Search Results (2,579)

Health systems face pressure to strengthen resilience against supply chain disruptions while maintaining cost-effective service delivery. This mixed-methods study describes a pilot project that integrated 3D printing services into a Canadian provincial health authority. Quantitative data were derived from internal clinical engineering work orders, where a scenario-based economic analysis compared original equipment manufacturer (OEM) procurement with modelled 3D-printed parts. Using conservative assumptions, selected non-electronic structural parts were assigned a fixed unit cost. Qualitative data were collected from two focus groups with clinical engineers and other end-users. Results from an exploratory scenario-based economic analysis suggest that substituting selected structurally simple clinical engineering parts with 3D-printed alternatives would be associated with modelled cost impacts ranging from a 67.4% net increase (OEM prices halved and 3D-printing costs doubled) to a 69.6% cost reduction (OEM prices increased by 10% and 3D-printing costs decreased by 20%). Demand changes affected absolute savings but not the percent difference (58.1% under ±50% quantity changes), and a pessimistic procurement scenario (OEM prices decreased by 30% and 3D-printing costs increased by 50%) reduced savings to 10.3%. Focus groups highlighted perceived benefits and implementation challenges associated with integrating additive manufacturing. Implementation was facilitated through an outsourcing model, which was perceived to shift certain responsibilities and risk-management functions to the vendor. Long-term adoption will require clearer communication and targeted education. This pilot study suggests that, under constrained regulatory scope and scenario-based assumptions, additive manufacturing may contribute to supply chain resilience and may be associated with modelled cost advantages for selected low-risk components. Full article

Background/Objectives: Enhancing excipient functionality through environmentally friendly and scalable processing methods is essential for improving the manufacturability and performance of orally disintegrating tablets (ODTs). Microwave-assisted wet granulation enables controlled microstructural modification without chemical alteration of excipient components. This study aimed to develop and evaluate a rice starch (RS)–mannitol co-processed excipient using microwave-assisted wet granulation for direct compression of ODTs. Methods: RS and mannitol were co-processed by wet granulation followed by microwave treatment under varying power levels and irradiation times. The effects of processing conditions on granule morphology, solid-state properties, porosity, powder flow, compressibility, wettability, and disintegration behavior were systematically investigated. The optimized excipient was further evaluated in ODT formulations containing chlorpheniramine maleate and piroxicam and benchmarked against a commercial co-processed excipient (Starlac^®). Results: Microwave treatment generated internal vapor pressure that promoted pore formation and particle agglomeration, resulting in enhanced powder flowability (compressibility index 8.4–10.8%). Partial crystallinity reduction and microstructural modification improved compressibility and surface wettability compared with non-microwave-treated materials. The optimized formulation (MW-RM-H-30) exhibited rapid wetting (25 s), high water absorption (90.5%), low contact angle (42°), and fast tablet disintegration (31 s). ODTs prepared with MW-RM-H-30 showed rapid disintegration (42 s for chlorpheniramine maleate and 32 s for piroxicam) and dissolution behavior comparable to Starlac^®. Conclusions: Microwave-assisted wet granulation provides an efficient, scalable, and environmentally friendly strategy for engineering starch-based co-processed excipients with enhanced functionality for direct compression ODT applications. The developed excipient demonstrates strong potential for solid dosage form manufacturing. Full article

Accurately determining actual energy consumption is essential for guiding technological developments in the transport sector, assessing vehicle development outcomes, and designing effective energy and climate policies. Although laboratory driving cycles such as the WLTP provide standardized benchmarks, they do not reflect the complex interactions between human behavior, environmental conditions, and vehicle dynamics under real-world operating conditions. This article presents an integrated framework for assessing long-term, actual energy carrier consumption in four main vehicle categories: internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), hydrogen fuel cell electric vehicles (H2EVs), and battery electric vehicles (BEVs). The entire discussion here is based on the results of data analysis from natural operation using the so-called vehicle energy footprint. This framework provides a method for determining the average energy carrier consumption for each group of vehicles with the specified drivetrains. This information formed the basis for assessing the total energy demand for the operation of the analyzed vehicle types in normal operation. The simulations show that among mid-range passenger vehicles, ICEVs are the most energy-intensive in normal operation, followed by H2EVs and HEVs, and BEVs are the least. This study highlights the methodological challenges and implications of accurately quantifying energy consumption. The presented method for assessing energy demand in vehicle operation can be useful for manufacturers, consumers, fleet operators, and policymakers, particularly in terms of energy efficiency, emission reduction, and public health protection. Full article

Food waste remains a significant challenge in the European Union, reflecting structural differences across economic sectors and member states. This study examines how macroeconomic conditions relate to sectoral food waste using harmonized Eurostat data for the EU-27, covering five stages of the food chain and three economic indicators: GDP (Gross Domestic Product) per capita, adjusted gross disposable income per capita, and the Harmonized Index of Consumer Prices for food. The research design integrates factor analysis, structural equation modeling, and hierarchical clustering. Results show that income-related variables have a positive, statistically significant effect on overall food waste, particularly in manufacturing and distribution. In contrast, food prices show a negative, statistically non-significant relationship with waste generation. Cluster analysis identifies two statistically distinct country groups; however, substantial internal heterogeneity indicates that these clusters reflect structural economic configurations rather than typological or behavioral categories. The findings suggest that macroeconomic factors partially explain cross-country differences in food waste and support the need for context-sensitive, sector-specific policy interventions. Full article

Existing research on the linear rolling guide has predominantly focused on performance under ideal conditions or isolated error types, while systematic studies concerning multi-error coupling mechanisms and their impact on internal contact parameters remain limited. To address this, a comprehensive static model based on Hertz contact theory is proposed that simultaneously incorporates ball diameter, raceway radius, and raceway curvature center distance errors. This model is validated using finite element analysis (FEA) in ABAQUS, and the numerical results verify the feasibility and effectiveness of the proposed analytical model. Analysis of single, combined, and random errors indicates that geometric errors significantly influence vertical stiffness, load distribution, and critical load-carrying capacity. For example, as the ball diameter error varies from −2.5 to 2.5 μm, the vertical stiffness increases by a factor of 3.8, while a representative negative error combination reduces the critical load by nearly 40%. Additionally, random error analysis reveals that larger manufacturing tolerance ranges lead to increased fluctuation in ball contact forces, raising performance uncertainty. These findings establish the proposed model as a theoretical foundation for the precision design and load-bearing assessment of linear rolling guides under static conditions. Full article

Despite substantial growth in eco-innovation (EI) research, most studies rely on cross-sectional data, limiting understanding of the temporal dynamics of EI and its determinants under varying macroeconomic conditions. This study addresses this gap by analysing panel data from Spanish manufacturing firms across three phases of the business cycle: pre-crisis expansion (2004–2007), the global financial crisis (2008–2013), and recovery (2014–2016). We investigate the drivers of two distinct types of eco-innovation: efficiency EI (energy and material savings) and environmental EI (reducing environmental harm), focusing on the role of regulation, institutional interventions, and firm-level innovation capacities. Using a random-effects panel probit model that accounts for unobserved firm heterogeneity, we examine how these drivers operate across different macroeconomic contexts. Our findings reveal that regulation consistently fosters EI, while the influence of subsidies, R&D capacity, and collaborative networks is more context-dependent, particularly during economic downturns. The results highlight the cumulative, path-dependent, and cyclical nature of EI, providing novel insights into the conditions that enable firms to sustain green innovation over time. Drivers of eco-innovation differ systematically between efficiency- and environment-oriented strategies, and these differences remain stable over the business cycle, implying distinct underlying mechanisms and policy implications. Accordingly, policy design—particularly during economic downturns—should distinguish between reinforcing incentives for internal efficiency improvements and sustaining regulatory and financial support for environmental EI. Full article

Despite European and international regulatory frameworks promoting circular economy principles, sustainability in the furniture sector is still challenged by the limited access to reliable information about circular materials for designers, manufacturers, and waste managers in the Made-in-Italy furniture ecosystem. This research develops a digital infrastructure to address these information gaps through mixed methodology, combining desk research on regulatory frameworks and existing platforms; field research involving stakeholder mapping and interviews with designers, manufacturers, and waste managers; and the experimental development of AI-enhanced digital tools. The result integrates a web-based platform for circular materials with a CAD plugin supporting real-time sustainability assessment. As AI-assisted data entry showed a reduced form completion time while maintaining accuracy through human verification, testing also revealed how the system effectively bridges knowledge gaps between stakeholders operating in currently siloed value chains. The platform is a critical step in enabling designers to incorporate circular materials during the early design stages, while providing manufacturers access to verified punctual sustainability data compliant with mandatory Green Public Procurement criteria. Beyond the development of an innovative digital tool, the study outlines a corresponding operational model as a practical framework for strengthening the transition toward a circular economy in the Italian furniture industry. Full article

Despite the immense potential of digital intelligence technologies to enhance corporate profitability, manufacturing enterprises often face the “digital–green paradox”, which indicates that while companies invest in digital and intelligent transformation, their energy consumption increases rather than promoting green transition. To provide reasonable transformation solutions for manufacturers still caught in this paradox, this paper adopts a single-case study approach from a product lifecycle perspective. Focusing on FAW-Volkswagen—a manufacturing enterprise demonstrating outstanding performance in digital-intelligent green transformation—this study conducts an in-depth investigation into the stage characteristics and underlying mechanisms. The results show that the following: (1) The digital-intelligent green transformation of manufacturing enterprises is an iterative process evolving from “green design, low-carbon production, intelligent service to enterprise spiral value-added”, with distinct digital-intelligent empowerment models at each stage. (2) By leveraging digital-intelligent technologies, manufacturing enterprises can build a multi-tiered “internal-external dual circulation” green development system encompassing the “enterprise—industrial chain—full ecosystem,” driving comprehensive green upgrades across the entire industry and ecosystem. This paper reveals the intrinsic mechanisms through which digital-intelligent technologies facilitate manufacturing enterprises’ green transformation. It expands and enriches the research context and theoretical implications of product lifecycle management, offering management insights and strategic references for other enterprises pursuing green transformation and upgrading pathways in the digital-intelligent economy era. Full article

Industrial pumps are critical components in manufacturing and process plants, where early acoustic anomaly detection is essential for preventing unplanned downtime and reducing maintenance costs. In practice, however, strong background noise, severe class imbalance between rare faults and abundant normal data, and the limited computing resources of edge devices make reliable deployment challenging. In this work, a lightweight Audio Spectrogram Transformer (Tiny-AST) is proposed for robust pump anomaly detection under imbalanced supervision. Building on the Audio Spectrogram Transformer, the internal Transformer encoder is redesigned by jointly reducing the embedding dimension, depth, and number of attention heads, and combined with a class frequency-based balanced sampling strategy and time–frequency masking augmentation. Experiments on the pump subset of the MIMII dataset across three SNR levels (−6 dB, 0 dB, 6 dB) demonstrate that Tiny-AST achieves an effective trade-off between computational efficiency and noise robustness. With 1.01 M parameters and 1.68 GFLOPs, it maintains superior performance under heavy noise (−6 dB) compared to ultra-lightweight CNNs (MobileNetV3) and offers significantly lower computational cost than standard compact baselines (ResNet18, EfficientNet-B0). Furthermore, comparisons highlight the performance gains of this lightweight supervised approach over traditional unsupervised benchmarks (e.g., autoencoders, GANs) by effectively leveraging scarce fault samples. These results indicate that a carefully designed lightweight Transformer, together with appropriate sampling and augmentation, can provide competitive acoustic anomaly detection performance while remaining suitable for deployment on resource-constrained industrial edge devices. Full article

Against the backdrop of accelerating servitization transformation in the global manufacturing sector, how digital platform capability effectively drives improvements in innovation performance has become a critical issue. Existing research mainly focuses on the instrumental attributes of digital technologies, while relatively few studies examine their strategic role in servitization transformation, particularly the systematic explanation of the “capability–behavior–context–performance” transmission mechanism. To address this gap, this study integrates dynamic capability theory and the opportunity window theory to construct a moderated mediation model that uncovers the internal mechanisms and boundary conditions through which digital platform capability influences servitization innovation performance. Based on survey data from 237 manufacturing firms in Guangdong Province, the empirical results indicate that: (1) digital platform capability and value co-creation both exert significant positive effects on servitization innovation performance; (2) value co-creation mediates the relationship between digital platform capability and servitization innovation performance; and (3) although organizational distance was theoretically expected to function as an important contextual variable, this study does not find evidence supporting its inverted U-shaped moderating effect, suggesting that its role in digital contexts may be more complex. This study not only extends the application of dynamic capability theory and opportunity window theory in servitization innovation settings but also provides managerial insights for manufacturing firms to optimize digital platform strategies and build more resilient and sustainable innovation systems. Full article

This study establishes a systematic and reproducible workflow for topology optimization (TO) of indexable face milling cutter bodies with integrated internal coolant channels, designed for Additive Manufacturing (AM) of metallic parts. Grounded in Design for Additive Manufacturing (DfAM) principles, the workflow combines displacement-based TO and computational fluid dynamics analysis to generate simulation-driven tool geometries tailored to the constraints of AM. By leveraging iterative design knowledge, the proposed methodology enhances the scalability and repeatability of the design process, reducing development time and supporting rapid adaptation across various tool geometries. AM is explicitly exploited to integrate support-free internal coolant channels directed toward the insert cutting edge, thereby achieving a 20% mass reduction relative to the initial milling tool designs, and improving material usage efficiency at the design stage. The workflow yields numerically optimized geometries that maintain simulated global stiffness under the considered loading conditions and exhibit coolant flow distributions that effectively target the exposed cutting edges. These simulation results demonstrate the feasibility of an AM oriented, workflow-based approach for the numerical design of milling tools with internal cooling, mass reduction and provide a focused basis for subsequent experimental validation and comparison with conventionally manufactured counterparts. Full article

Due to a number of advantages, such as the high power-to-weight ratio of the system, the possibility of easy control and the freedom of arrangement of the system components on the machine, hydrostatic drive is one of the most popular methods of machine drive. The actuators in such a system are hydraulic cylinders that convert fluid pressure energy into mechanical energy for reciprocating motion. One disadvantage of conventional actuators is their weight, so research is being conducted to make them as light as possible. Directions for this research include the use of modern engineering materials such as composites and plastics. This paper presents the possibility of using new lightweight yet strong materials for the design of a hydraulic cylinder. The base of the hydraulic cylinder were designed and subjected to FEM numerical analyses. The base was made of PET. In addition, a composite cylinder made of wound carbon fibre was subjected to numerical analyses and experimental validation. The numerical calculations were verified in experimental studies. To improve the reliability of the numerical calculations, the material parameters of the composite materials were determined experimentally instead of being taken from the manufacturer’s data sheets. The composite cylinder achieved a weight reduction of approximately 94.4% compared to a steel cylinder (95.5 g vs. 1704 g). Under an internal pressure of 20 MPa, the composite cylinder exhibited markedly higher circumferential strain (4329 μm/m) than the steel cylinder (339.6 μm/m), and axial strain was also greater (−1237 μm/m vs. −96.4 μm/m). Full article

This study presents a Design for Additive Manufacturing (DfAM)–driven redesign of an industrial robot vacuum gripper for Fused Deposition Modeling (FDM), focusing on the systematic transformation of a multi-part, machined aluminum assembly into a lightweight, support-minimized polymer component suitable for continuous industrial operation. Beyond a practical redesign, the work contributes a geometry-centered DfAM methodology that links internal channel topology, overhang control, and functional interfaces to manufacturability, vacuum performance, and cost efficiency. The development follows three iterative design revisions, progressing from a geometry-adapted baseline toward a fully DfAM-optimized solution. A key innovation is the introduction of support-free internal vacuum channels with triangular cross-sections, enabling complete elimination of soluble support material within enclosed cavities. This redesign reduces the internal vacuum volume by 44%, leading to faster vacuum response while maintaining functional suction performance. The optimized overhang angles, filleted load paths, and DfAM-compliant suction cup seats significantly reduce post-processing requirements and improve structural robustness. Experimental validation under industrial operating conditions confirms that the final design achieves reliable vacuum performance and mechanical durability. Compared to the original configuration, the optimized gripper demonstrates a substantial reduction in manufacturing complexity, with printing time reduced by approximately 50% and total part cost decreased by 26%, primarily due to eliminated tooling, reduced support material, and simplified post-processing. The presented results demonstrate that DfAM principles, when applied systematically at both global and internal geometry levels, can yield quantifiable functional and economic benefits. The findings provide transferable design guidelines for support-free internal channels and functional interfaces in FDM-manufactured vacuum components, offering practical reference points for researchers and practitioners developing end-use additive manufacturing solutions in industrial automation. Full article

This study aims to assess the energy efficiency of LED luminaires used in public road lighting by comparing manufacturer-declared photometric and electrical parameters with laboratory simulation results. The research also evaluates the performance of these luminaires across various road types and installation configurations to determine compliance with national and international standards. Eleven LED luminaires were tested using a rotating mirror goniophotometer in an ISO/IEC 17025-accredited laboratory. Simulations were conducted using Dialux Evo software across six road types (M1–M6) and three installation configurations (unilateral, bilateral, and staggered). Key parameters analyzed included brog (L_m), overall uniformity (U₀), longitudinal uniformity (U_l), luminous efficacy (lm/W), power factor, and total harmonic distortion (THD) in voltage and current. Discrepancies were found between manufacturer-declared and simulation results, especially in higher-class roads (M1–M3), where up to 28.57% of luminaires failed to meet the minimum luminance requirements when tested. The study highlights the importance of validating manufacturer specifications through accredited laboratory testing. Overall, LED technology improves energy efficiency in public lighting, and inconsistencies in the power factor and luminance performance suggest the need for stricter regulatory oversight and more rigorous quality control. Simulation tools like Dialux Evo prove essential for optimizing lighting designs tailored to specific road types and traffic conditions. Full article

This study investigates the mechanical characteristics of a multi-stage centrifugal pump rotor through fluid–structure interaction (FSI) analysis. A two-stage centrifugal pump equipped with back vanes on the trailing impeller is selected as the research object. Numerical simulations are performed based on the continuity equation and Reynolds-averaged Navier–Stokes (RANS) equations, with experimental data utilized to validate the numerical model’s accuracy. The internal flow field mechanisms are analyzed, and the effectiveness of two axial force calculation methods—formula-based and numerical simulation-based—for the rotor system is comprehensively evaluated. Employing an FSI-based modal analysis approach, the governing differential equations of motion are established and decoupled via Laplace transformation to introduce modal coordinates. Modal analysis of the pump rotor system is conducted, revealing the first six natural frequencies and corresponding vibration modes, along with critical speed calculations. The findings demonstrate that when the flow field near the back vanes exhibits complex characteristics, the formula-based axial force calculation shows reduced accuracy. In contrast, without back vanes, the hydraulic motion in the impeller rear chamber remains relatively stable, resulting in higher accuracy for formula-based axial force predictions. The calculation error between the two conditions (with/without back vanes) reaches 27.6%. Based on vibration mode characteristics and critical speed analysis, the pump is confirmed to operate within a safe region. The rotor system exhibits two similar adjacent natural frequencies differing by less than 1 Hz, with perpendicular vibration mode directions. Additionally, rotational speed fluctuations in the rotor system induce alternating critical speed phenomena when operating in this region. This study establishes a coupled analysis framework of “flow field stability–axial force calculation accuracy–rotor dynamic response”, quantifies the axial force calculation error patterns under different flow field conditions of a special pump type, supplements the basic data on axial force calculation accuracy for complex structure centrifugal pumps, and provides new theoretical insights and reference benchmarks for the study of hydraulic–mechanical coupling characteristics of similar fluid machinery. In engineering applications, it avoids over-design or under-design of thrust bearings to reduce manufacturing costs and operational risks. The revealed rotor modal characteristics, critical speed distribution, and frequency alternation phenomena can provide direct technical support for the optimization of operating parameters, vibration control, and structural improvement of pump units in industrial scenarios, thereby reducing rotor imbalance, bearing wear, and other failures. Full article