Search Results (403)

With the successful deployment of several mRNA vaccines against SARS-CoV-2, an mRNA vaccine against RSV (respiratory syncytial virus) and a large pipeline of mRNA products against other infectious diseases, cancers and rare diseases, it is important to examine the whole product lifecycle. mRNA technology enables product design, testing and manufacturing systems to be rapidly developed, but these advantages can be lost if other factors that determine public access are not closely considered. This review analyzes key aspects of the mRNA product lifecycle including candidate design, manufacturing, quality systems and product safety and storage. Regulatory thinking is well advanced in some countries but not others, but more thought on the regulation of mRNA vaccines outside of a pandemic situation as well as mRNA therapeutics including individual neoantigen therapies and rare disease treatments is needed. Consumer acceptance—the “social license to operate” around mRNA products—is critical for their uptake, particularly outside of a pandemic. Full article

Mecanum and omni wheel-based assistive technologies present an alternative to conventional mobility devices for individuals with motor impairments, owing to their omnidirectional movement capabilities and high maneuverability in constrained environments. This systematic review identifies and categorizes the key challenges and emerging trends in the development of such systems. Primary obstacles include limited stability and maneuverability on uneven terrain, high energy consumption, complex control requirements, and elevated production costs. In response, recent studies have introduced several innovative approaches, such as advanced suspension systems to enhance terrain adaptability, modular mechanical designs to reduce manufacturing complexity, energy-efficient motor control strategies such as field-oriented control, AI-driven autonomous navigation, and hands-free user interfaces—including gesture recognition and brain–computer interfaces. By synthesizing findings from 26 peer-reviewed studies, this review outlines current technical limitations, surveys state-of-the-art solutions, and offers strategic recommendations to inform future research in intelligent assistive mobility technologies. Full article

Laser powder bed fusion has been demonstrated as a promising additive manufacturing technology due to its unique advantages, such as weight reduction, the ability to produce arbitrarily complex geometries and single-step manufacturing. However, the production quality may deteriorate due to the poor surface quality of deposited layers caused by the occurrence of the balling phenomenon, which hampers its widespread application. In this work, a data-driven framework is proposed to optimize the process parameters of laser powder bed fusion to achieve satisfactory balling levels. The effects of key process parameters on balling levels are also investigated. Specifically, an image segmentation-based method is introduced to quantitatively evaluate the balling levels on the interlayer surfaces of as-built specimens under various process parameter combinations. Considering the limited amount of experimental data, different machine learning models, including polynomial regression, support vector regression, and backpropagation neural networks, are developed to predict the balling levels within a predefined process parameter space. The predicted values from the best-performing model are then used as fitness values of individuals in an improved genetic algorithm to search for globally optimal process parameters. The final validation experiments confirm that the as-built parts fabricated using the optimized process parameters exhibit minimal balling levels, demonstrating the effectiveness and feasibility of the proposed framework for balling level prediction and optimization. This study provides valuable insights and practical guidance for enhancing the quality of specimens produced in the laser powder bed fusion process. Full article

Upper limb prostheses face acceptance challenges due to factors such as discomfort, limited functionality, high weight, and elevated costs. Despite the availability of advanced models with sophisticated technologies, their accessibility remains limited to individuals with greater financial means. This study presents the development of a parametric hand prosthesis designed for total or partial amputations, utilizing additive manufacturing and affordable hypoallergenic materials. The parametrization was based on customized anthropometric geometries, modeled using CAD software, with structural validation conducted through finite element analysis under static forces. The printing material was characterized according to ASTM D638 standards. The results indicate that the prosthesis provides a personalized, functional, and accessible solution that meets the specific needs of users. It is concluded that the use of additive manufacturing and parametric design not only reduces costs and improves accessibility but also enables the creation of devices tailored to individual user characteristics, promoting greater functionality and quality of life. Full article

Shitsukan, which encompasses the perception of roughness, glossiness, and transparency/translucency, represents the comprehensive visual appearance of objects and plays a crucial role in accurate reproduction across various fields, including manufacturing and imaging technologies. This study experimentally examines the impact of the pixel–aperture ratio on the perception of roughness, glossiness, and transparency. A visual evaluation experiment was conducted using natural images presented on stimuli with pixel–aperture ratios of 100% and 6%, employing an RGB sub-pixel array. The results demonstrated that the pixel–aperture ratio significantly affects the perception of glossiness and transparency, with the 100% pixel–aperture ratio producing a statistically significant effect compared to the 6% condition. However, roughness perception varied substantially among the observers, and no statistically significant effect was observed. Nonetheless, when comparing two observer clusters identified through clustering analysis, the cluster favoring the 100% pixel–aperture ratio exhibited “Huge” effect sizes for all perceptual attributes. Additionally, the findings indicate that the degree of influence of pixel–aperture ratio on glossiness and transparency is not constant and can vary depending on individual observer differences and image characteristics. Full article

Background: Reliable biomarkers are urgently needed to aid in the differential diagnosis, prognosis, disease progression monitoring, and prediction of therapeutic response in patients with systemic sclerosis (SSc). This study aimed to evaluate a panel of potentially pathogenic circulating cytokines and chemokines in a cohort of SSc patients. Methods: Serum samples were obtained from 35 SSc patients and 40 age- and sex-matched healthy controls. Twenty-three cytokines/chemokines were quantified using a Luminex^® multiplex immunoassay (BioRad-BioPlex 200 System-Lumine x-Map technology R&D Systems, USA) following the manufacturer’s instructions and customized procedures. Data were acquired using Bioplex manager v 6.1. Data analysis was performed using GraphPad Prism v.8 (GraphPad Software, Inc.), with significance defined as p ≤ 0.05. V.8 Results: Levels of TNFRII and MMP-8 were significantly higher in SSc patients compared to healthy controls, while IL-1RII levels were significantly elevated in healthy individuals (p < 0.001 for all comparisons). Patients with elevated ESR at baseline (>30 mm/h) showed higher IL-15 levels (p = 0.019). A strong positive correlation was found between MCP-1 and the modified Rodnan skin score (mRSS) (p = 0.009, r = 0.740), and a moderate correlation between TNFRII and diffusing capacity for carbon monoxide (p = 0.046, r = 0.339). PLS regression identified MMP-8, MCP-1, TNFRII, IL-15, and IL-1RII as key predictors of SSc, with MMP-8 having the strongest influence. The logistic regression model showed high performance (AUC = 0.93, accuracy = 87.5%). Conclusions: TNFRII, MMP-8, and IL-1RII may play a pathogenic role in SSc. TNFRII, in particular, may serve as a biomarker for pulmonary involvement, aligning with its known role in pro-fibrotic pathways. These findings support their utility in diagnosis and disease profiling. Full article

Solid-state batteries (SSBs) present a promising advancement in energy storage technology, with the potential to achieve higher energy densities and enhanced safety compared to conventional lithium-ion batteries. However, their commercialisation is hindered by technical limitations and fragmented research efforts that predominantly focus on materials or individual performance parameters. This narrow scope limits SSB design and optimisation, potentially delaying the transition to commercial cells. Addressing these challenges requires a systematic framework that integrates key design and performance considerations. This study introduces a modelling framework that addresses these challenges by offering a systematic approach to SSB design. The model streamlines the design process by enabling users to define material selections and cell configurations while calculating key performance indicators (KPIs), such as energy density, power density, and resistance, as well as the specifications required for cell manufacturing. A material compatibility validation feature ensures appropriate selection of anode, cathode, and electrolyte materials, while an integrated sensitivity analysis (SA) function identifies critical design parameters for performance optimisation. The model’s accuracy and applicability were validated through comparisons with experimental data, established design frameworks, and the reverse-engineering of commercial SSB prototypes. Results show that the model predicts energy densities within a ±4% deviation in most cases. Additionally, the application of SA highlights its effectiveness in refining design parameters and optimising cell configurations. Despite certain limitations, the model remains a valuable tool in the early stages of battery concept development. It offers researchers and industry professionals a practical means to assess the feasibility of SSB designs and support future scale-up and industrialisation efforts. Full article

This study analyzes the impact of digital transformation on the international economic integration of ASEAN-6 countries during the period of 2000–2023 using the Generalized Least Squares (GLS) estimation method. The findings indicate that factors such as fixed broadband subscriptions (FixB), fixed telephone subscriptions (FixT), and the value added from medium- and high-tech manufacturing (MHT) have a positive and statistically significant effect on trade openness (TO). Conversely, mobile cellular subscriptions (MB) and the percentage of individuals using the Internet (IU) exhibit a negative impact on economic integration, reflecting the uneven development of digital infrastructure across countries. Based on these results, the study suggests policy implications, including substantial investment in digital infrastructure, technological advancement in production, and improved accessibility to digital services to foster more effective economic integration. ASEAN-6 countries should adopt tailored development strategies that emphasize innovation and the development of a skilled digital workforce to enhance their competitiveness both regionally and globally. Full article

The integration of Industry 4.0 technologies, Circular Economy (CE) principles, and Green Human Resource Management (GHRM) offers transformative potential to address global sustainability challenges. Industry 4.0, characterized by advanced digital technologies like IoT, Additive Manufacturing (AM), and Big Data Analytics (BDAA), enhances operational efficiency, resource optimization, and waste minimization. Concurrently, CE redefines economic models through resource conservation, lifecycle extension, and reduced environmental impact, supported by frameworks like ReSOLVE. GHRM aligns human resource practices with sustainability objectives, fostering Green behaviors and embedding environmental considerations into organizational culture. Despite the individual benefits of these frameworks, their combined application remains underexplored, with limited research on their systemic integration. This study addresses this gap by examining the synergies between Industry 4.0 technologies, CE principles, and GHRM strategies, identifying opportunities and challenges in their implementation. A theoretical model is proposed, emphasizing systemic innovation, resource efficiency, and collaborative value chains as key enablers of sustainable development. The model highlights the necessity of aligning technological advancements with human-centric approaches to overcome behavioral, organizational, and infrastructural barriers in transitioning toward sustainability. The findings offer practical insights for policymakers and industry leaders, outlining strategies for integrating Industry 4.0 with CE and GHRM to drive sustainability transitions. By synthesizing technological, environmental, and human resource dimensions, this research contributes both theoretically and practically, positioning organizations to enhance sustainability while maintaining competitiveness in evolving economic landscapes. Full article

This pioneering study examines metallographic characteristics of 19th-century steel semi-finished products, kept by the National Museum of Slovenia. These artefacts, manufactured in pre-industrial ironworks in present-day Slovenia, reflect the craftsmanship and technological practices of their time. Metallographic analyses revealed significant microstructural variations within individual samples, attributed to differences in carbon content, cooling rates, and forging techniques. All samples contain non-metallic inclusions composed of Si, Mn, and other oxide-forming elements. The results indicate that the semi-finished products were often manufactured by combining steels with varying carbon contents and were sometimes hardened. Additionally, this study highlights correlations between the metallurgical properties of the analysed materials and their historical classification as “iron” or “steel”. Full article

This study explores factors promoting and inhibiting advanced technology adoption in small- and medium-sized manufacturing firms (SMEs). With AI’s rapid advancement impacting productivity and efficiency across industries, understanding the challenges that SMEs face to remain competitive is crucial. Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) model as a theoretical framework, we analyzed managers, engineers, and line workers’ observations on workforce challenges, training needs, and opportunities faced by SMEs to provide insights into their smart manufacturing deployment experiences. Our findings highlight social influence’s role in promoting technology adoption, emphasizing community, shared experiences, and collaborative networks. Conversely, effort expectancy emerged as the largest inhibitor, with concerns about the complexity, time, and resources required for implementation. Individuals were also influenced by factors of facilitating conditions (organizational buy-in, infrastructure, etc.) and performance expectancy on their propensity to adopt advanced technology. By fostering positive organizational environments and communities that share success stories and challenges, we suggest this can mitigate the perceived effort expected to implement new technology. In turn, SMEs can better leverage AI and other advanced technologies to maintain global competitiveness. The research contributes to understanding technology adoption dynamics in manufacturing, providing a foundation for future workforce development and policy initiatives. Full article

Three-dimensional printing technology is transforming pharmaceutical manufacturing by shifting from conventional mass production to additive manufacturing, with a strong emphasis on personalized medicine. The integration of bioinks and AI-driven optimization is further enhancing this innovation, enabling drug production with precise dosages, tailored drug-release profiles, and unique multi-drug combinations that respond to individual patient needs. This advancement is significantly impacting healthcare by accelerating drug development, encouraging innovative pharmaceutical designs, and enhancing treatment efficacy. Traditional pharmaceutical manufacturing follows a one-size-fits-all approach, which often fails to meet the specific requirements of patients with unique medical conditions. In contrast, 3D printing, coupled with bioink formulations, allows for on-demand drug production, reducing dependency on large-scale manufacturing and storage. AI-powered design and process optimization further refine dosage forms, printability, and drug release mechanisms, ensuring precision and efficiency in drug manufacturing. These advancements have the potential to lower overall healthcare costs while improving patient adherence to medication regimens. This review explores the potential, challenges, and environmental benefits of 3D pharmaceutical printing, positioning it as a key driver of next-generation personalized medicine. Full article

The advent of 3D printing technology has revolutionized various manufacturing sectors, including the medical field, particularly in the production of prosthetic limbs. Traditional prosthetic manufacturing processes are often time-consuming and expensive, causing amputees to endure long waiting periods and high costs. In contrast, 3D printing offers a rapid, cost-effective alternative, enabling the creation of custom-made prosthetics tailored to the specific needs and measurements of each wearer. Integrating 3D printing technology into prosthetics and orthopedics has ushered in a new era of customization and innovation. This advanced approach facilitates the creation of personalized prosthetics and bone replacements tailored to individual patients’ needs. With the latest advancements in software and 3D printing, the use of custom orthopedic implants for complex surgical cases has gained significant popularity. This paper explores the advantages of using 3D printing for prosthetic limb production, highlighting its ability to significantly reduce the production time and costs while maintaining high functionality and quality. By leveraging 3D scanning and computer-aided design (CAD), precise digital models of a patient’s residual limb can be created, ensuring a perfect fit and improved comfort. Additionally, the flexibility of 3D printing allows for the incorporation of advanced materials and design features, enhancing the durability and performance of the prosthetics. The study also examines the potential for 3D printing to democratize access to prosthetic care, especially in low-resource settings. The affordability and accessibility of 3D printers, coupled with open-source designs, empower local communities and healthcare providers to produce prosthetics on demand, reducing dependency on centralized manufacturing facilities. By addressing the current limitations and challenges, including material constraints and regulatory hurdles, this paper highlights the transformative impact of 3D printing on the prosthetics industry. Full article

The concept of Industry 4.0 envisions the flexibilization of production and high levels of automation of existing manufacturing processes. As an extension of this concept, Industry 5.0 assumes the adaptation of products to the individual needs of users, with a particular emphasis on creativity, personalization, sustainability, and an ethical approach to business. Within these concepts, the development of metal forming technology is also recognized. In addition to the usual mass production, the development of various roboforming ideas is steering this branch of industry towards greater flexibilization, as well as personalization of production. This supports the idea of sustainability, enables more precise determination of the quantity of required material and energy resources, and emphasizes quality over quantity. This paper provides an overview of metal forming technologies that belong to the domain of roboforming of sheet metals, from the basic idea in 1960s to the present day. These technologies have seen a marked tendency to accelerate in development over the past few years. The technologies are classified, and an overview of scientific papers proposing their development and application is provided, with a discussion of the fundamental production parameters that influence product quality as well as the production trend towards Industry 5.0. Full article

This review draws on a systematic literature review and bibliometric analysis to examine how Digital Twins (DTs), Extended Reality (XR), and Artificial Intelligence (AI) support the reconfiguration of Cyber–Physical Systems (CPSs) in modern manufacturing. The review aims to provide an updated overview of these technologies’ roles in CPS reconfiguration, summarize best practices, and suggest future research directions. In a two-phase process, we first analyzed related work to assess the current state of assisted manufacturing reconfiguration and identify gaps in existing reviews. Based on these insights, an adapted PRISMA methodology was applied to screen 165 articles from the Scopus and Web of Science databases, focusing on those published between 2019 and 2025 addressing DT, XR, and AI integration in Reconfigurable Manufacturing Systems (RMSs). After applying the exclusion criteria, 38 articles were selected for final analysis. The findings highlight the individual and combined impact of DTs, XR, and AI on reconfiguration processes. DTs notably reduce reconfiguration time and improve system availability, AI enhances decision-making, and XR improves human–machine interactions. Despite these advancements, a research gap exists regarding the combined application of these technologies, indicating potential areas for future exploration. The reviewed studies recognized limitations, especially due to diverse study designs and methodologies that may introduce risks of bias, yet the review offers insight into the current DT, XR, and AI landscape in RMS and suggests areas for future research. Full article