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Buildings are one of the largest contributors to negative environmental impacts because of the high consumption of energy and materials during their life cycle. The present work proposes a framework, able to make available information, both of general materials and specific commercial solutions; moreover, it overcomes the current state of the art, since, although focused on environmental sustainability, provides the opportunity to compare simultaneously several choices, also considering their properties and characteristics. Based on the proposed methodology, a tool structure and workflow are presented. The main potentiality is represented by the possibility of executing sustainability assessment already in the early stages of building design using the proposed tool when design choices significantly contribute to the global environmental impact of solutions. A validation procedure to quantitatively evaluate the main tool's limits and potentialities is proposed.

In the era of the fourth industrial revolution, human has still a central role. Manufacturing industries have to deal with human sustainability in order to guarantee workers’ health and well-being. Several studies have proved the importance of ergonomics in workplace design and the benefits related to the adoption of the human-centered approach. The enabling technologies of Industry 4.0 are changing the role of the operator and can support him from a physical and cognitive point of view. On the other hand, companies are increasingly implementing lean philosophies, such as World Class Manufacturing, to maintain their competitiveness by reducing wastes and costs. However, the need arises for a comprehensive methodology to support the design of manufacturing equipment considering human factors by integrating Industry 4.0 technologies and World Class Manufacturing elements. It aims at improving both ergonomic and efficiency aspects of the workstation. The proposed methodology allows identifying and in-depth analyzing the problem, thus finding and implementing a solution that complies with all the requirements and constraints defined. Each step of the methodology can be strengthened by Industry 4.0 technologies. The methodology has been experimented in a real case study with a global company of agriculture and industrial vehicles, leading to the design and implementation of a new equipment. Relevant benefits in terms of ergonomics, efficiency, and process standardization have been achieved.

The work environment influences workers’ well-being and contributes to the growth of personal experiences. In fact, working in an unhealthy workplace can cause stress, frustration, and anxiety. Therefore, companies have to deal with the workers’ well-being in the work environment, making the management of human factors a crucial aspect. In this context, the introduction of Industry 4.0 technologies can support workplace monitoring and improvement. Some researchers propose structured methods that consider several ergonomic domains together; however, it is necessary to create platforms that support data collection, elaboration, and correlation in an integrated way. Accordingly, this paper presents a tool that supports the monitoring of operators’ activities, the data analysis, and the implementation of corrective actions to make the workplace socially sustainable. Preliminary tests were conducted to assess the functionality of the tool architecture and two use cases are presented. They focus on posture analysis and stress detection by inertial sensors and unsupervised machine learning algorithms, respectively.

Investment casting (IC) is a manufacturing process for making components giving an excellent surface finish, dimensional accuracy, and complex shapes. Despite these benefits, IC requires high cost and lead time for realizing the metallic mold for pattern manufacturing. To avoid the shortcoming of casting processes, Additive Manufacturing (AM) is widely used for fabricating patterns, cores, and molds (Rapid Casting - RC). Several applications concerning rapid investment casting (RIC) through Fused Filament Fabrication (FFF) and Stereolithography (SLA) were developed. However, a techno-economic analysis based on SLA application for RIC is missing. This paper presents a techno-economic analysis regarding SLA adoption for RIC. SLA is compared with wax injection, the traditional approach for realizing wax patterns. The article provides a decision-making tool that supports stakeholders in evaluating when AM is convenient (cost and lead time) for creating wax patterns, considering different production scenarios. For the compared technologies, the authors developed analytical cost models capable of assessing the cost of the entire production process and evaluating the postprocessing phases. The following characteristics were considered: (i) different production volume, (ii) machine load factor, and (iii) parts features (i.e., dimensions and shape). The results show that SLA, for small parts, is more convenient than wax injection when the production volume is higher than 1E+03.

Collaborative robotics is a key pillar of the smart factory of the future making production systems more flexible and responsive. To this aim, the research communities have made considerable efforts to enable direct interaction between humans and robots in a safe and integrated shared workspace. However, the industrial sector still shows a mismatch between the HRC potentialities and the HRC existing applications. The design is often technology-driven, and coexistence prevails on cooperation or collaboration. Through the case study, this article describes the human-driven design approach that a company should follow to define and evaluate different scenarios and choose the one that best suits its context and workforce. It considers safety, ergonomic, technical, spatial, and equipment issues. It presents an application common to all sectors, the packaging, addressing the complexities of the new production paradigm of mass customization. The design approach has been tested by the major Italian kitchen manufacturer and the resulting collaborative workstation has been simulated by using the software Tecnomatix Process Simulate. The simulation allowed the analysis and evaluation of risks, layout, and performance. The simulation results showed significant benefits in terms of efficiency ensuring a safe collaboration.

Background Simulation has been recognized as a shift in health care education that can improve skills and patient safety and outcomes. High-fidelity simulation of critical medical situations can be a source of stress among participants that can interferes with students' abilities leading to unexpected emotional response. In the current study, we sought to evaluate stress responses during a session including a high-fidelity simulation dedicated to the management of an emergency and one performing a complex technique such as spinal tap, in a population of medical students during a session including high-fidelity simulation (HF) dedicated to the management of an emergency and one performing a complex technique such as spinal tap (ST). Methods A quasi-experimental before-after study was used including the administration of questionnaires before and after simulation, and biomarkers evaluation by salivary cortisol samples. A total of 148 students 148 were eligible and agreed to participate in the study. We used paired T-test for mean comparison regarding State-trait anxiety for both HF and ST simulations. For NASA-TLX we performed a T-test mean comparison between groups. We used paired T-test mean comparison for cortisol analysis in the HF simulation. Multivariable linear regression has been used to assess variables associated with AUCg Results values of State-Trait Anxiety Inventory scores were relatively higher at the end of the HF and ST simulation sessions. NASA task load index (NASA-TLX) was significantly higher at baseline for the high fidelity simulations, with respect to the ST simulation. Regarding HF simulation, a T-test for paired samples showed a statically significant difference between cortisol levels at 10 minutes after the start of the training and after 30 minutes from the simulation in both groups. Fold increase was similar in the two groups. Linear regression showed that cortisol AUCg was related to the STAI-Y score in both groups. Conclusions This work highlights how our students developed a stress response, testified by psychological and biological outputs more related to their personal attitude rather than complexity of simulated scenario. More studies are needed to confirm this trend and to clarify the role of simulated stress response in a long-term learning scenario.

As life expectancy increases, the likelihood of more falls and fall-related hospitalizations increases with a significant impact on the health system. Given the high incidence of falls in healthy elderly people, in order to prevent them, it is necessary to identify predisposing risk factors, analyze the specific needs of the subjects and use a targeted preventive strategy. This paper investigates the influence of multidimensional health parameters on the fall risk of community-dwelling older people, living in inner areas of Marche Region (Italy). Multidimensional data on the global health of each individual has been collected among several health domains (i.e., mobility, psychological, nutritional, cardiological, social). Statistical analysis has been applied for the assessment of the relationship among the defined health variables and the influence on the fall risk. The binary logistical regression analysis has produced a statistical model with good characteristics of fit and good predictability. The following features have been proven to be strong predictors of fall: female (OR for Gender, 5.526; 95% CI, 1.49–20.53), limited range of movement (OR 3.278; 95% CI, 1.01-10.68), diabetes (OR 4.487; 95% CI, 1.02-19.80), previous syncope (OR 7.686; 95% CI, 1.01-58.55), and body mass index (OR 1.176; 95% CI, 1.03-1.35). Future work will allow the development of a fall prediction index to have a framework of the elder’s global health status and to define a personalized intervention strategy for any adverse event prevention.

The numerousness of over-65 people in the EU-27 population will significantly increase by about 43% by 2050. The main issue is to help aging people stay healthy, active, and integrated into society. In this context, this work aims to develop a novel assistance model, for the elderly’ social and health care, based on a patient-oriented approach. The assistance model is provided through a software platform that integrates three different modules: i) frailty diagnosis and user-product/service matching, ii) users’ monitoring, data acquisition, and telemedicine, iii) organization and management of logistics. This paper focuses on the first module, showing the variables, the logics, and the necessary rules to realise the personalised product-service assignment, within the user-centred method.