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One of the key sectors for the green transition of European countries is construction, that is more and more asked to evolve towards innovative ecological binders and green cost-effective processes. The construction sector is highly energy intensive, and the cement production is one of the main sources of environmental pollution in the world. In this regard, GeoPolymers (GP) seem to be promising for a sustainable replacement of cementitious materials. Therefore, the Life Cycle Assessment (LCA) of the industrial production of different formulations of Geopolymer Concrete (GC) was performed in this study after scaling up the Life Cycle Inventory (LCI) from a laboratory scale to an industrial one. Based on LCA results, the Global Warming Potential (GWP) indicator demonstrated a lower greenhouse gas emission of the proposed GC production in respect to the CC manufacturing process, while no significant difference was observed in the GWP scores of the considered GC formulations when referring to the functional unit. Nevertheless, the usage of the innovative GC formulations, on an industrial scale, would avoid a significant reduction of sand and kaolin extracted, with a consequent decrease on the environmental impact. Finally, the economic assessment showed that the combined production of thermal and electrical energy by a cogeneration system could provide a significant cost reduction when the percentage of electricity fed into the public network is higher than 39%.

Performance Shaping Factors (PSFs) are contextual, individual, and cognitive factors used in Human Reliability Analysis (HRA) to quantify the worker contribution to errors when performing a generic task. Although the empirical evidence demonstrates the existence of PSF interrelationships, the majority of HRA methods assume their independence. As a consequence, the resulting Human Error Probability (HEP) might be over- or underestimated. To deal with this issue, only a few qualitative guidelines or statistical-based approaches have been proposed so far. While the former are not well structured, the latter require a high computational effort and a proper number of input data. Therefore, the present paper provides an alternative approach to deal with the PSFs interaction issue to facilitate the identification of the most influential human factors on which to take corrective actions. To this purpose, Multi Criteria Decision Making (MCDM) methods may represent a structured, effortless, and easily replicable framework. Owing to their ability to deal with the interdependence of decision factors, DEMATEL and ANP are hence considered and afterwards compared, highlighting their strengths and weaknesses. Both methods are implemented in an agri-food company which produces pistachios in Southern Italy. [ABSTRACT FROM AUTHOR]

In 2019, Europe adopted the New Green Deal as a strategic plan to become a competitive, resource-efficient, and driven economy by reducing its gas emissions and carbon footprint. Due the COVID-19 pandemic, this strategic plan was recently updated to expedite the green transition of European industries. Therefore, the present paper deals with the problem of deciding an appropriate size for a biomass plant that directly produces electric energy by means of two different conversion processes: combustion and gasification. After an initial estimation of the energy potential in western Sicily, GIS data of biomass growth were used to identify the appropriate size for the power plants under investigation. The economic feasibility of biomass utilization was evaluated over a capacity range of 10 to 30 MW, considering total capital investments, revenues from energy sales, and total operating costs. Moreover, the effect of variations on incentive prices was analyzed by means of a sensitivity analysis. Comparing the different plant solutions considered, the environmental sustainability was also analyzed using the life cycle assessment (LCA) approach. The results showed that the combustion solution had a higher profitability and a lower environmental impact for each plant size. The obtained results also demonstrated that providing power from residual biomass in small agricultural communities would significantly reduce their environmental impacts while improving the economic feasibility of their waste management practices. [ABSTRACT FROM AUTHOR]

The marble processing cycle involves the production of large quantities of wastes whose disposal represents an economic and environmental concern for marble companies due to the difficulty of identifying suitable landfills and the high transfer costs. In this context, the design of a sustainable industrial plant that allows the reuse of the calcium carbonate (CaCO3) contained in the marble waste is extremely challenging. With this recognition, the main industrial applications of CaCO3 are firstly analyzed in the present work to identify the physical–chemical properties required to CaCO3 in these contexts. Later, different plant solutions are suggested to recover CaCO3 from marble sludge in order to allow its use in industrial applications. The designed industrial plant includes an energy efficient drying phase, which exploits the thermal waste of the exhaust gases produced in a cogeneration section, and a subsequent milling phase. Since marble wastes currently constitute an economic burden for companies and an environmental emergency for the Public Administration, the performed technical–economic analysis shows that its recovery may represent an opportunity of sustainable development for the marble sector. [ABSTRACT FROM AUTHOR]

Project Managers (PMs) working in competitive markets are finding Project Management Information Systems (PMISs) useful for planning, organizing and controlling projects of varying complexity. A wide variety of PMIS software is available, suitable for projects differing in scope and user needs. This paper identifies the most useful features found in PMISs. An extensive literature review and analysis of commercial software is made to identify the main features of PMISs. Afterwards, the list is reduced by a panel of project management experts, and a statistical analysis is performed on data acquired by means of two different surveys. The relative importance of listed features is properly computed, and the interactions between the respondent's profiles and PMIS features are also investigated by cluster and respondents' analyses. The paper provides information for researchers and practitioners interested in PMISs packages and their applications. Furthermore, the analyses may help practitioners when choosing a PMIS, and also for developers of PMISs software in understanding user needs. [ABSTRACT FROM AUTHOR]

In recent years, the partnerships between private companies and public organizations are becoming key elements for improving local development, territorial competitiveness, and delivering innovation. These collaborations are widely promoted by the European Framework Programme for Research and Innovation thanks to the provision of several instruments, such as Horizon 2020. In this context, competitiveness's improvement of the territory employing research and innovation actions is supported by the technological districts. In Sicily, the AgroBioPesca district has attempted a strategic action named "Call for ideas" in order to design its own roadmap for research and innovation in the agri-food sector. For this purpose, many proponents of public and/or private sectors presented several innovative project ideas referred to specific Technological Trajectories. This paper aims at providing an instrument able to select the most suitable project ideas in order to constitute the AgroBioPesca projects portfolio. To such an aim, the authors propose the application of the multiple criteria sorting method ELECTRE TRI considering criteria deduced by the Horizon 2020 guidelines and documents. The application of this methodology allows subdividing the project ideas received into project ideas to be rejected, reviewable, and eligible for funding. Moreover, to consider the uncertainty of the decision-makers' judgment, the authors propose a new version of the method in which the crisp judgment is converted into an interval. A sensitivity analysis has lastly been conducted to study the weaknesses of non-financiable projects. [ABSTRACT FROM AUTHOR]

In the last decade, the nutritional and health benefits of Opuntia (Opuntia ficus-indica (L.) Mill.) were discussed by academic scientists and private companies. In particular, the introduction of this substance in frequently consumed foods, like, for example, pasta and bakery products, could have a wide diffusion due to its rich composition in polyphenols, vitamins, polyunsaturated fatty acids, and amino acids. The identified natural cactus compounds are responsible for biologically relevant activities including anti-inflammatory, antioxidant, hypoglycemic, antimicrobial, and neuro-protective properties. The aim of this paper is the evaluation of the best combination of Opuntia quantity and process parameters (recipe) for the production of sustainable functional pasta. The results obtained show that the new functional pasta guarantees the presence of the Opuntia quantity necessary to be considered a healthy food without altering the organoleptic and physical properties of the final product. An important indicator of a sustainable food product is its capacity to contribute to public health while maintaining a high quality of the final product. The selection of the optimal recipe was carried out by means of a multi-criteria decision-making procedure, ELECTRE III. Finally, a sensitivity analysis was conducted to assess the stability of the obtained solutions varying the ELECTRE III thresholds, showing that the results obtained are stable under uncertain conditions. Food productions are often affected by qualitative judgments in terms of physical and organoleptic properties of the final product, making the ELECTRE III particularly suitable in an industrial application in which different points of view are involved. [ABSTRACT FROM AUTHOR]

The aim of this paper was the development of a Smart Logistic Unit (SLU) based on RF technology to support the management of the food supply chain, in order to guarantee the shelf life of products in agreement with logistic efficiency and system sustainability. For this purpose, the main parameters that influence the quality of perishable products were determined and a shelf life equation based on Volatile Organic Compounds (VOCs) was modelled. The levels of VOCs were gathered by the sensors allocated inside the SLU, which configures as the remote element of a system for identification and data transmission. The proposed model was then validated through an experimental test, simulating the real life transport conditions. [ABSTRACT FROM AUTHOR]

Perishable goods are a fundamental source of revenue for the retail sector; their management, however, constitutes a severe challenge for retailers and supply chain partners. A significant cost in particular is the fraction of products perished through the supply chain, which also constitutes an ethical and environmental concern. Supply chain organisation and operative characteristics have a significant influence on this matter, as in fact ensuring suitable temperature conditions for the stock-keeping units throughout the supply chain is mandatory for perishable products. Recent developments in sensing and communication technologies allow detailed monitoring and control of cold chain; however, depending on the characteristics of the supply chain, an inherent risk of perished products is often inevitable, even in the hypothesis of perfect control. This article proposes a methodology to evaluate the performance of a cold chain in terms of expected product quality at the retail store, and to estimate the expected fraction of perished products, according to the supply chain configuration. The approach is based on Monte Carlo simulation, and implements referenced shelf-life models. A real application is also presented, involving a preliminary analysis and mapping of the supply chain activities based on time–temperature data, in order to demonstrate the practicability of the approach proposed. [ABSTRACT FROM AUTHOR]

Localization systems are becoming an important feature for many RFID-based inventory and warehouse management support tools, due to the ever increasing diffusion of Radio Frequency IDentification (RFID) in logistic processes. RFID-based Location system will allow offering value-added services to logistics operators, where RFID tags can be used for more than just labeling items. This paper proposes a Received Signal Strength (RSS) based positioning system for perishable products equipped with active UHF RFID tags, inside a refrigerated warehouse (4C°). A fundamental problem in the design of RFID based localization system is the evaluation and mapping of the signal attenuation, which depends upon several parameters (fading from obstacles in the transmission path, reflections off surfaces and relative antenna orientation). Such information should be considered in the design phase, where instead simplified theoretical approaches are frequently employed. Theoretical path loss models are however inadequate for a reliable prediction of the signal strength, which significantly affects the accuracy of distance measurement and ultimately the precision of localization. An accurate prediction of the coverage level is hence required for obtaining a reliable design. In this paper, a case study on the design of an RFID localization system is presented, comparing a realistic signal distribution, obtained considering the influence of reflections and refractions, and the theoretical approach based on simple path loss models. Realistic coverage maps are obtained by means of a simulation tool based on 2D ray tracing algorithm. [ABSTRACT FROM AUTHOR]

In the industrial warehouse design domain, today’s computerized information systems have gained a relevant interest due to the issues related to asset tracking and traceability. In such context, the employment of new information technologies on warehouse management systems has opened new business opportunities due to the sensible price reduction in the last years. This paper focuses on the technical issues related to the realization of wireless localization systems for warehouses, which are necessary for the implementation of random allocation policies, and in particular investigates the opportunities offered by RFID technology in such context. The enforcement of random allocation policies allows to increase the utilization coefficient of warehouses which is a critical issue, for example in refrigerated warehouses for perishable products. In particular, the development of localization systems based on trilateration is here considered, and an experimental model which links the received signal strength to the reading distance has been determined in order to take into account the specific features of the technology employed. A~methodology is hence proposed to overcome the simplifying assumptions theoretical attenuation models rely on, by fitting a mathematical model on experimental observations. The problem of the accuracy level required to locate Stock Keeping Units (SKUs) of fixed dimensions is also considered, resulting in the evaluation of the maximum allowed reading distance. On the basis of the obtained results, the optimal configuration of the fixed infrastructure in terms of the number of antennas and their position is finally defined. [ABSTRACT FROM AUTHOR]

Construction is recognized as one of the most polluting and energy consuming industries worldwide, especially in developing countries. Therefore, Research and Development (R&D) of novel manufacturing technologies and green construction materials is becoming extremely compelling. This study aims at evaluating the reuse of various wastes, originated in the Kraft pulp-paper industry, as raw materials in the manufacture of novel geopolymeric (GP) mortars whose properties fundamentally depend on the target application (e.g., insulating panel, partition wall, structural element, furnishing, etc.). Five different wastes were reused as filler: Two typologies of Biomass Fly Ash, calcareous sludge, grits, and dregs. The produced samples were characterized and a multi criteria analysis, able to take into account not only the engineering properties, but also the environmental and economic aspects, has been implemented. The criteria weights were evaluated using the Delphi methodology. The fuzzy Topsis approach has been used to consider the intrinsic uncertainty related to unconventional materials, as the produced GP-mortars. The computational analysis showed that adding the considered industrial wastes as filler is strongly recommended to improve the performance of materials intended for structural applications in construction. The results revealed that the formulations containing 5 wt.% of calcareous sludge, grits, and dregs and the one containing 7.5 wt.% of calcareous sludge, grits, dregs, and Biomass Fly Ash-1 have emerged as the best alternatives. Furthermore, it resulted that the Biomass Fly Ash-2 negatively influences the structural performance and relative rank of the material. Finally, this case study clearly shows that the fuzzy Topsis multi-criteria analysis represents a valuable and easy tool to investigate construction materials (either traditional and unconventional) when an intrinsic uncertainty is related to the measurement of the quantitative and qualitative characteristics. [ABSTRACT FROM AUTHOR]