCED PHOTOPOLYMER COMPOSITES FOR 3D PRINTING

Denisa-Andreea Sarbu (Cretu) — 2026-10-30

Abstract. Ceramic-reinforced photopolymer composites have attracted considerable attention for additive manufacturing applications in regenerative medicine, digital dentistry, and biomedical engineering. The incorporation of ceramic fillers into photocurable resin systems enables the fabrication of structures with enhanced mechanical properties, dimensional stability, bioactivity, and antimicrobial functionality. However, the successful processing of these materials by stereolithography (SLA), digital light processing (DLP), and LCD-based technologies requires careful control of suspension composition, rheological behavior, photopolymerization kinetics, and post-processing conditions. This paper reviews the principal methods and techniques employed in the development of ceramic-filled photopolymer composites. Particular attention is devoted to resin formulation, ceramic filler selection, suspension preparation, particle surface modification, and characterization techniques including SEM, EDS, XRD, UV-Vis spectroscopy, rheological analysis, thermal characterization, and mechanical testing. The relationships among particle size distribution, curing behavior, microstructure, and final properties are discussed. Current challenges and future research directions are also highlighted, emphasizing multifunctional and biocompatible materials for advanced biomedical applications.

HUMAN RESOURCE MANAGEMENT'S RISK-PERSPECTIVE

Mihai Doru Buliga — 2026-10-30

The process of identifying and assessing risk based on human characteristics, followed by the development of plans for strategic human resource management, is known as risk management to human factor. The value of risk management in human resources has grown significantly in the modern era, and some experts even characterize it as an essential ability and function for each human resources practitioner. At this point in technical advancement, when artificial intelligence is practically ingrained in corporate culture, human factors remain crucial in the majority of operations and duties accomplished by organizations. This study aims to investigate the framework for human resource risk management in public sector (customs) and the various components which impact it. To define the study we used as research methods: the system approach, analysis, and synthesis by examining existing literature and collecting data, and also we utilized an descriptive statistics. As the main results in the framework, we highlighted, the main disadvantages for the public sector regarding the recruitment of human resources in customs field - absence of a unique curriculum in colleges and universities for customs area, as likewise currently happening concerning the state's other national security agencies European Union, the incompatibility of previous training with the requirements of the current job description of customs officer - it establishes a lower level of productivity at work and also, the absence of continuous, professionally-focused training program.In line with an existing human resources management system that can address an extensive spectrum of needs in the customs activity field - We believe that the opportunity is appropriate to implement a few adjustments such as a better staff recruitment campaign depending on the real needs of the departments (e.g. for IT departments is inappropriate a psychologist) will give the administration of human resources in the customs sector an updated aproach and even can be laid a new level of performance in human resureces management.

COMPARATIVE ANALYSIS OF RCM AND FMEA IN THE CONTEXT OF ECO-MAINTENANCE SUSTAINABILITY AND CIRCULAR ECONOMY

Denisa Alexandra Nica — 2026-10-30

Environmental challenges, particularly those relating to waste disposal from industrial processes, are increasing around the world and therefore require the adoption of sustainable maintenance techniques. The notion of eco-maintenance is the application of environmentally conscious approaches in equipment maintenance to reduce waste, conserve resources, and extend the useful life of the machinery, practices consistent with sustainability and circular economy. This research compares two maintenance systems, namely Reliability Centered Maintenance (RCM) and Failure Mode, Effects, and Criticality Analysis (FMECA) under eco-maintenance philosophy. While FMECA enables anticipation of potential failure modes and their prevention by prioritizing risks through Risk Priority Number (RPN), it can be time-consuming and complex. RCM offers maintenance strategies that lead to reduced consumption of resources while maximizing the useful life of the equipment, although extra cost will be incurred in the initial stages.

Innovation: Assessing the variables influencing business process and product innovation

Andreea-Gabriela Gradinaru — 2026-10-30

Innovation has become a must for companies to improve their organizational resilience, to increase their financial performance and to respond to external challenges. Based on the object being innovated, innovation can be classified in two types: product innovation and business process innovation. A product innovation can trigger the need for a business procees innovation, resulting in the two types being intertwined in practice. Since innovation triggers economic growth, both companies and countries are looking into generating more innovation by policies, activities and funding. To evaluate whether their endeavours are reaching their targeted goals, they need to measure innovation. Organisation for Economic Co-operation and Development (OECD)/Eurostat are providing a standardized approach to evaluate innovation across organizations and countries, enabling not only measurement, but also comparative analysis between entities. This approach includes a standardized questionnaire, which is applied in more than 80 countries, and is continuously improved based on the feedback obtained. The results obtained by applying this questionnaire, which were published by OECD, represent the data used in this research. By using a quantitative methodology, this study explores the variables that influence business process innovation and product innovation. The hypotheses are multifold and have been tested using statistical methods. Firstly, the study analyses whether the research and development (R&D) expenditures influence both business process innovation (H1) and product innovation (H2). Hypotheses H1 and H2 are invalidated by statistical means. Secondly, the research assesses whether the share of persons employed in innovation-active firms, in total employment in 2020, has an influence on both business process innovation (H3) and product innovation (H4). Both hypotheses (H3, H4) are validated statistically, showing a positive influence between the analysed variables. Thirdly, the study proves whether the turnover of the firms is influenced by product innovation (H5) and by business process innovation (H6). Hypotheses H5 and H6 are validated statistically. The conclusions of this research expand the existing scientific knowledge in innovation, by revealing the relationships between business process innovation, product innovation, R&D expenditure, share of employees and turnover of the firms. It also provides recommendations for managers aiming to increase innovation and turnover.

Responsible Artificial Intelligence and Sustainable Management Practices in the Context of Industry 5.0

Petrina-Delia Vagiuc — 2026-10-30

Based on the idea of the Industry 5.0 paradigm, Artificial Intelligence (AI) is used for more than automation; it supports collaboration and sustainable organizational operations. The present paper focuses on the concept of responsible AI, highlighting the importance of moral values, transparency, ecological management, and social responsibility. Through a qualitative approach based on reviewing the academic literature and analyzing representative organizational practices, the study identifies principles and ways to apply responsible AI. The findings suggest that responsible AI helps organizations make better decisions, use resources more efficiently, support workers’ well-being, and build trust with stakeholders by using clear, sustainability-focused practices. In this way, organizations need to increasingly integrate the human-centered principles of Industry 5.0 into their strategic approaches. To implement Industry 5.0, a balanced approach is needed between the responsible use of artificial intelligence and sustainable management practices. This study offers a conceptual starting point for researchers and organizations that supports this direction.