Influence of occupants’ behaviour on energy use in buildings. Field survey case study

In order to achieve the energy saving and reduction of CO2 emissions objectives set by EU policies, it is essential to decrease the amount of energy absorbed by buildings to ensure occupants’ thermal-hygrometric well-being. To this aim, the two most popular ways are the energy requalification of the existing built heritage and the search for the best performing building technological systems solutions. A further research line, which is becoming increasingly important, involves the modification of users’ behaviour as they become aware of the consequences of their energy choices. Detecting, analysing and understanding occupants’ behaviour is a key element in profiling users’ incorrect habits, evaluating the building energy performance and simulating and optimizing the building energy consumption during operation phas

Production Management Fundamentals for Additive Manufacturing

The additive manufacturing (AM) is a new way to produce parts, which in the last years had a significant application in the traditional production environment, since it demonstrated its capability to produce parts without particular defects and with good mechanical properties. During the last two decades the AM was firstly used to produce polymers’ products and after metals’ products; this evolution made possible the breakthrough in the traditional industrial sectors such as the aerospace, the mechanical, and other related sectors. Nevertheless, the introduction of this technology in this context put on the table of the researchers and practitioners some questions about the management of this technology in a more complex context, characterized by the integration with other machines. Aim of this chapter is to present a literature review of the principal facets of the AM related to the field of operations management and trying to define a model to account the costs of production and to schedule the machine activity

The impact of Additive Manufacturing on Supply Chain design: a simulation study

Additive Manufacturing is a production technology, which completely differs from the traditional subtractive approach. Because its different nature, its application could cause strong changes in supply chains and it could affect the relationship between the supply chain players. This paper proposes a quantitative evaluation of the Additive Manufacturing effects on the supply chain performance, considering different system configurations. A simulation model has been implemented in order to reproduce the behavior of the players and compare different scenarios. Both additive and traditional technologies have been modelled in order to compare their efficiency. Moreover, different supply chain configurations have been tested to assess the additive production feasibility combined with different supply chain structures. Results confirm that Additive Manufacturing provides good improvements in supply chain performances offering significant benefits in the decentralized solution

Economic and Environmental Sustainability for Aircrafts Service Life

Aircrafts are responsible for a significant environmental impact mainly due to the air pollution caused by their motors. The use of composite materials for their production is a way to significantly reduce the weight of the structures and to maximise the ratio between the payload weight and the gasoline consumption. Moreover, the design phase has to consider the cost of different operations performed during the aircraft service life. During the entire life cycle, one of the main costs is the maintenance one. In the current literature, there is a lack of knowledge of methods for maintenance cost estimation in the aircraft industry; moreover, very few environmental assessment methods have been developed. Thus, the aim of this paper is to define a new method to support the aircraft design process; both the environmental and the economic dimensions have been included with the purpose of assessing the aircraft sustainability during its service life. A green index has been identified mixing the maintenance cost and an environmental parameter with the aim of identifying the greenest solution. A final practical application shows the feasibility and the simple application of the proposed approach

A Cost Estimation Approach for Aircraft Design Enhancement

This paper presents a novel reliability-based parametric methodology for quantifying the reliability of cost estimates for new composite aircraft components. In recent years, the aircraft production sector has increased its attention on optimizing their composite manufacturing operations. It has become clear that a key factor in the success of these operations is the consideration that not only technical factors, but also economic ones as well are relevant. Composite manufacturing variability is greatly influenced by many of these factors, and since manufacturing with composites is significantly more difficult than with more traditional materials, there are many sources of uncertainty that could influence the reliability of manufacturing cost estimates for new composite aircraft components. Therefore, it is worth considering these sources of uncertainty during the cost estimation process and to quantify the reliability of the cost estimates. To demonstrate the proposed methodology, a numerical example featuring a real-life composite aircraft component from a Boeing 787, with real-life data, is presented. Results show that the proposed methodology can quantify the uncertainty associated with cost estimates for new composite aircraft components in an effective manner, thereby supporting engineers in optimising the cost of their designs, helping them avoid errors in budget definition, and enabling them to allocate resources more efficiently

Workers’ Aging Management—Human Fatigue at Work: An Experimental Offices Study

The aging issue in the work context is becoming a significant element of the future sustainability of service and industrial companies. It is well known that with increasing worker age the problem of maintaining the performance and the safety level when fatigue increases is a crucial point, and fatigue increases with the age. Due to social and political developments, especially in Western countries, the retirement age is increasing and companies operate with a higher workforce mean age. Therefore, the problem of recognizing and measuring fatigue has become a key aspect in the management of aging. Note that in the scientific engineering field, the problem of fatigue evaluation when a worker is performing his/her work activities is an important issue in the industrial and service world and especially in the context of the researchers that are investigating the human reliability assessment. As it is clear from the literature, the industrial operations management are suffering from some misleading concepts that only the medicine scientific context can clarify. Therefore, the aim of this paper is to define what are the open issues and the misleading concepts present in the classical fatigue evaluation methods, and second to define two experimental curves of fatigue that will help the decision makers to minimize the impact of fatigue on the workers, thus maximizing the sustainability of the working tasks assigned. This aim is achieved by examining the medical literature about the measurement of a particular kind of fatigue related to the circadian cycle, i.e., the cognitive one; after that, a survey about the possible technologies for measurements is performed. On the basis of technology selection, an experiment on real work activities is performed and some remarkable results about the fatigue in the workers observed and the technology use and its limitations are defined

Towards Digital Twin Implementation for Assessing Production Line Performance and Balancing

The optimization of production processes has always been one of the cornerstones for manufacturing companies, aimed to increase their productivity, minimizing the related costs. In the Industry 4.0 era, some innovative technologies, perceived as far away until a few years ago, have become reachable by everyone. The massive introduction of these technologies directly in the factories allows interconnecting the resources (machines and humans) and the entire production chain to be kept under control, thanks to the collection and the analyses of real production data, supporting the decision making process. This article aims to propose a methodological framework that, thanks to the use of Industrial Internet of Things—IoT devices, in particular the wearable sensors, and simulation tools, supports the analyses of production line performance parameters, by considering both experimental and numerical data, allowing a continuous monitoring of the line balancing and performance at varying of the production demand. A case study, regarding a manual task of a real manufacturing production line, is presented to demonstrate the applicability and the effectiveness of the proposed procedure

Assessing Risks Awareness in Operating Rooms among Post-Graduate Students: A Pilot Study

Background: In this study, we promote a global approach to occupational risk perception in order to improve occupational health and safety training programs. The study investigates the occupational risk perception of operating room healthcare workers using an Analytic Hierarchy Process approach. Methods: A pilot study was carried out through a cross-sectional survey in a university hospital in Southern Italy. An ad hoc questionnaire was administered to enrolled medical post-graduate students working in the operating room. Results: Fifty medical specialists from seven fields (anaesthetists, digestive system surgeons, general surgeons, maxillofacial surgeons, thoracic surgeons, urologists, and gynaecologists) were questioned about perceived occupational risk by themselves. Biological, ionizing radiation, and chemical risks were the most commonly perceived in order of priority (w = 0.300, 0.219, 0.210). Concerning the biological risk, gynaecologists unexpected perceived this risk as less critical (w = 0.2820) than anaesthesiologists (w = 0.3354), which have the lowest perception of the risk of ionizing radiation (w = 0.1657). Conclusions: Prioritization methods could improve risk perception in healthcare settings and help detect training needs and perform sustainable training programs