ABSTRACT. This extended abstract outlines a framework for product design that encourages emotional responses by combining experiential and analytical methods. It introduces a "second life" concept, where participants engage creatively with a product - specifically packaging - by reinterpreting its form and significance. To quantitatively measure these responses, questionnaires and eye tracking systems analyze correlations between users' emotions, attractive and physical feactures. By integrating this approach with structured feedback, the methodology provides valuable insights into how design elements influence emotional experiences, ultimately guiding the development of user-centered products. Preliminary results reveal moderate correlations between specific emotional states, such as curiosity, joy, and fascination, and eye tracking metrics, highlighting the potential of visual behaviour as an indicator of emotional engagement.

ABSTRACT. The development of human-centered products is becoming increasingly relevant, for the Industry 5.0 context. The present study describes the development of an industrial quality control prototype for the ceramic industry. The case study consists of two participatory design sessions, in which user experience and opinions were systematically collected and analyzed. On the first session, the novel Unified Theory of Acceptance and Use of Technology for industry model was introduced to assess worker acceptance of the prototype. The second session included a cognitive walkthrough and a usability questionnaire regarding the perceived ease of use, usefulness and satisfaction from using the prototype for the first time. The goal is to enhance informed decision making with increased user acceptance and integration requirements, both for the management and product development of the prototype. This work highlighted the advantages of integrating a Human-centered design approach in product development to increase product acceptance and user satisfaction.

ABSTRACT. The transition towards a Circular Economy has prompted the development of various frameworks aimed at improving circularity in product design. However, existing methodologies present limitations in effectively implementing circular approaches to product development. This study proposes a structured decision-making framework to overcome these challenges, applied to an industrial case study that emphasizes profitability, circularity, and functionality. The findings highlight critical design elements requiring refinement, particularly concerning structural stability and vibrational performance. By incorporating circular design principles, the approach enhances product longevity, sustainability, and market adaptability in the market. Future research will focus on experimental validation of the framework through real-world application in industrial settings, assessing its effectiveness in improving material efficiency, structural performance, and cost optimization.

ABSTRACT. Resin Transfer Moulding (RTM) is a technology that allows the manufacturing of high-performance composite structures with a low-cycle time process. It consists of injecting resin pre-mixed with hardeners into a closed mould. This mould, in which an internal cavity holds a stack of fibres for reinforcement, determines the final geometry of the structure. The hardeners used in this process play a crucial role. High injection pressures and a fast resin flow front are necessary for their quick curing. Many variations exist for this process; some use even higher pressures, such as High-Pressure Resin Transfer Moulding (HP-RTM), some use a vacuum on one end of the mould, such as Vacuum-Assisted Resin Transfer Moulding (VARTM), and others use staged compression, such as Compression Resin Transfer Moulding (CRTM), whose main goal is to perform the process with as few defects as possible while adapting to the complex shape of the structure and the properties of the resin being used. A critical concern with this process is the lack of data about the resin flow front during the injection phase. Generally, researchers position a grid of sensors along the mould to address this challenge and aid in understanding the phenomenon. However, this approach incurs significant expenses; on the other hand, the sensors could interfere with the composite structure's mechanical performance by causing superficial defects. The sensors' placement limits the information about the flow front to specific individual points. Additionally, the price of accurate and durable sensors is very high, and more machining operations and support systems are needed to properly read and understand the data that is generated. This study focuses on developing a surrogate model to predict the resin flow front in an RTM process. It's important that this model doesn't use as much computing power as a finite element approach so that it can be used in a control system with embedded computing. Using this different model is a beneficial way to solve the inverse problem of resin infusion in real time, which leads to the creation of a control method based on a model-predictive approach. It achieves its objective by continuously estimating the resin flow front and contrasting these estimates with real-time data collected from various sensors. The model proposed to be used along this methodology is based on a neural network approach. Once neural networks are set up to work with a certain problem, they can quickly compute a response compared to other numerical methods like finite differences or finite elements. On the other hand, to tune the neural network for the specific problem, it is required that some data be available. This data is mandatory to determine a specific set of parameters that fits such data. Since obtaining the data from real experiments is costly, we rely on numerical simulations. In this studresin injection simulationsons of the resin injection using Abaqus to build a training dataset. We perform these simulations under various boundary and initial conditions to gather as much training data as possible. The main goal of simulating a range of possible boundaries and initial conditions is to tune the neural network parameters to be able to reproduce any of those scenarios. The simulations are then calibrated by performing a set of physical tests. For the physical tests, a series of injections are made, the inlet pressure is recorded, and the time at which each of the spread resin sensors picks up the flow front is recorded.For the physical tests, a series of injections are made, the inlet pressure is recorded, and the time at which each of the spread resin sensors picks up the flow front is recorded. The collected data has the objective of minimising the uncertainties about the properties of the materials and components that compose the RTM process that are generated between the mathematical model represented by the computational software and the real physical system. After compiling the dataset for the neural network model, the first step is to define the model's architecture. The architecture consists of the number of neurones per hidden layer, as well as the number of hidden layers. The neural network is described as a fully connected, sequential network, and all of its activation functions will use the hyperbolic tangent to deal with negative values for the weights and biases that are inside the network. The selected optimiser for the training stage of the neural network is Adam, due to its simple implementation. To integrate this surrogate model with a control system, there has to be feedback between the digital system and the physical system. Such communication is performed using a set of distributed sensors placed along the mould that provide information about the resin flow front at each location. An edge computing system will connect the sensors to in-house equipment for data collection and processing. Together with the real-time estimate of the resin flow front and the data from the sensors, the control system can figure out the right injection pressure to fill the mould as much as possible while avoiding dry spots. An in-house experimental procedure characterises the material to determine the permeability of the reinforcement for the first simulation. The reinforcement consists of nine layers of fabric—four aramid layers and five carbon fibre layers. We compress the stack to achieve a thickness of 3 mm. The average permeability obtained was 3.16 × 10-12 for the "x" direction and 3.16 × 10-12 for the "y" direction. For practical purposes, the permeability is considered homogeneous; for the "z" direction, the permeability value is defined with the same value due to the thickness being much smaller than the other two main directions. We derived other key parameters, such as density and capillary pressure, required to simulate the resin propagation in an unsaturated conditions medium.By developing this solution, we hope to be able to eliminate the need for the use of a large number of in-mould sensors to track resin propagation during the RTM process. As a follow-up to the model creation and training with a physics-based simulated dataset, experimental tests are done in a laboratory environment using a mould instrumented with several resin flow and cure sensors to validate the model and dataset created. This approach enables the creation and training of future models for various parts, eliminating the need for costly moulds. The study shows how important permeability is for simulation accuracy and convergence. This will help with making changes in the future after experiments are confirmed. After the experiments are done, the numerical simulation will be used to make the dataset that will be used to train the neural network-based surrogate model. We hope that this work will help us create a substitute model for the injection process using neural networks that is easier to compute than the Abaqus numerical model. This offers the advantage of processing the information locally, using low-cost hardware like a Jetson Nano Orin, which is an ARM-based single-board computer with a coupled Nvidia graphics card to perform a significant amount of inferences. Those inferences will serve as possible solutions to the real physical process and, with the information gathered from the installed sensors, solve the inverse problem. To get a good idea of where the resin flow front is, we can solve the inverse problem and use the definition of a virtual sensor. The virtual sensor gets rid of the need to set up an expensive network of sensors, which not only adds a lot to the initial cost of the project but also damages the surface, making the final product less mechanically sound.

ABSTRACT. The introduction of the industry 5.0 framework marked a shift in the robotics field, which led to the creation of collaborative robots with the goal of enabling a safe human-robot collaboration in factories. However, ensuring worker safety extends beyond just the robot, as robotic grippers, which allow object manipulation, also pose as a safety risk. Therefore, there is a need to develop grippers for collaborative applications that are not only characterized by their performance during the handling process, but also by their adherence to Ecodesign principles and their contribution to the creation of a circular economy. This paper focuses on this issue by proposing a development process that outlines strategies that can be used to create a gripper that meets both environmental and performance objectives. Through the initial application of the methodology, it was possible to assess that it is crucial to directly relate the functional requirements of the gripper with Ecodesign goals. The gripper was divided into three major modules: structure, pneumatical material and suction cups. This study emphasizes the importance of integrating sustainability considerations into the design of robotic grippers, paving the way for more efficient, safe, and environmentally responsible solutions in collaborative robotics.

ABSTRACT. This paper presents a methodological framework for design for remanufacturing (DfRem), aimed at optimizing remanufacturing in the product development phase, detailing several possible strategies for it. The study focuses on a turn counter, integrated in a stone cutting machine, whose inefficiencies were identified, such as excessive component parts, weight and complexity. Ultimately, Additive Manufacturing (AM) was incorporated as a DfRem strategy, resulting in a redesigned turn counter, reducing its number of parts by 23%, its weight by 75%, and production costs by 90%. The redesigned product demonstrated improved modularity, material efficiency, and easier assembly/disassembly. This case study showcases the potential of AM to enhance remanufacturing, making it more cost-effective and sustainable.

ABSTRACT. This study explores the integration of Design for Safety (DfS) methodologies in the development of a collaborative robotic palletizing system. Through the incorporation of a sensorized gripper with an integrated bumper, a hybrid safety monitoring system that combines laser scanners and radar sensors, and a risk-adaptive control mechanism, the system enhances operator safety while maintaining operational efficiency. The research also includes a structural static analysis of the gripper using Ansys software, assessing three material options (PA12, carbon fiber-reinforced nylon, and T6 aluminum alloy) to optimize structural performance and weight. The proposed safety solutions align with ISO 10218-2:2025, ISO/TS 15066:2016, and the European Machinery Directive (2006/42/EC), contributing to improved human-robot collaboration in industrial automation.

ABSTRACT. Traditional gripper design methods often struggle to address the diverse challenges posed by varying object geometries, materials, and contact dynamics, leading to limited adaptability and tactile perception in robotic manipulation. To address this gap, this article proposes a five-phase framework that combines Virtual Reality simulation and real-time haptic interaction to evaluate gripper functionality and task performance before physical prototyping. The framework was applied to a hybrid gripper that features extensible branches and suction capabilities with a Virtual Reality environment developed in Unity. In this setup, human hand movements were mapped to the actions of the gripper via a haptic glove. Results demonstrate the successful integration of the gripper model and the preliminary environment. This study highlights the framework’s potential to accelerate gripper development, lower costs, and improve usability by aligning technical specifications with human factors.

ABSTRACT. The integration of Design for Automation (DfA), Design for Edge Services (DfES) and Design for Manufacturing (DfM) plays a cru- cial role in optimizing industrial processes, especially in predictive main- tenance. This paper presents an integrated design approach to imple- ment a vibration-based predictive maintenance system in stone cutting machines. By leveraging IoT sensors, Edge Computing and automation strategies, the study explores how smart design can increase operational efficiency and reduce maintenance costs. The proposed system architec- ture enables real-time vibration analysis at the Edge, minimizing la- tency and enabling faster decision making. Experimental validation is conducted in an industrial environment, demonstrating the effectiveness of the approach in detecting early signs of machine failure. The results highlight the advantages of an Edge-based predictive maintenance frame- work over traditional cloud-based solutions. This work contributes to the advancement of Industry 4.0 practices by providing insights into how in- tegrated design methodologies can improve reliability, sustainability, and cost-effectiveness in manufacturing environments.

ABSTRACT. The presented paper focuses on the implementation of a risk assessment model that employs predictive maintenance practices in a real industrial environment and its integration with a mechanical systems analyser. Older legacy machines often do not come equipped with the required technology to integrate the modern Industry 4.0 patterns, as such, it becomes relevant to develop methodologies that allow to retrofit those machines. Many are the sensors relevant to predictive maintenance and risk assessment, including thermometers, vibration sensors and current analysers. However simply attaching sensors to machinery is not enough to extract useful contextual information without machine-specific rules. The demonstrated model is inspired on an older mechanism invented to regulate the steam engine named “centrifugal governor”. This solution integrates the functioning of that system with artificial neural networks to portrait, in real time, the current state of health of a working piece of machinery. The neural network is trained on real historical data from the machines and by learning decay patterns it can extrapolate the current condition of different components, reflecting that in a model of the centrifugal governor which reacts accordingly to advert of any eminent dangers or risks.

ABSTRACT. This paper focuses on an application of Large Language Models (LLMs) in the industry sector, fusing the summary and interpretation capabilities of these models, with sensor data to evaluate the condition of IoT devices. The objective was to elaborate a system which would leverage the documentation provided by the manufacturer of a machine, as well as sensors connected to it to create an assistant which is able to use external application programming interfaces (APIs), based on the interpretation of safety parameters and current sensor levels, to regulate the performance and maintenance of a machine. This enables factory personnel and managers to better grasp the proper functioning of hardware, communicate, and act on equipment which might be performing poorly with the assistance of models that have knowledge of the domain. Furthermore, the capabilities of LLMs to interpret API endpoint documentation were tested as well as the ability to formulate HTTP requests on those same endpoints. The implementation of this system allows API calls to be performed automatically by command of an LLM assistant, without requiring user approval, even if it may be integrated for added security in critical cases. The usage of this system provides yet another practical application of LLMs that contributes to the automatization of the shopfloor while improving the flow and monitorization of the assembly line, ensuring the establishment of foundational guardrails the provide active continuous safety mechanisms following Industry 4.0 standards.

ABSTRACT. This paper presents an enhanced OPC UA-based architecture using model-driven device descriptions to improve interoperability and scalability in industrial environments. Developed within the PRODUTECH R3 initiative, the system targets remote monitoring and control of mobile industrial machines by leveraging OPC UA’s semantic modeling strengths. Building upon the SmartObject concept and integrating lessons from prior deployments, the architecture addresses synchronization and scalability challenges previously identified in industrial IoT systems. Data acquisition is performed via Modbus RS485, with centralized processing and semantic structuring through OPC UA, and operator interaction facilitated via a browser-based GUI. The pilot deployment involving 30 sensors validated the system’s robustness and usability. This work contributes a practical, standards-aligned path for integrating legacy devices into Industry 4.0 infrastructures, supporting predictive maintenance and sustainable manufacturing goals. Future work will address real-time constraints and generalization of the information model for broader industrial applicability.

ABSTRACT. The increasing demand for sustainable manufacturing practices requires industries to adopt advanced technologies that optimize resource use while maintaining high product quality. This study explores the role of automated quality control systems, particularly vision-based inspection technologies, in enhancing industrial efficiency and sustainability. By integrating real-time monitoring, data analytics, and data-driven decision-making, these systems minimize material waste, reduce energy consumption, and improve overall production efficiency. The research highlights how vision systems enable proactive defect detection, reducing both immediate waste and the need for overproduction, thereby optimizing resource allocation. The study also underscores the significance of traceability, compliance, and auditability, as automated systems systematically document quality parameters, ensuring regulatory adherence and facilitating industry-wide accountability. Moreover, the findings emphasize the transfer of knowledge and technology between sectors with different automation maturity levels, accelerating the adoption of advanced quality control solutions. Finally, the research supports the transition from Industry 4.0 to Industry 5.0, advocating for a more sustainable, and intelligent manufacturing paradigm.

ABSTRACT. This paper presents a comprehensive framework, and an assessment toolbox aimed to assist manufacturing companies in navigating their transformation journey toward sustainable zero-defect manufacturing. Specifically, they support assessment and decision-making across strategic, tactical, and operational levels, and incorporate a balanced consideration of key manufacturing competitive priorities, including economic, environmental, social, and innovation aspects. In doing so, the paper contributes to advance current research and practice on sustainable zero-defect manufacturing by offering an integrated approach and toolbox that facilitate alignment of technical innovations with organizational needs and sustainability outcomes.

ABSTRACT. As industries shift toward more sustainable manufacturing practices, green manufacturing and eco-efficiency play a crucial role in reducing environmental impact while enhancing economic performance. Green manufacturing integrates environmentally friendly processes and technologies to minimize waste, reduce energy consumption, and optimize resource utilization. Eco-efficiency complements this by improving process efficiency to achieve sustainability without compromising industrial growth. In this context, OPeraTIC presents an innovative manufacturing platform that leverages high-power Ultra-Short Pulsed Lasers (USPL) to advance green manufacturing through precision surface processing. The OPeraTIC platform addresses key industrial challenges by offering an open, interoperable, and expandable architecture that enables the adoption of laser microstructuring for large 3D parts. The project enhances productivity and quality through three primary developments: (i) advanced optical modules for beam transport and manipulation, (ii) a dexterous and precision robotic manipulator, and (iii) AI-enhanced process planning and adaptability. By overcoming existing industrial barriers, OPeraTIC establishes a sustainable alternative to traditional surface processing methods, reducing energy consumption and material waste. A core innovation within OPeraTIC is its modular and automated routing of optical components, ensuring versatility and replicability in beam delivery, management, and metrology. This includes the use of polarization-maintaining fibres for beam transport, dynamic control beam shaping for optimized energy distribution, and novel optical setups for real-time process and product monitoring. These advancements enable high-precision, high-efficiency laser-based surface processing, reducing reliance on environmentally harmful conventional techniques. To scale up USPL technology for large-envelope and complex-trajectory applications, OPeraTIC introduces a system architecture based on RAMI4.0-compliant controllers. This integrates specialized robotic manipulation with high-level CNC motion accuracy, ensuring full synchronization of motion, laser processing, and quality control. By seamlessly merging automation with advanced manufacturing intelligence, OPeraTIC enhances precision and repeatability, making it viable for industrial applications with stringent quality standards. Additionally, OPeraTIC’s Industry 4.0-compliant platform facilitates systematic data exchange and integrated bidirectional communication using Automation-ML and OPC-UA standards. This fosters real-time interaction between physical systems and their digital twins, supporting a Machine Intelligence Framework for Zero Defect Manufacturing (ZDM). The incorporation of AI-driven monitoring and control strategies allows predictive maintenance, process optimization, and adaptive manufacturing, further reinforcing sustainability goals. The impact of OPeraTIC is demonstrated through four large-scale industrial use cases spanning the automotive, aeronautics, lighting, and white goods sectors. The results of OPeraTIC showcase the feasibility of USPL-based green manufacturing, offering an economically and environmentally viable alternative to conventional surface processing. Through its innovative approach, OPeraTIC aligns with global sustainability initiatives by significantly reducing the carbon footprint of manufacturing processes while enhancing productivity and precision. This work highlights how intelligent automation, AI-driven process control, and modular laser technology can revolutionize industrial manufacturing, paving the way for a new era of eco-efficient production.

ABSTRACT. Defect detection plays a critical role in ensuring product quality and reducing waste in manufacturing. Traditional visual inspection methods have been increasingly replaced by automated solutions leveraging computer vision and machine learning techniques. Among these, unsupervised learning approaches offer significant advantages by eliminating the need for labelled datasets, thus improving scalability and adaptability to diverse defect types. This study benchmarks unsupervised deep learning architectures for defect detection in woven textile labels, using as sample a label for the automotive industry produced via Jacquard weaving. Up to the moment, two architectures proposed in the literature have been assessed: a Variational Autoencoder with L2 + SSIM loss and Adversarial Feature Fusion GAN. The preliminary results highlight the challenges faced in unsupervised learning-based approaches, namely regarding reconstruction quality and anomaly detection ability, emphasising the need for further research to enhance reliability in industrial inspection systems. Future work will aim at further hyperparameter tuning and implementing additional architectures to reach more comprehensive results.

ABSTRACT. Recycling multi-material composites in the automotive industry, particularly those combining metals and polymer matrix composite, presents significant challenges due to the strong adhesion between the materials. This complicates their separation, resulting in higher recycling costs and increased environmental concerns. Based on previous studies that explore cryogenic treatment to promote material segregation by embrittling the metal-polymer matrix composite interface, this study evaluates its effect on the metallic insert coatings. Results show no significant mass loss, indicating that cryogenic treatment does not affect the coating. However, some experimental data suggest that the material separation process may impact the zinc coating, potentially compromising the integrity of the inserts and their reusability in the manufacturing process. The results indicate that if precautionary measures are taken during the cryogenic cycle and the removal process, the integrity of the bolts is not compromised, allowing the inserts to be reused.

ABSTRACT. Introduction The increasing demand for sustainable alternatives to fossil-based resources has driven significant research into bio-based materials (Souza et al., 2020). Lignocellulosic biomass, derived from plant sources, offers a renewable feedstock for producing biofuels, biopolymers, and advanced nanomaterials (Becker & Wittmann, 2019; Cao et al., 2019, Blasi et al., 2023). This biomass can be sourced from various origins, including wastes from agricultural and industrial lignocellulosic crops (Pires et al., 2019a). These wastes provide a stable and renewable supply of cellulose, hemicellulose, and lignin, the three main components of lignocellulosic biomass (Isikgor & Becer, 2015), which can be converted into high-value nanomaterials. Nanocellulose (NC), a nanoscale bio-based material, is obtained by isolating cellulose from lignocellulosic fibers and subsequently depolymerizing it. Due to its abundance, biodegradability, renewability, and outstanding mechanical properties, NC has gained interest in various fields, including automotive manufacturing, agriculture, medicine, the food and biotech industries, and energy. Additionally, when incorporated into biobased polymers, NC functions as a nanoreinforcement, improving their mechanical strength and permeability, thereby expanding their industrial applications (Pires et al., 2019b; Pires et al., 2019c).

Objective of the Article This study aimed to assess the potential of NC derived from lignocellulosic biomass as a reinforcement in biobased films. Specifically, it investigated the production of nanocrystalline cellulose through an alkaline pre-treatment followed by acid hydrolysis and its incorporation into biobased films at different concentrations. The study also compared the performance of biomass-derived NC with commercial NC and evaluated its impact on the mechanical and barrier properties of the films.

Methodology • Production of Nanocrystalline Cellulose (NC): NC was obtained from lignocellulosic biomass through an alkaline pre-treatment followed by acid hydrolysis. The alkaline pre-treatment removed non-cellulosic components, while acid hydrolysis facilitated the breakdown of cellulose fibers into nanoscale crystals. • Film Preparation: Biobased films were produced via solvent casting. NC was incorporated at different concentrations (1.5–2.5% w/v in the film-forming dispersion) to evaluate its reinforcement effects. Films without NC served as controls, and commercial NC was also tested for comparison. • Characterization of Biobased Films: The prepared films were analyzed for: o Mechanical properties – tensile strength, elastic modulus, and elongation at break; o Barrier properties – permeability to water vapor and oxygen; o Physical properties – thickness, optical properties (opacity and transparency), surface color, solubility, and swelling behavior.

Results The incorporation of NC into biobased films significantly influenced their mechanical and barrier properties. The tensile strength of the films increased by 13%, while the elastic modulus improved by 33%, indicating enhanced rigidity. However, the flexibility of the films was reduced, as reflected by a 68% decrease in elongation at break, suggesting a higher tendency to fracture under stress. The barrier properties of the films were also positively affected by NC incorporation. Water vapor permeability decreased by 10%, and oxygen permeability was reduced by 36%, demonstrating an improvement in protective capabilities. Despite these enhancements, the solubility of the films remained unchanged, while swelling doubled in comparison to the control films. No significant differences were observed between films reinforced with NC derived from lignocellulosic biomass and those containing commercial NC. Nevertheless, biomass-derived NC exhibited slightly superior barrier properties, although this advantage was accompanied by a further reduction in elongation at break. Increasing the NC concentration from 2.0% to 2.5% led to improved barrier performance. However, the mechanical strength showed minimal improvement, while flexibility was further compromised. These results indicate that lignocellulosic residues can serve as a viable raw material for NC production in bionanocomposites. However, further research is needed to optimize the incorporation process and improve the balance between mechanical strength and flexibility in the resulting materials.

Theoretical Implications The findings of this study help expand knowledge on the use of NC as a reinforcement material in biobased polymers. The results confirm that NC enhances mechanical strength and barrier properties, aligning with previous research (Srivastava et al., 2021; Ge et al., 2024; Xu et al., 2024). Notably, the comparable effectiveness of lignocellulosic biomass-derived NC and commercial NC reinforces the potential of biomass residues as a sustainable feedstock for nanocellulose production. These insights support the development of bio-based nanocomposites with improved functional properties, which could advance applications in sustainable packaging, coatings, and other materials requiring enhanced mechanical and barrier characteristics. Additionally, the study highlights the trade-off between mechanical strength and flexibility when incorporating NC, emphasizing the need for further research to optimize its integration into polymer matrices. Future work should focus on refining processing techniques to maximize the benefits of NC while mitigating the reduction in elongation at break.

Practical Implications The results of this study demonstrate the feasibility of using lignocellulosic biomass-derived NC as a sustainable alternative to commercial NC for reinforcing biobased polymers. The observed improvements in mechanical strength and barrier properties suggest that NC can enhance the durability and functionality of biodegradable films, making them more suitable for industrial applications, particularly in packaging and coatings. The comparable performance of biomass-derived NC and commercial NC indicates that agricultural and industrial lignocellulosic residues could serve as cost-effective and eco-friendly raw materials for NC production. This could reduce reliance on commercial sources, lower production costs, and contribute to a circular bioeconomy by valorizing biomass waste. However, the reduction in film flexibility with increasing NC content highlights the need for process optimization to maintain mechanical integrity while improving functional properties. Future industrial-scale applications should explore modified processing techniques and formulations to balance these properties, ensuring the practical viability of NC-based biopolymer films for commercial use.

Limitations Although lignocellulosic biomass-derived NC shows strong potential as a reinforcement in biobased films, some aspects require further exploration. One consideration is the reduction in elongation at break, which suggests a trade-off between mechanical strength and flexibility. Optimizing the formulation and processing conditions could help achieve a balance that meets industrial needs. Scaling up NC production is another important factor. While this study was conducted at a laboratory scale, assessing the feasibility of large-scale extraction from lignocellulosic biomass is essential. Further research into biomass variability, pretreatment efficiency, and process scalability will help ensure consistent NC quality. Additionally, while key properties such as mechanical strength and barrier performance were evaluated, other characteristics such as biodegradability, thermal stability, and interactions with different biopolymer matrices need further investigation. Expanding the scope of future studies in these areas will provide a more comprehensive understanding of NC-based bionanocomposites and their commercial potential.

Innovation This study contributes to the field of sustainable materials by demonstrating the viability of NC derived from lignocellulosic biomass as a reinforcement in biobased films. Unlike conventional approaches that rely on commercial NC, this work explores as alternative source agricultural and industrial residues, promoting a circular economy and reducing dependency on commercial products. The innovative aspect of integrating an alkaline pre-treatment followed by acid hydrolysis to extract NC from lignocellulosic biomass not only enables the valorization of waste materials but also provides a competitive alternative to traditional NC sources, with comparable mechanical and barrier properties. Furthermore, the study identifies an optimal NC incorporation range, highlighting the balance between improved mechanical strength and barrier properties while minimizing adverse effects on flexibility. These findings provide valuable insights for future material design, advancing the development of high-performance, bio-based nanocomposites with potential applications in sustainable packaging and beyond.

Conclusion This study demonstrated that NC derived from lignocellulosic biomass can serve as an effective reinforcement in biobased films, improving their mechanical strength and barrier properties. The incorporation of NC enhanced tensile strength and elastic modulus while also reducing water vapor and oxygen permeability. However, a trade-off was observed, as the addition of NC led to a decrease in elongation at break, impacting film flexibility. No significant differences were found between films reinforced with biomass-derived NC and those incorporating commercial NC, suggesting that lignocellulosic residues are a viable and sustainable alternative for NC production. These findings reinforce the potential of biomass-derived NC in the development of high-performance bionanocomposites, contributing to the advancement of bio-based materials with applications in sustainable packaging and other industries. Future research should focus on optimizing NC incorporation techniques to further enhance film performance and overcome limitations related to flexibility, ensuring its broader industrial applicability.

Keywords Nanocellulose; Lignocellulosic Biomass; Bionanocomposites; Biobased Films; Sustainable Materials.

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Xu, Y, Wu, Z, Li, A, Chen, N, Rao, J, Zeng, Q (2024) Nanocellulose Composite Films in Food Packaging Materials: A Review. Polymers, 16, 423. https://doi.org/10.3390/polym16030423

ABSTRACT. Ultrasonic spray coating and atmospheric plasma jet are advanced surface modification technologies that provide sustainable and efficient alternatives to conventional treatment methods. Ultrasonic spray coating enables precise and uniform deposition of functional coatings using high-frequency vibrations to generate a fine mist, ensuring minimal material waste and eliminating the need for hazardous organic solvents. Atmospheric plasma jet, operating at atmospheric pressure, modifies surface properties by generating ionized gas, enhancing adhesion, wettability, and overall material performance without requiring vacuum conditions or harsh chemicals. When combined with precursor deposition, plasma technology allows the formation of specialized coatings with tailored functionalities, such as hydrophobicity, antimicrobial resistance, and gas barrier properties. CeNTI has successfully applied these technologies to various substrates, including cellulosic, polymeric, metallic, and natural materials such as stone and cork, demonstrating their versatility in sustainable material processing. The effectiveness of these approaches is illustrated through three case studies: the enhancement of gas barrier properties in biopolymer-based films for packaging, where plasma pre-treatment significantly improved surface wettability and adhesion, leading to a 67% reduction in water vapor transmission rate (WVTR) and a 98% decrease in oxygen transmission rate (OTR); the plasma-activated biocoloration of cotton textiles, which increased the adhesion of natural antioxidant-based dyes and improved wash durability from 50% to 93.9%; and the development of an anti-fogging coating for polycarbonate substrates, where plasma-assisted deposition ensured stable anti-fogging properties before and after water cleaning. These results highlight the potential of atmospheric plasma and ultrasonic spray coating as scalable, eco-friendly technologies for advanced material applications. By eliminating chemical primers, reducing solvent usage, and lowering energy consumption, these methods contribute to more sustainable manufacturing processes while ensuring high-performance surface functionalities.

ABSTRACT. Automating the handling of rigid, porous, and fibrous polymer fabric pads for automotive acoustic applications, currently a manual and challenging process due to their texture and stiffness, is the focus of this research. The study explores a range of robotic gripper technologies – including vacuum suction, high-airflow systems, Bernoulli ejectors, needle penetration, Velcro, adhesives, cryogenics, mechanical friction, and electro-adhesion – designed to overcome these challenges. A custom measurement system and industrial robot were used to evaluate the grip strength (normal and shear) and potential material damage. The comparative analysis of these technologies provides crucial guidance for engineers in selecting and optimizing automated handling solutions for non-woven polymer fabrics.

ABSTRACT. Objective of the article: The transition to a circular economy is key to reducing pressures on natural resources1. This transition begins at the research and innovation level, by investigating and demonstrating value-added pathways that make circularity possible. As global waste generation continues to rise, innovative valorisation strategies are essential to transition from linear waste management to a circular economy. Conventional recycling methods sometimes fail to fully exploit the value embedded in complex waste streams, leading to resource inefficiencies and environmental burdens. To address these challenges, an integrated waste valorisation approach is being explored, that leverages the combination of conservation, mechanical and (bio)chemical processes, offering a more tailored and effective solution that can explore the value of more varied and complex waste originating from different industrial sectors. This approach also prioritizes higher ranks of the waste management hierarchy, namely reusing and recycling, instead of recovery strategies such as gasification and pyrolysis. This multi-step strategy maximizes resource extraction while minimizing residual waste, reducing reliance on virgin resources and lowering environmental impact. In this context, the present paper explores different approaches to valorise different residues, describes the potential of an integrated waste valorisation line, and shows some examples of the application of the valorised resources in new value-added functional materials, fostering a circular economy.

Methodology: To promote circularity and maximize the valorisation of industrial residues and by products, a simple yet effective strategy has been followed that considers the sequential combination of treatment processes, aiming at zero-waste: i) Pretreatment for conservation This may include freezing, drying, dehydration and/or sterilising processes (more relevant for perishable residues) to minimize degradation processes and increase storage time. ii) Mechanical processing Milling and grinding processes aimed at particle size reduction and uniformization, either as preparation for the subsequent treatment processes, or for compatibilization of the micronized material for direct application. iii) (Bio)Chemical processing Conventional and (pressure, ultrasounds, microwave, supercritical fluids) assisted chemical methods for the extraction and recovery of bioactive agents, functional compounds and chemical elements of previously mechanically processed wastes, as well as chemical recycling reactions of organic and synthetic materials. Additionally, chemical processes are also used as pretreatment before biochemical processes, such as enzymatic reactions and fermentation. iv) Revalorization of remaining residue after processes in iii). Any residue remaining after (bio)chemical processing, can be filtered, recovered, and reintroduced in the sequential process for further valorisation until no waste remains.

The approach can be tailored to the properties of the resource material, its potential for valorisation and envisioned application pathway.

Results: A few examples of this approach, using all or some of the described steps, are provided as follows along with some possible applications of the processed materials: Valorisation of agro-forest residues The scraped biomass pulp obtained after the decortication process of banana leaves constitutes a residue, rich in bioactives and pigments, that can be valorised. After properly dried (i) at an adequate temperature to remove moisture but without thermal degradation, the material was milled (ii), for uniformity and to improve the yield of the subsequent chemical process. The dried milled biomass was then subjected to an ultrasound assisted extraction (iii) to obtain a polyphenol rich extract. After filtration of the remaining biomass, this extract can be applied directly, or evaporated and lyophilized to obtain a concentrated dried extract. These extracts, both liquid and dried, can be used as additives to obtain antioxidant bicolouring properties. The recovered filtered biomass was valorised further (iv). After dried, it was milled again and sieved to a finer granulometry, compatible with incorporation in coating formulations. Valorisation of marine residues In the field of blue bioeconomy, an invasive macroalgae from the Portuguese sea was studied for possible valorisation in several industries (from a direct application perspective). After the harvest step to mitigate its proliferation, a properly drying process was performed (i), and the marine biomass was grinded (ii). The macroalgae was then characterized using physical-chemical techniques and the presence of micronutrients (magnesium, calcium and sodium) was confirmed – important for application in the food sector; the antioxidant property – for cosmetic industry – was observed, as well as the fluorescent property – interesting for the traceability area; in addition to the potential for the development of bioplastic materials. Valorisation of ore residues Aluminosilicates generated as waste from the extraction process from minerals can be chemically processed, aiming at the dissociation of these compounds to obtain and valorise silica. What remains after the mechanical processing (ii) of ore and its mineral extraction (iii), can be further processed (iv) by a chemical process that consists of leaching, using temperature and under agitation. The reaction medium is filtered, and the solution is subjected to a pH correction to precipitate silica. Finally, the solid is washed and dried. This silica can be then functionalized, acquiring added value properties or even incorporated as an additive or filler directly into formulations.

Theoretical implications: The theoretical goal of this valorisation strategy is to demonstrate that residues can be valuable resources for value-added and functional materials with numerous, diverse and appealing applications, facilitated by adequate processing. By the combination of mechanical and chemical processing techniques, tailored to the type of resource material and its composition, it is possible to maximize the valorisation potential of industrial wastes and by products, while unlocking the possibility of new, sustainable and circular products for the industry, with both functional and decorative properties provided by the incorporation of processed residues. This ultimately contributes to accelerate the uptake of the circular bioeconomy model and to strengthen cooperation with the industry.

Practical implications: From the practical point of view, powdered wastes have the potential to be used as coloured pigments for decorative and functional coatings, or reinforcing agents for composites. Biomass extracts rich in bioactives can be used as functional and colourants additives. Biopolymers extracted from biomass can be applied to a new generation of packaging and fibres. Even food waste can be repurposed into vegan leathers and substrates. Applications are countless. In the broader context, by motivating waste valorization and circularity of resources, this approach will consequently contribute to a decrease in landfilled waste and greenhouse gas emissions, reduced dependency on fossil-based resources and improved environmental sustainability of products and industries.

Limitations: For valorisation processes to be economically viable and appealing for industrial application, certain limitations regarding the residues and by products still need to be overcome, such as consistency (batch-to-batch variation) and availability (industrial scale supply and seasonality). Also, compatibility of resources and valorisation processes with conventional applications and processes needs to be improved. Last but not least, the current additional cost of these new products, when compared to fossil-based everyday solutions, is still a barrier to the adoption of valorization strategies.

Innovation: The main innovation of this work and the establishment of this waste valorisation line is the integrated approach to the valorisation process with the goal to maximize every aspect that can bring value to otherwise untapped resources. A waste valorisation line that considers the conservation, mechanical and (bio)chemical processes is innovative because it maximizes resource recovery and enhances sustainability, promoting zero-waste. This hybrid valorisation line can handle a wider range of waste types, from plastics and textiles to food and agricultural residues. It enables a flexible response to different waste compositions, making it suitable for various industrial applications. More waste streams are transformed into marketable secondary raw materials, enhancing economic and environmental sustainability. This multistage valorisation strategy is an advancement in waste management, transforming waste from a burden into a high-value resource. It aligns with the principles of the circular economy, making industries more sustainable and reducing dependency on virgin raw materials.

References: [1] European Commission. (2020). A new Circular Economy Action Plan: For a cleaner and more competitive Europe. Publications Office of the European Union. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52020DC0098

ABSTRACT. Objective of the Article The BioEquip project is a key initiative within the Mobilizing Agenda for Business Innovation, Produtech R3, aimed at developing innovative industrial and more sustainable solutions the manufacturing of biomaterials and biocomposites. This project seeks to create a sustainable and efficient value chain that integrates novel composition methods and advanced production technologies. By establishing new industrial production units, termed "factories of the future", BioEquip will enable the large-scale, environmentally conscious production of biocomposites. This work provides a comprehensive review of the project's objectives, methodologies, technological advancements, and its potential impact on industrial innovation and sustainability.

Methodology The BioEquip project is part of the Mobilizing Agenda for Business Innovation, called Produtech R3, focusing on the development of industrial solutions. It aims at manufacturing raw materials from biomass covering the entire value chain for the development and implementation of new industrial production units, that is, the factories of the future for the production of biomaterials. The BioEquip project is structured around three technological PPS (Product, Process, or Service) developments: 1. Development of an Optimized Composition Pilot Line: o A novel pilot line will be designed to incorporate cellulose nanocrystals and curcumin as reinforcement and active agent into polymeric matrices. This technique, combined with catalytic processes, enhances efficiency and reduces processing time. o Implementation of methodologies and quality control systems will be implemented to ensure production consistency. o The composition line will be developed for the fabrication of biocomposites, incorporating advanced online and inline sensing and control systems. 2. Development of Modular Tools and Sensors for Laboratory Extruders: o The project will design and integrate modular tools and sensors that can be integrated and adjusted in laboratory extruders, applicable to both industrial and academic research and development (R&D) settings. o These systems will facilitate real-time monitoring of the characteristics of the material to be processed; online and inline approaches are considered, to evaluate the dispersion of charges using optical spectroscopy and rheometry. 3. Ozone Generation and Dispersion Equipment: o The third PPS aims to develop the conceptualization, manufacture and integration of new ozone generation and dispersion equipment for the production of ozonized oils for the health and cosmetics industries; o The resulting products include low-cost ozonized oils for medical and cosmetic applications; vegetable oils in commercial formulations, in accordance with the REACH regulation. The methodology adopted by the BioEquip project ensures a holistic approach to sustainability, efficiency, and scalability, integrating energy-efficient processes, treatment of materials and waste minimization strategies throughout production.

Results The project achieved key advancements in biocomposite production and sustainability assessment. In the first PPS, Pellets of different PLA+Curcumin compositions were produced and their properties are being characterized to choose the best formulation. In the second PPS, the focus was on process monitoring and lifecycle assessment, leading to the fabrication of a characterization module, integration of real-time sensing tools, and the definition of an LCA baseline. In the third PPS, an ozone-based bioactive production was advanced, with detailed engineering for ozonized oil processes, validation of ozone application protocols, and sustainability assessment through clinical, chemical, and regulatory analysis. These developments lay the groundwork for scalable, high-efficiency bioprocesses in sustainable materials.

Theoretical Implications The BioEquip project contributes to the theoretical understanding of bioactive extraction and sustainable biocomposite manufacturing. The integration of ultrasonication and catalytic methods in bioactive extraction presents new avenues for improving efficiency and reducing chemical dependency. Furthermore, the development of real-time monitoring tools enhances the theoretical framework for process optimization in biopolymer production. The project also expands knowledge on ozone applications in industrial processing, demonstrating its potential in stabilizing bioactive compounds and extending their functionality. By advancing these theoretical insights, BioEquip lays the foundation for future research in green manufacturing and industrial biotechnology.

Practical Implications The practical applications of the BioEquip project extend across multiple industries, including packaging, automotive, electronics, and healthcare. The production of high-quality biocomposites opens new possibilities for sustainable packaging solutions. In the automotive sector, lightweight and durable biocomposites offer an alternative to conventional materials, reducing the industry's carbon footprint. The integration of ozone-treated bioactives in health and cosmetics products enhances their stability and effectiveness, expanding market opportunities for naturally derived ingredients. Furthermore, the development of modular tools for laboratory extruders facilitates more precise and scalable material processing, benefiting both industrial and academic research. The project’s focus on sustainability ensures that these advancements contribute to environmentally responsible manufacturing practices.

Limitations Despite its promising advancements, the BioEquip project faces several challenges: • Scalability Issues: While the pilot-scale developments show significant potential, scaling up these technologies for full industrial implementation may require additional optimization and investment. • Regulatory Compliance: The production of bioactives and biocomposites must align with stringent regulatory standards, such as REACH, which can pose hurdles in commercialization. • Material Variability: Variability in biomass feedstocks may impact process efficiency and product consistency, requiring adaptive strategies to standardize raw material inputs. • High Initial Costs: The adoption of advanced sensing technologies and new production methodologies involves high initial capital costs, which may limit accessibility for smaller enterprises. • Integration Challenges: The implementation of real-time monitoring systems requires seamless integration with existing industrial infrastructure, which may present technical difficulties.

Innovation The BioEquip project introduces several key innovations that contribute to the advancement of sustainable industrial processing: • Advanced Monitoring Systems: The development of modular, real-time monitoring tools represents a significant step forward in process control for biocomposite manufacturing. • Ozone-Based Processing: The application of ozone treatment in bioactive stabilization offers a novel approach to enhancing product quality while maintaining environmental sustainability. • Sustainable Biocomposites: The production of biocomposites provides a viable alternative to traditional petroleum-based materials, contributing to the circular economy. • Factory of the Future Concept: By integrating cutting-edge extraction and production technologies, the project paves the way for the next generation of sustainable industrial facilities.

Conclusion The BioEquip project represents a significant step toward developing sustainable, high-performance industrial solutions for biocomposite production. Through its focus on energy-efficient processes, advanced monitoring systems, and novel extraction techniques, BioEquip is poised to revolutionize the bioeconomy sector. While challenges remain in terms of scalability, regulatory compliance, and cost, the project’s commitment to sustainability and innovation ensures its long-term viability. As the project progresses toward completion in December 2025, its outcomes will provide valuable insights for industries seeking to transition towards greener, more efficient manufacturing practices. BioEquip stands as a model for integrating cutting-edge technology with sustainability, setting the stage for the factories of the future.

Keywords Biocomposites; Real-Time Sensing; Ozone Applications

ABSTRACT. This development explores the potential of digital marketplaces to drive circular economy practices by fostering value creation through efficient interactions between businesses. Unlike traditional value chains, digital platforms harness network effects to minimize transaction costs and enhance resource organization. This study introduces a novel digital platform, "Eco Opportunities," designed to actively promote circular business models via three distinct modules: “Solutions,” “Materials/Products,” and “Surplus Materials.” These modules enable companies to address technical challenges, increase material and product circularity, and find alternatives for surplus materials. The digital platform supports decision-making through features based on criteria such as distance, quantity, price, and upcycling level. The upcycling level is defined through a weighted scoring system and visualized using a color scheme, simplifying the selection of high-value solutions.

ABSTRACT. Blending of renewable hydrogen (H2) with natural gas (NG) is a short-term opportunity to the pathway of the decarbonization of industrial processes of energy-intensive industries (EII), specially, those highly dependent of gaseous fossil fuels such as natural gas, and where electrification is more difficult. This paper presents a methodology developed under WP14 Tech4Decarb of PRODUTECH R3 Mobilizing Agenda to repurpose industrial gas distribution networks to hydrogen blend service, namely through the characterization of an existing gas infrastructure, integrity assessment and inspection of the reconverted infrastructure. Additionally, critical aspects for the reconversion of existing gas networks are also discussed, such as regulatory framework and compatibility of pipping and other component materials to hydrogen exposure. The viability assessment of an existing gas grid at a selected manufacturing plant is presented as case study for the conversion to hydrogen blends of 20% H2/80%NG (v/v), to be used in a drying oven with a 35 kW gas burner. The developed methodology intends to be scalable and applicable across various industrial sectors and it serves as an important guide for the implementation and conversion of existing gas grid to hydrogen service, contributing to reduced carbon emissions in production processes.

ABSTRACT. Urban waste generation has increased exponentially in recent decades, driven by population growth, migration, and uncontrolled urban expansion. This phenomenon presents significant regional disparities in waste treatment: while Europe has advanced in recycling and valorization strategies, regions such as Asia or Latin America face challenges due to high population density and intensive resource consumption. In countries like Portugal, waste generation continues to rise annually, surpassing the response capacity of conventional treatment methods, which include open-air dumping, sanitary landfilling, and incineration. Given this critical scenario and the associated environmental impacts, including air pollution, soil degradation, and contamination of water sources, urban biorefineries have emerged as integrated technological systems that promote the circular economy by transforming residual urban waste streams into high-value-added products for the energy, manufacturing, construction, and environmental remediation sectors. This paper presents an integrated review of technologies applied in recent urban biorefinery models, analyzing technological pathways, commercial products, case studies, and regulatory and economic barriers. The methodology is based on a structured review of scientific literature and technical reports, focusing on the technological classification and application of these systems in various urban contexts. Results show significant environmental and economic benefits; however, challenges remain, such as high capital expenditure (CAPEX), operational costs (OPEX), systemic complexity, and the lack of robust regulatory frameworks. Of particular concern is the absence of effective Extended Producer Responsibility (EPR) mechanisms to ensure the successful integration of these solutions. From a theoretical perspective, this study reinforces the need to transition toward regenerative waste management models. In practical terms, it provides key insights for designing scalable solutions that optimize material recovery and energy efficiency in urban environments. As an innovative contribution, the review proposes an integrated classification of conversion technologies and design recommendations for future urban biorefinery systems.

ABSTRACT. Innovation is the process of developing or enhancing ideas, products, or methods that create value across industries and society. As a key driver of long-term economic growth [1], innovation has become an area of increasing focus for both academic research and industrial advancement [2], [3]. Schroeder et al. [4] provide a shared academic-industrial perspective on defining, measuring, and improving innovation in manufacturing. Their study highlights how innovation influences manufacturing performance and how various external factors, such as resource availability, organizational structure, and cultural dynamics affect innovation potential. In term, innovation itself is influenced by aspects such as team leadership vision and team creativity [5]. In the context of small and medium-sized enterprises (SMEs), innovation efforts are often hindered by constraints such as limited human capital, government support, external economic pressures, and dependency on collaborative businesses [5], [6], [7]. Additive manufacturing (AM) technologies, particularly those with low investment requirements, present a promising innovation pathway for SMEs, given their typically limited resources for innovation-related investments. Building on recent literature and a case study from a Portuguese SME, this work assesses how AM can serve as an accelerator of innovation within resource-constrained environments. It explores AM’s impact on product development, supply chain configuration, and business model transformation, while also identifying limitations and contextual factors that influence its effectiveness. The objective is to demonstrate that AM not only enhances existing processes but also enables new approaches to how products are designed, manufactured, and delivered.

ABSTRACT. Driven by the increasing demand for cabin comfort and the unique acoustic landscape of electric vehicles (EVs), the Heating, Ventilation, and Air Conditioning (HVAC) system has emerged as a critical noise source. This paper starts with a short presentation of numerical simulation techniques for predicting noise generation in automotive air vents, followed by some fundamental aeroacoustic mechanisms, advanced simulation methodologies including Computational Fluid Dynamics (CFD), Computational Aeroacoustics (CAA), Lattice Boltzmann Method (LBM), Finite Element Method (FEM), and Boundary Element Method (BEM) and then a practical application of noise prediction in automotive air vents is presented.