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The use of light but strong materials is largely studied in various area of the shipbuilding, this because the need of reducing the weight, and especially the weight of all the structures above the main deck assume primary importance for the stability. Traditionally in fast boats like fast ferries, hydrofoils, patrol boats, the typical materials are Aluminum alloy or composites, both those materials have advantages and disadvantages, but the new development of technologies made possible to combine them, in order to have a new material, combining the advantages of both, in terms of fatigue resistance, firefighting characteristics. In this paper, predominant mode II fatigue delamination tests of fiber metal laminates made of alternating layers of 2024-T3 aluminum alloy sheets and unidirectional E-Glass/epoxy laminates are presented. Several experimental tests are carried out employing the End Notched Flexure fixture and a progressive damage model is used to simulate the damage accumulation in the aluminum-composite interface, in the localized area in front of the crack tip, where micro-cracking or void formation reduce the delamination strength during fatigue tests. In particular, the numerical model is based on the cohesive zone approach and on the analytical definition of a damage parameter, directly related to the fatigue crack growth rate da/dN. The numerical model, implemented in ANSYS environment, uses a fracture mechanics-based criterion in order to determine the damage propagation. In particular, the study has allowed to determine the damage model constants that are used for numerical verification of the experimental results.

The problem of the active stabilization of ship motions is particularly important in the case of pleasure boats or in any case of passenger ships, since the commercial value of the ship is directly related to the comfort of the load transported in this case “people”, considered as stresses induced on them by the vessel movements, with particular attention to roll, given the ship geometric characteristics. Naval architects developed trough the years different solutions to reduce the roll of the ship, and consequentially to increase the passengers comfort, and the development of this solutions followed the progress of technology. Active fins have been the most used, but now the gyroscope solution is coming out with interesting solutions also for large yacht with displacement over 1000 t. The paper aimed at making a interactive comparison between the two systems: active fins and gyroscopes, trough the case study of a yacht of 77.77 m, in order to evaluate if, assuming the same capability to reduce the roll for each one of the two systems, there are other advantages or disadvantages from the point of view of the naval architecture, in particular the resistance of the hull. In fact the importance of the resistance on high Froude number hulls, like planning hulls it is well known, but the paper aimed at giving result useful for naval architects also on traditional displacement hulls, like the one considered here, in order to give also a contribution for preliminary design. The interactivity of the process has been realized using not a theoretical estimation of the gain resistance of the ship according to equations etc. but real tank tests on the hull, according to International Towing Tank Conference methodology, with and without appendages.

Purpose The purpose of this paper is to propose a methodology to support the Hoshin Kanri (HK) process taking into account the variance of senior managers’ perspective regarding the relationships among objectives, key performance indicators and continuous improvement (CI) projects. Design/methodology/approach A four-step methodology incorporates the A3 report into the HK, whose deployment was weighted by the variability among managers’ perception about the importance of each decision. This methodology was applied in a market-leader Mexican auto parts manufacturing company that is undergoing a Lean Manufacturing (LM) implementation. Findings The results indicate that the proposed methodology provides an easier approach to consolidate different perspectives and weight the importance of CI projects. Moreover, it minimizes the possibility of managerial conflicts or the influence of a determined senior manager on others’ opinions during the deployment and prioritization. Practical implications This work may be of great interest to managers, consultants and professionals who deal with the implementation of LM and wish to prioritize the importance of CI projects within the perspective of HK. Originality/value HK provides a systematic approach to integrate strategic management with daily routine management through an adequate deployment of organizational policies to all levels. However, companies usually struggle with several issues such as the style of senior managers and consensus establishment among different opinions, which emphasizes the relevance of the proposed methodology in this study.

In today’s competitive global market it is mandatory to improve warehousing operations integrating economic, environmental and social aspects. The recent advancement in monitoring technologies can greatly improve the performance of the food supply chain reducing product loss. In particular, in the perishable food supply chain, initially inventory operations are critical because they manage the material flows in very variable conditions. The deterioration level of the products as well as the market demand are the main factors that can influence warehouse strategy. This research aims to consider the application of sustainability principles in the context of warehouse storage, evaluating the combined decision of implementing shelf life based picking policy and pricing strategy. In particular, the proposed approach is based on a referenced shelf life model and on the Monte Carlo simulation. Three different pricing scenarios in a case study for the management of the warehouse were defined and their Economic Traceability Lot was determined on the basis of an economic feasibility analysis. Finally, the carbon footprint for each scenario was determined in terms of emissions produced by temperature-controlled transportations and for the landfilling of product wasted.

While digitalisation is at the heart of the strong research stream on Factory of the Future and Industry 4.0, the convergence between digitalization and business innovations through servitization leads to a new and already very active area of research on Digital Servitization. Part of this transition are Product-Service-Systems (PSS), which have generated a large amount of research work over the past decade and which have recently evolved towards the ‘smart PSS’ concept, by integrating artificial intelligence and digital supports. These new generation Product-Service-Systems are not only smart in terms of functionalities for the final users, but also smarter and smarter along most of the phases of their proper life cycle, thus providing added-value to most of the actors of the ecosystem in addition to the final user: smart at design time, smart for installation and delivery phase, smart for usage and maintenance, smart for end-of life. Digital Servitization opens opportunities for multi-dimensional and multi-actor value exchanges, increasing its strategical innovative impact for industrial companies.

In this work, composite coatings of chitosan and silver nanoparticles were presented as an antibacterial coating for orthopedic implants. Coatings were deposited on AISI 304L using the galvanic deposition method. In galvanic deposition, the difference of the electrochemical redox potential between two metals (the substrate and a sacrificial anode) has the pivotal role in the process. In the coupling of these two metals a spontaneous redox reaction occurs and thus no external power supply is necessary. Using this process, a uniform deposition on the exposed area and a good adherence of the composite coating on the metallic substrate were achieved. Physical-chemical characterizations were carried out to evaluate morphology, chemical composition, and the presence of silver nanoparticles. These characterizations have shown the deposition of coatings with homogenous and porous surface structures with silver nanoparticles incorporated and distributed into the polymeric matrix. Corrosion tests were also carried out in a simulated body fluid at 37 °C in order to simulate the same physiological conditions. Corrosion potential and corrosion current density were obtained from the polarization curves by Tafel extrapolation. The results show an improvement in protection against corrosion phenomena compared to bare AISI 304L. Furthermore, the ability of the coating to release the Ag+ was evaluated in the simulated body fluid at 37 °C and it was found that the release mechanism switches from anomalous to diffusion controlled after 3 h.

Nowadays, we are assisting in the exceptional growth in research relating to the development of wearable devices for sweat analysis. Sweat is a biofluid that contains useful health information and allows a non-invasive, continuous and comfortable collection. For this reason, it is an excellent biofluid for the detection of different analytes. In this work, electrochemical sensors based on polyaniline thin films deposited on the flexible substrate polyethylene terephthalate coated with indium tin oxide were studied. Polyaniline thin films were abstained by the potentiostatic deposition technique, applying a potential of +2 V vs. SCE for 90 s. To improve the sensor performance, the electronic substrate was modified with reduced graphene oxide, obtained at a constant potential of −0.8 V vs. SCE for 200 s, and then polyaniline thin films were electrodeposited on top of the as-deposited substrate. All samples were characterized by XRD, SEM, EDS, static contact angle and FT-IR/ATR analysis to correlate the physical-chemical features with the performance of the sensors. The obtained electrodes were tested as pH sensors in the range from 2 to 8, showing good behavior, with a sensitivity of 62.3 mV/pH, very close to a Nernstian response, and a reproducibility of 3.8%. Interference tests, in the presence of competing ions, aimed to verify the selectivity, were also performed. Finally, a real sweat sample was collected, and the sweat pH was quantified with both the proposed sensor and a commercial pH meter, showing an excellent concordance.

Lead-acid batteries are now widely used for energy storage, as result of an established and reliable technology. In the last decade, several studies have been carried out to improve the performance of this type of batteries, with the main objective to replace the conventional plates with innovative electrodes with improved stability, increased capacity and a larger active surface. Such studies ultimately aim to improve the kinetics of electrochemical conversion reactions at the electrode-solution interface and to guarantee a good electrical continuity during the repeated charge/discharge cycles. To achieve these objectives, our contribution focuses on the employment of nanostructured electrodes. In particular, we have obtained nanostructured electrodes in Pb and PbO2 through electrosynthesis in a template consisting of a nanoporous polycarbonate membrane. These electrodes are characterized by a wider active surface area, which allows for a better use of the active material, and for a consequent increased specific energy compared to traditional batteries. In this research, the performance of lead-acid batteries with nanostructured electrodes was studied at 10 C at temperatures of 25, −20 and 40 °C in order to evaluate the efficiency and the effect of temperature on electrode morphology. The batteries were assembled using both nanostructured electrodes and an AGM-type separator used in commercial batteries.

Dopamine is an important neurotransmitter involved in many human biological processes as well as in different neurodegenerative diseases. Monitoring the concentration of dopamine in biological fluids, i.e., blood and urine is an effective way of accelerating the early diagnosis of these types of diseases. Electrochemical sensors are an ideal choice for real-time screening of dopamine as they can achieve fast, portable inexpensive and accurate measurements. In this work, we present electrochemical dopamine sensors based on reduced graphene oxide coupled with Au or Pt nanoparticles. Sensors were developed by co-electrodeposition onto a flexible substrate, and a systematic investigation concerning the electrodeposition parameters (concentration of precursors, deposition time and potential) was carried out to maximize the sensitivity of the dopamine detection. Square wave voltammetry was used as an electrochemical technique that ensured a high sensitive detection in the nM range. The sensors were challenged against synthetic urine in order to simulate a real sample detection scenario where dopamine concentrations are usually lower than 600 nM. Our sensors show a negligible interference from uric and ascorbic acids which did not affect sensor performance. A wide linear range (0.1–20 μm for gold nanoparticles, 0.1–10 μm for platinum nanoparticles) with high sensitivity (6.02 and 7.19 μA μM-1 cm-2 for gold and platinum, respectively) and a low limit of detection (75 and 62 nM for Au and Pt, respectively) were achieved. Real urine samples were also assayed, where the concentrations of dopamine detected aligned very closely to measurements undertaken using conventional laboratory techniques. Sensor fabrication employed a cost-effective production process with the possibility of also being integrated into flexible substrates, thus allowing for the possible development of wearable sensing devices.

La presente invenzione riguarda un dispositivo che ha lo scopo di sottoporre a prova rotismi meccanici per la trasmissione di elevata potenza. L’impiego di tale dispositivo sostituisce, quindi, l’uso di freni di prova il cui impiego per elevate potenze risulta costoso e i cui ingombri sono rilevanti.

Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 agenda and includes smart manufacturing, energy efficient buildings and low-impact industrialization. Industry 4.0 technologies help to achieve sustainability in business practices. However, very limited studies reported about the extensive reviews on these two research areas. This study uses a systematic literature review approach to find out the current research progress and future research potential of Industry 4.0 technologies to achieve manufacturing sustainability. The role and impact of different Industry 4.0 technologies for manufacturing sustainability is discussed in detail. The findings of this study provide new research scopes and future research directions in different research areas of Industry 4.0 which will be valuable for industry and academia in order to achieve manufacturing sustainability with Industry 4.0 technologies.

Deep water activities are essential for many industrial fields, for instance in repairing and installation of underwater cables, pipes and constructions, marine salvage and rescue opera- tions. In some cases, these activities must be performed in deep water and hence require special equipment and prepared and experienced personnel. In some critical situations, re- motely controlled vehicles (ROVs) can't be used and a human diver intervention is required. In the last case, divers are required to perform work at high depths, which could be as low as 300m below the water surface. Usually, this is the limit depth for commercial diving and when operations must be carried out even deeper, ROVs remain only possibility to perform them. In the past, the safety regulations were less strict and numerous operations on depth of 300-350 meters of seawater were conducted. However, in the beginning of the 90s gov- ernments and companies started to impose limits on depths of operation; for instance, in Norway maximum operational depth for saturation divers is limited to 180 meters of sea- water (Imbert et al., 2019). Obviously, harsh environmental conditions impose various limitations on performed activi- ties; indeed, low temperature, poor visibility and high pressure make it difficult not only to operate at depth, but even to achieve the point of intervention. One of the main problems is related to elevated pressure, which rises for about 1 bar for each 10 meters of water depth and could achieve up to 20-25 bars at required depth, while pressure inside divers? atmospheric diving suites must be nearly the same. Considering this, there are several evident limitations. First is related to the fact that at high atmospheric pressure oxy- gen becomes poisonous for human body and special breath gas mixtures are required to avoid health issues. The second one is maximum pressure variation rate which would not cause damage for the human body; indeed, fast compression or decompression could easily cause severe damages and even death of divers. Furthermore, surveys found that circa 1/3 of divers experience headache during decompression which usually last for at least several hours and up to several days (Imbert et al., 2019). The same study indicates that majority of the divers experience fatigue after saturation and it lasts on average more than 4 days before return to normal. Obviously, risk of accidents increases with high number of compression- decompression cycles. To address these issues, in commercial deep water diving the common practice is to perform pressurization only one time before the start of the work activity which typically lasts 20-30 days and consequent depressurization after its end. Hence, divers are living for several weeks in isolated pressurized environments, typically placed on board of a Dive Support Vessel (DSV), usually barge or a ship, and go up and down to the workplace using submersible decompression chamber also known as the bell. While long-term work shifts provide numerous advantages, there is still necessity to perform life support supervision of the plant, the bell and the diving suits, which require presence of well qualified personnel. Currently, most of training activities are performed on empty plant during idle time, but obviously this approach is low efficient and costly, as well as accom- panied by the risk to broke equipment. To address such issues, this research project proposes utilization of simulator of plant and its life support system, devoted to train future Life-Support Supervisors (LSS), taking into account gas dynamics, human behaviour and physiology as well as various aspect of opera- tion of saturation diving plants.

The paper reports some preliminary results concerning the manufacturing process of CuZnSnSe (CZTSe) and CuInGaSe (CIGS) nanowire arrays obtained by one-step electrodeposition for p-n junction fabrication. CZTSe nanowires were obtained through electrodeposition in a polycarbonate membrane by applying a rectangular pulsed current, while their morphology was optimized by appropriately setting the potential and the electrolyte composition. The electrochemical parameters, including pH and composition of the solution, were optimized to obtain a mechanically stable array of nanowires. The samples were characterized by scanning electron microscopy, Raman spectroscopy, and energy-dispersion spectroscopy. The nanostructures obtained showed a cylindrical shape with an average diameter of about 230 nm and a length of about 3 µm, and were interconnected due to the morphology of the polycarbonate membrane. To create the p-n junctions, first a thin film of CZTSe was electrodeposited to avoid direct contact between the ZnS and Mo. Subsequently, an annealing process was carried out at 500 °C in a S atmosphere for 40 min. The ZnS was obtained by chemical bath deposition at 95 °C for 90 min. Finally, to complete the cell, ZnO and ZnO:Al layers were deposited by magnetron-sputtering.

Negli ultimi decenni, le aziende manifatturiere hanno assistito al diffondersi di due trasformazioni, una orientata all?introduzione di nuovi modelli di business, e un'altra orientata al miglioramento dei processi di produzione e di servizio. La prima, relativa al modello di business, � consistita nello sviluppo di nuove offerte basate sulla vendita congiunta di prodotti e servizi (ad esempio un macchinario ed il servizio di manutenzione), volte a creare relazioni stabili e durature con i clienti. La seconda, invece, ha riguardato l'introduzione di nuove tecnologie che hanno spinto le aziende verso la digitalizzazione dei processi di lavoro e che dovrebbero consentire di migliorare il monitoraggio degli stessi garantendo, al contempo, un incremento della competitivit�. La tesi, collocata in questi due filoni di ricerca, si concentra sul tema dell'erogazione della manutenzione e propone un framework che, sfruttando i dati provenienti dal campo, permette di migliorare il processo decisionale a livello operativo e la gestione del flusso di informazioni interno all?azienda. Il framework, sfruttando dati storici e real-time relativi all'asset ed ai servizi, permette di prendere decisioni relative all'erogazione della manutenzione. Il framework introduce un approccio di miglioramento continuo che, utilizzando informazioni aggregate sull'attivit� di manutenzione, permette di introdurre miglioramenti non solo a livello operativo ma anche tattico e strategico. A livello operativo si potrebbero introdurre miglioramenti in termini di processo di erogazione della manutenzione. A livello tattico si potrebbero introdurre miglioramenti in termini di definizione delle politiche di manutenzione. Infine, a livello strategico, le informazioni potrebbero essere utilizzate per migliorare la gestione della capacit� delle risorse. A sostegno del processo decisionale, il framework integra diversi metodi e strumenti, quattro dei quali sviluppati e testati durante lo svolgimento del dottorato. Ognuno di questi strumenti si riferisce ad una specifica fase del framework e mira a supportare attivit� specifiche (ad esempio l?identificazione delle componenti critiche e delle politiche di manutenzione, la selezione del metodo di analisi dei dati, l?assegnazione delle richieste di manutenzione, la raccolta e analisi dei dati di manutenzione).

Nell'ultimo decennio, due macro fenomeni stanno rappresentato una sfida nei confronti delle strategie delle aziende manifatturiere: Servitizzazione e Digitalizzazione (Frank, Mendes, Ayala, & Ghezzi, 2019). Da un lato la possibilit� di affrontare la concorrenza vendendo pacchetti di prodotti e servizi, instaurando con il cliente un rapporto duraturo e basato sulla creazione di valore e dall'altro il progresso nel campo tecnologico che consente lo sviluppo di sistemi e prodotti automatici e intelligenti. All?incrocio dei due, uno degli aspetti pi� rilevanti da considerare � la possibilit� di raccogliere una grande quantit� di dati da fonti connesse che, abbinate ad efficaci strumenti di analisi, possono diventare una fonte chiave di creazione di valore nel contesto della fornitura di servizi. Sebbene le opportunit� in questo contesto siano chiare, la loro realizzazione sta creando difficolt� sia per dal punto di vista accademico che applicativo. In questo contesto, la ricerca presentata in questa tesi, contribuisce alla conoscenza e realizzazione di sistemi prodotto-servizio basati sulla raccolta dati, tramite lo sviluppo di conoscenze sistematiche nel contesto del Data-Driven Product Service System (DDPSS), formalizzando le caratteristiche dei DDPSS in un framework concettuale a due livelli e fornendo una metodologia data-driven di ingegnerizzazione dei servizi per le prime fasi del loro sviluppo. La ricerca � stata sviluppata in collaborazione continua con ABB, azienda che ha sponsorizzato il progetto e nella quale si sono svolte attivit� di action research. Inoltre, grazie al coinvolgimento nel ASAP Service Managemnt Forum, la ricerca ha beneficiato della collaborazione con svariate aziende impegnate nello sviluppo do DDPSS.

Failure Mode, Effects, and Criticality Analysis (FMECA) is a proactive reliability and risk management technique extensively used in practice to ensure high system performance by prioritising failure modes. Owing to the limitations of traditional FMECA, multi-criteria decision-making methods have been employed over the past two decades to enhance its effectiveness. To consider the vagueness and uncertainty of the FMECA evaluation process, an interval-based extension of the Elimination et Choice Translating Reality (ELECTRE) TRI method is proposed in the present paper for the classification of failure modes into risk categories. Therefore, ratings of failure modes against risk parameters are provided in an interval form by a panel of FMECA experts and then properly synthesised to provide a group consensus and improve the accuracy of the results. The relative importance of the risk parameters is also considered. The method is validated using a numerical example relating to the propulsion system of a fishing vessel.

Organometallic perovskites are one of the most investigated materials for high-efficiency thin-film devices to convert solar energy and supply energy. In particular, methylammonium lead iodide has been used to realize thin-film perovskite solar cells, achieving an efficiency higher than 20%. Different fabrication procedures based on the spin-coating technique have been proposed, which do not ensure homogenous morphologies. In this work, we present a scalable process to fabricate methylammonium lead iodide thin films directly on conductive substrates, consisting of electrodeposition and two subsequent chemical conversions. A thorough investigation of the morphological, structural and compositional properties of the layer is performed after each fabrication step. It is demonstrated that this method allows fine control of the thickness of the layer by tuning the cell parameters during the electrodeposition step. X-ray diffraction patterns and energy-dispersive X-ray analysis indicate the achievement of high-purity methylammonium lead iodide layers. Micro-Raman analyses were used to demonstrate the formation of methylammonium lead iodide. Finally, ultraviolet-visible absorption spectra were acquired to determine the optical band edge of the layer ( 1.56 eV) and the absorbance of methylammonium lead iodide as a function of the film thickness. As expected, the material exploits excellent optical properties, achieving an absorption ≥ 99.9% in the entire visible range for a layer thickness of 1.3 µm. The results presented here pave the way for the application of cost-friendly solution-based processes to fabricate high-quality perovskite solar cells.

Cigarette smoke exposure induces oxidative stress within the airways. Increased oxidative burden contributes to the pathogenesis of chronic lung disorders and is associated with aging and chronic inflammation. Airway epithelial cells highly contribute to Reactive Oxygen Species (ROS) generation within injured and inflamed lung tissues. Among ROS, hydrogen peroxide (H2O2) can be monitored in the extracellular space. Herein, we present an amperometric/voltammetric sensor based on gold nanoparticles and graphene oxide able to detect H2O2 with good sensitivity and selectivity. Using this sensor, H2O2 release was measured in conditioned medium from primary bronchial epithelial cells (PBEC), bronchial epithelial cell line, 16HBE, and adenocarcinoma alveolar basal epithelial cell line, A549, exposed to cigarette smoke extracts (CSE). 16HBE were also treated with resveratrol, an anti-oxidant compound. The results were compared with those obtained by flow cytometry using the same cells stained with Carboxy-H2DCFDA and MitoSOX Red, which detect intracellular ROS and mitochondrial superoxide, respectively. The exposure to CSE resulted in a significant increase of the cathodic current due to the reduction of H2O2 indicating an increased release. Addition of resveratrol decreased CSE-induced release of H2O2 in 16HBE. All the results paralleled those obtained by flow cytometry. The proposed sensor is highly sensitive and selective, fast and cost effective and can potentially be applied for real time and easy monitoring of oxidative stress.

In this work, nickel-iron alloy nanostructured electrodes obtained by template electrosynthesis method are investigated for both hydrogen and oxygen evolution reactions. Electrodes consist of nanowire arrays with high surface area that are able to ensures a high electrolytic activity. To obtain different alloy compositions, the concentration of the elements in the deposition baths is appropriately tuned. Results show that the composition of nanowires does not change linearly with the composition of deposition bath but are richer in Fe. Nanostructured electrodes are tested as both cathodes and anodes in 30 wt% KOH aqueous solution, at room temperature to determine the best alloy composition. In all electrochemical tests, the electrodes that performed best are those with iron content of 78.95 at%. Particularly, the results are very promising for the oxygen evolution reaction, with a Tafel's slope of 40 mV and a potential of 1.532 V vs. RHE after 6 h at constant current of 50 mA cm−2. Besides, preliminary tests in 0.5 M NaCl alkaline aqueous solution are also reported showing very promising results.

Maintenance service delivery constitutes one of the most problematic tasks for companies offering such service. Besides dealing with customers expecting to be served as soon as possible, companies must consider the penalties they are incurring if the service is delivered later than the deadline, especially if the service suppliers want to establish long and lasting relationships with customers. Despite being advisable to use appropriate tools to schedule such activity, in many companies, planners rely only on simple tools (e.g., Excel sheets) to schedule maintenance interventions. Frequently, this results in a suboptimal allocation of the interventions, which causes customer satisfaction problems. This paper, contextualised in the Balance Systems case study, proposes an optimisation model that can be used by planners to perform the intervention allocation. The optimisation model has been developed in the context of the Dual-perspective, Data-based, Decision-making process for Maintenance service delivery (D3M) framework, which aims to improve the maintenance service delivery by making a proper use of real-time and historical data related to the asset status and the service resources available. The proposed model tries to cope with the current problems present in the company’s service delivery process by proposing the introduction of a mathematical instrument in support of the planner. Being strongly influenced by the contextual setting, the model discussed in this paper originates from the D3M framework logic and is adapted to the company necessities.

International audience

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.

Fiber-reinforced plastic composite materials are increasingly used in many industrial applications, leading to an increase in the amount of waste that must be treated to avoid environmental problems. Currently, the scientific literature classifies existing recycling technologies into three macro-categories: mechanical, thermal, and chemical, however, none are identified as superior to the others. Therefore, scholars and companies struggle to understand where to focus their efforts. Patent analysis, by relying on quantitative data as a precursor to new technological developments, can contribute to fully grasping current applications of each recycling technology and provide insights about their future development perspectives. Based on these premises, this paper performs a patent technology roadmap to enhance knowledge about prior, current, and future use of the main recycling technologies. The results show that recycling macro-categories have different technology maturity levels and growth potentials. Specifically, mechanical recycling is the most mature, with the lowest growth potential, while thermal and chemical recycling are in their growth stage and present remarkable future opportunities. Moreover, the analysis depicts several perspectives for future development on recycling technologies applications within different industries and underline inter- and intra-category dependencies, thus providing valuable information for practitioners and both academic and non-academic backgrounds researchers interested in the topic.

Following the spread of the Industry 4.0 paradigm, the role of digital technologies in manufacturing, especially in production and industrial logistics processes, has become increasingly pivotal. Although the push towards digitalization and processes interconnection can bring substantial benefits, it may also increase the complexity of processes in terms of integration and management. To fully exploit the potential of technology, companies are required to develop an in-depth knowledge of each operational activity and related human aspects in the contexts where technology solutions can be implemented. Indeed, analyzing the impacts of technology on human work is key to promoting human-centred smart manufacturing and logistics processes. Therefore, this paper aims at increasing and systematizing knowledge about technologies supporting internal logistics working activities The main contribution of this paper is a taxonomy of the technologies that may be implemented in the different internal logistics areas to support a Logistics 4.0 model. Such a contribution is elaborated in accordance with a deductive approach (i.e., reasoning from the particular to the general), and backed up by an analysis of the literature. The taxonomy represents a useful framework to understand the current and possible technological implementations to drive logistics processes towards Logistics 4.0, with specific attention to the relation between human operators and technologies.

The Urban Freight Fleet Composition (UFFC) problem addresses the need of a logistics service provider to define the optimal fleet mix in terms of types and number of vehicles to serve the demand for goods delivery in an urban area. Urban areas can be subject to access restrictions (e.g. based upon the time of the day or vehicles’ characteristics) that could affect the performance of transport assets. In this paper, we consider time-window access restrictions based upon the characteristics of the vehicles, and we propose a human-in-the-loop decision support system (HIL-DSS) architecture using optimisation and simulation models to address the trade-off between vehicles characteristics, revenues, costs, and performance. We formulate both a deterministic and a stochastic optimisation decision model addressing the problem in the context of the HIL-DSS. In doing this, we emphasise the role of the human decision maker in tackling a complex problem affected by variability and uncertainty, and to overcome the rigidity of optimisation models thanks to the possibility to include qualitative information into the process.

International audience; Nowadays, Internet of Things (IoT) platforms are becoming a huge opportunity for companies to collect data from connected machinery and analyse them to increase efficiency in production, optimize maintenance and introduce personalized service offerings. Specifically, multiple users can monitor real-time data and act based on updated information. Nevertheless, few studies are systematically focused on the implementation of Key Performance Indicators (KPIs) in the IoT environment. Based on an empirical case study, the article presents the implementation of dynamic KPI dashboards for an IoT platform, showing the challenges to face related to the trade-off between user desire and companies’ technological readiness.

In industry 4,0, the establishment of an interconnected environment where human operators cooperate with the machines offers the opportunity for substantially improving the ergonomics and safety conditions of the workplace. This topic is discussed in the paper referring to the vibration risk, which is a well-known cause of work-related pathologies. A wearable device has been developed to collect vibration data and to segment the signals obtained in time windows. A machine learning classifier is then proposed to recognize the worker’s activity and to evaluate the exposure to vibration risks. The experimental results demonstrate the feasibility and effectiveness of the methodology proposed.

The delivery of services creates major disruptive change to a business and involves a change management process at different levels of the service chain, thus really representing a journey for the firm and its partners. Strategically, management teams like the idea of developing service business because customers require after-sales services and margins are generally higher than in the traditional product sales business. But considering moving into service just “a good move” without first understanding the underlying barriers risks failure. This chapter provides a conceptual guideline that supports firms and practitioners to understand the change management aspects of servitization. The guideline is based on conceptual literature, combined with empirical data from a major study based on survey and interview data from 150 firms. It aids middle managers in developing an agile roadmap to allow them to take actions that support their strategic vision around servitization.

Increased oxidative burden contributes to the pathogenesis of most inflammatory diseases and is associated with aging and chronic inflammation. Macrophages contribute to the generation of reactive oxygen species (ROS) within inflamed tissues. Currently, ROS generation is measured using fluorescent probes and colorimetric/fluorimetric biochemical assays. Hydrogen peroxide (H2O2) diffuses through the cell membrane and can be monitored in the extracellular space. Herein, we present a sensor for H2O2 detection released by cells in culture supernatants. H2O2 sensing performance was evaluated using chronoamperometric detection. A sensitivity of 0.0641 μA μM−1 cm−2 with a limit of detection of 6.55 μM and excellent selectivity against many interferents was found. H2O2 release was also measured in conditioned medium from human THP-1 macrophages exposed to pro-oxidant and anti-oxidant treatments. The results were compared with those obtained by flow cytometry using the same cells stained with carboxy-H2DCFDA and MitoSOX Red, which detect intracellular ROS and mitochondrial superoxide, respectively. The addition of pro-oxidants lipopolysaccharide (LPS) and nigericin resulted in a significant increase in the cathodic current due to the H2O2 reduction, indicating an increased release of H2O2. The addition of 17-oxo-DHA, which inhibits LPS- and nigericin-dependent responses, decreased the LPS- and nigericin-induced release of H2O2. All the results obtained with the sensor were consistent with those obtained using flow cytometry. The operation of the sensor directly in the cell culture growth medium had no impact on cell viability. The sensor is highly sensitive, fast, and cost effective, and it can potentially be used for real time monitoring of oxidative stress.

Many industrial companies are introducing new automation and digital technologies to improve their manufacturing and logistics processes, thereby implementing the Industry 4.0 paradigm. Nevertheless, choosing and adopting the most appropriate technologies is challenging and requires companies to consider many factors, including human and organizational aspects. This paper aims to present a reference framework to guide the choice of new technological solutions to introduce in manufacturing and logistics processes, starting from identifying the company objectives through a detailed analysis of the tasks and human factors (HF) involved.

COVID-19 has been impacting worldwide supply chains causing interruption, closure of production and distribution. This impact has been drastic on the supplier side and, as a consequence of disruptions, strong reductions of production have been estimated. Such a circumstance forces companies to propose innovative best practices of supply chain risk management aimed at facing vulnerability generated by COVID-19 and pursuing industrial improvements in manufacturing and production environments. As a part of supply chain strategy, supplier selection criteria should be revised to include pandemic-related risks. This article aims to propose an answer to such a problem. In detail, a comprehensive tool designed as a hybrid combination of multi-criteria decision-making (MCDM) methods is suggested to manage important stages connected to the production development cycle and to provide companies with a structured way to rank risks and easily select their suppliers. The main criteria of analysis will be first identified from the existent literature. Risks related to COVID-19 will be then analysed in order to elaborate a comprehensive list of potential risks in the field of interest. The Best Worst Method (BWM) will be first used to calculate criteria weights. The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) will be then applied to rank and prioritize risks affecting suppliers. The effectiveness of the approach will be tested through a case study in the sector of automotive industry. The applicability of the designed MCDM framework can be extended also to other industrial sectors of interest.

In an ever-changing environment, supply chains face countless risks generated by different sources of uncertainty. The adoption of lean management initiatives has been recognized as a viable and effective way for dealing with these uncertainties. However, since constant and rapid change of variables affecting supply chains risks nullifying or diminishing the potential benefits of lean initiatives, identification of proper lean practices emerges as essential to address their successful implementation. On these premises, this study proposes a model linking lean management practices with different forms of supply chain uncertainty. The model, built upon an analysis of the literature, is designed to help managers and practitioners in identifying and prioritizing lean actions to address issues within their supply chains.

In this work, an electrochemical sensor for uric acid determination is shown with a preliminary study for its validation in real samples (milk and urine). Uric acid can be electrochemically oxidized in aqueous solutions and thus it is possible to obtain electrochemical sensors for this chemical by means of this electrooxidation reaction. Indium tin oxide coated on flexible polyethylene terephthalate substrate, modified with reduced graphene oxide and gold nanoparticles by co-electrodeposition, was used. Electrodeposition was performed at -0.8V vs SCE for 200 s. All samples were characterized by electron scan microscopy and electron diffraction spectroscopy. A careful investigation on the effect of pH was performed to understand its influence on uric acid oxidation. The detection of uric acid was using the linear sweep voltammetry. Results show that the peak current increases linearly with uric acid concentration from 10 to 1000 μM with a limit of detection of about 7.1 μM. The sensor shows high selectivity towards different interferents that can be found in the milk and urine matrix, such as chloride, calcium, sodium and ammonium ions. To prove the applicability of the proposed sensor, uric acid was quantified in real milk and urine samples with excellent results comparable to those of conventional techniques.

Highlights • This paper proposes a MCDM framework to support risk evaluation for maintenance activities. • The ANP is proposed to select the best maintenance strategy on the basis of real systems’ features. • The ELECTRE III is used to prioritise the main risks related to the interventions of the selected maintenance policy. • The proposed framework is applied to a core subsystem of a real-world marine salt manufacture firm., This paper intends to contribute with a multi-criteria decision-making (MCDM) framework to support risk evaluation for maintenance activities carried out on critical systems in industry. We propose to first select the best maintenance strategy tailored to companies’ requirements and systems’ features, and second to perform a risk prioritisation aimed at highlighting priorities of intervention. The Analytic Network Process (ANP) is suggested to select the maintenance policy representing the best trade-off considering the complex and varied interdependencies amongst a diversity of clustered elements characterising the system. Then, the main risks related to the interventions associated to the selected maintenance policy are ranked using the ELimination Et Choix Traduisant la REalité III (ELECTRE III) method, using the same criteria weighted by the previous ANP application. This hybrid MCDM framework is applied to a core subsystem of a real-world marine salt manufacture firm.

Construction is nowadays considered an extremely energy intensive industry and one of the main sources of environmental pollution in the world. Therefore, the research and the development of novel energy-saving manufacturing processes and sustainable construction materials is more than ever urgent and challenging. This paper aims at identifying the industrial process for the production of novel geopolymers to be used as a greener substitute for cement, especially the Portland one, widely used for structural applications to significantly reduce the environmental impact of the construction industry. Here, the materials sustainability and the manufacturing process are improved by valorising and reusing wastes, deriving from the pulp-paper industry, as raw materials. This industry generates a great quantity of wastes that represent a real concern both for their environmental impact and cost of disposal. The new industrial process was evaluated after scaling up the laboratory procedure to an industrial dimension. Consequently, each small-scale process was deeply analysed (raw materials involved and processes) and transposed into a massive-production. The most relevant processes that show an elevated environmental impact were identified and the energy consumption of the whole process has been assessed resulting, for the analysed geopolymeric product, an embodied energy of 645 MJ/ton, being about one sixth of the OPC. Moreover, a preliminary economic analysis has been conducted in terms of raw materials involved in the proposed industrial process revealing a decreasing cost per ton increasing the waste recycling. All considered, the main conclusions are that the industrial scale up of the proposed geopolymeric product, assessed for the first time in literature along with the related proposed considerations, could be highly competitive to the Portland production involving greener processes with a much lower energy consumption and a greater financial saving by improving the wastes quantity.

Coffee is one of the most important commodities in the world. Every year the coffee industry is responsible for generating a large amount of wastes, mainly Spent Coffee Grounds (SCGs). The traditional disposal of this residue into the environment should be avoided due to its toxicity and organic character. Because of the decrease in nonrenewable natural resources, society has been making a huge effort to valorize and reuse several types of wastes in the production of novel sustainable products. In this regard, construction is considered one of the most energy-intensive sectors. As a consequence, the goals of sustainability and energy efficiency must be prosecuted to achieve the results expected by the recent European directives and national regulations. The present paper aims at providing further knowledge on wastes recycling, analyzing the influence of the SCG incorporation as an aggregate in construction materials. To this purpose, the produced mortar specimens are firstly characterized. Afterwards, engineering properties as well as environmental and economic aspects are taken into account to rank the considered mixtures by a multicriteria approach. The performed analysis highlights how the addition of the considered industrial wastes is strongly recommended to improve the performance of materials intended for various applications in construction.

The paradigm of Industry 4.0 allows to increase the efficiency and effectiveness of the production. Companies that will implement advanced solutions in production systems will increase their level of competitiveness and will be able reach high market shares. The present paper is focused on the development of advanced digital solutions to be implemented on a close power loop test bench designed to test high power transmissions for naval unit. In particular, the test configuration consists of a back-to-back connection between two identical mechanical reducers. Since the efficiency of these systems are very high, it is not necessary to use large electric motors, thus managing to contain the operating costs of the testing phase. The particular test bench allows to size the electric motor simply based on the dissipated power by the kinematic mechanisms. By means of suitable sensors installed on the test bench it is possible to extrapolate countless technical data. The implementation of Industry 4.0 enabling technologies allows to evaluate the increase in efficiency compared to traditional systems in terms of reduction of noise and vibrations, efficiency of lubrication, reduction of consumption, installation and maintenance cost of the entire system.

The COVID-19 Pandemic has caused an economic breakdown, especially in the manufacturing industry. Manufacturing companies have used Digital service to stay in contact with their customers and as a source of revenue even during the general lockdown An exploratory focus group has been carried out to understand the problems and opportunities manufacturing companies went and are going through and to suggest open research questions that both research and industry should explore further. To deeply analyses the content of the discussion, Latent Dirichlet Allocation (LDA) was used to identify the main research topics. 4 topics were identified as the most relevant to be investigated: digitalization and collaboration emerged as the most interesting trends that will characterize the new normal. For each of the topics, insights, critical points and research questions are presented and discussed, reporting the main evidence of the focus group discussion.