Polypropylene (PP) parts produced by means of extrusion-based additive manufacturing, also known as fused filament fabrication, are prone to detaching from the build platform due to their strong tendency to shrink and warp. Apart from incorporating high volume fractions of fillers, one approach to mitigate this issue is to improve the adhesion between the first deposited layer and the build platform. However, a major challenge for PP is the lack of adhesion on standard platform materials, as well as a high risk of welding on PP-based platform materials. This study reports the material selection of build platform alternatives based on contact angle measurements. The adhesion forces, investigated by shear-off measurements, between PP-based filaments and the most promising platform material, an ultra-high-molecular-weight polyethylene (UHMW-PE), were optimised by a thorough parametric study. Higher adhesion forces were measured by increasing the platform and extrusion temperatures, increasing the flow rate and decreasing the thickness of the first layer. Apart from changes in printer settings, an increased surface roughness of the UHMW-PE platform led to a sufficient, weld-free adhesion for large-area parts of PP-based filaments, due to improved wetting, mechanical interlockings, and an increased surface area between the two materials in contact.

Human-centricity, sustainability, and resilience are the core pillars of the Industry 5.0 concept. The human-centric perspective emphasizes the development of socio-technical systems designed to enhance human health, safety, and well-being while fostering sustainable practices that benefit society at large. This paper presents a systematic literature review to identify the key characteristics of human-centered work environments. The findings reveal growing interest in human factors and ergonomics, with notable gaps in cognitive ergonomics requiring further attention. Beyond ensuring safety and health, human-centric systems must address cognitive workload and well-being to maintain productivity, efficiency, and motivation, which are closely tied to a company’s market performance. This study provides valuable insights for both scientific and industrial stakeholders, outlining the principles and requirements essential for the effective implementation of human-centric systems.

The study investigates how the presence of traffic signalling elements (road markings and traffic signs) affects the behaviour of young drivers in night-time conditions. Statistics show that young drivers (≤30 years old) are often involved in road accidents, especially those that occur in night-time conditions. Among other factors, this is due to lack of experience, overestimation of their ability or the desire to prove themselves. A driving simulator scenario was developed for the purpose of the research and 32 young drivers took two runs using it: (a) one containing no road markings and traffic signs and (b) one containing road markings and traffic signs. In addition to the driving simulator, eye tracking glasses were used to track eye movement and an electrocardiograph was used to monitor the heart rate and to determine the level of stress during the runs. The results show statistically significant differences (dependent samples t-test) between the two runs concerning driving speed, lateral position of the vehicle, and visual scanning of the environment. The results prove that road markings and traffic signs provide the drivers with timely and relevant information related to the upcoming situation, thus enabling them to adjust their driving accordingly. The results are valuable to road authorities and provide an explicit confirmation of the importance of traffic signalling for the behaviour of young drivers in night-time conditions, and thus for the overall traffic safety.

With the introduction of Society 5.0 for the sustainable future, special caution is given to humans’ role within the general system. Similarly, Industry 5.0 as a concept has been presented, followed by Logistics 5.0 in its theoretical framework. The transition towards the new concept of Logistics 5.0 requires an accurate and optimal strategic plan definition for which, in this paper, an implementation model based on decision support systems will be developed. The output data from this model are the priority of Logistics 5.0 elements (from five groups—green warehousing, green transport, green packaging, infrastructure and organization, and human resources) for the optimal implementation, based on three goals (initial investment, return of investment time, implementation and exploitation complexity) that companies aim to achieve in the future. The model is based on the analytic hierarchy process, and data were collected from an expert group and analyzed with several statistical methods. The result is a model that provides an optimal strategy for the implementation of elements of Logistics 5.0. The implementation priority list of elements is very beneficial for the management of many companies from various types of industries.

The implementation of the Industry 4.0 concept enables the flexibility, modularity and self-optimization of the manufacturing process. Process planning, placed in the value chain between construction and physical manufacturing, therefore, also demands digital transformation, while management of the transformation towards the new digital framework represents one of the most demanding challenges. Continuing the research on its structure and role within the smart factory, the main motivation for this work was to recognize the potential of the digital transformation of process planning elements, and to define the key dimensions that are essential for the readiness factor calculation and later transformational strategy formation, but also to recognize the current level of awareness of the Industry 4.0 concept among the process planners, along with the current use of its elements and key priorities for the transformation. The research has therefore been conducted in 34 Croatian metal machining companies, within which the influence of company size, level of education and familiarity with Industry 4.0 on final results and the stage of development have been investigated. The results have shown that the company size has a significant influence on the development stage and the use of certain elements wherein small and medium enterprises (SMEs) have already implemented certain digital elements, while they also tend to have a better fundamental infrastructure when using complex process planning methods, unlike others, which are still highly traditional. Organization and human resources have been ranked with the highest priority for change, while target goals for hardware and software have been set, with the managerial challenges of transformation defined and discussed.

The digitization of the manufacturing industry, 10 years after the introduction of the Industry 4.0 concept, is still one of the most demanding tasks for the companies, especially for SMEs. As one of the biggest barriers in new business model implementation, the lack of strategy and workforce skills is frequently mentioned in the literature. The high level of investments it requires and the perception of high risks with unclear future benefits can be avoided with readiness factor calculation. This paper presents a novel model for readiness factor calculation, oriented to process planning and based on decision support systems. The model enables the definition of the optimal strategic plan for the digitization with the use of decision support systems (analytic hierarchy process) and through the use of statistical methods implemented within the model it minimizes the influence of human subjectivity and quantification of qualitative criteria. This innovative approach enables the understanding of the transition process to new technology-enabled business models, in this case oriented towards process planning. The useability and reliability of the model is proven in a case study of a metal machining company.