Manufacturing Process Research Articles

Enhancing manufacturing efficiency and quality through automation and deep learning: addressing redundancy, defects, vibration analysis, and material strength optimization

This article explores the integration of automation and deep learning in modern manufacturing to address critical challenges such as redundancy, defects, vibration analysis, and material strength. As manufacturing processes evolve, the need for more sophisticated methods to optimize production efficiency and product quality becomes paramount. Automation, coupled with deep learning techniques, offers powerful tools for enhancing manufacturing processes. These technologies enable predictive maintenance, reducing downtime by identifying potential equipment failures before they occur. Furthermore, deep learning algorithms can analyse complex data sets to detect defects in products with greater accuracy and speed than traditional methods. Vibration analysis, a key aspect of predictive maintenance, benefits from automated systems that monitor and diagnose issues in real-time, preventing costly disruptions. Additionally, deep learning models can assess material strength and predict potential failures, ensuring that products meet rigorous safety and quality standards. The synergy between automation and deep learning not only streamlines manufacturing processes but also enhances the ability to adapt to changing conditions, thereby minimizing operational inefficiencies. This article highlights the transformative impact of these technologies on the manufacturing industry, illustrating their potential through case studies and practical examples. By addressing key challenges such as redundancy and defects, automation and deep learning contribute to the creation of more reliable, efficient, and resilient manufacturing systems. The insights provided in this study underscore the importance of continued innovation in integrating these technologies to maintain a competitive edge in the rapidly evolving manufacturing landscape.

Ergonomic design of paddy irrigation covers to increase agricultural productivity

The use of conventional galengan in rice fields in Rumpa'e hamlet, Telle Village, Ajangale District. Bone is still made from soil, banana trees and bamboo as raw materials for making galengan. This is easy for damage to occur because the soil is not dense and is not effective in making galengan, thus hampering the irrigation process system between rice fields. Therefore, the aim of this research is to design a rice irrigation cover design that is not easily damaged and makes the irrigation process system between rice fields easier. This research uses the method QFD (Quality Function Deployment)So there are 9 statements produced based on the results of interviews with farmers, these 9 statements have been classified based on the interests and needs of farmers. Based on the results of this research, it is possible to design a rice irrigation cover design based on the results of QFD data processing that is not easily damaged using various types of raw materials.(Stainless steel) and is efficient in the manufacturing process, making it easier for farmers in the process of using it because it uses a sliding system.

Sustainable waste management practices in the informal sector: Towards industrial symbiosis

Industrial pollution is considered to be routed in the waste and byproducts of the production process. Traditional pollution control approaches try to eliminate and/or treat the pollutants which are often technically complicated and expensive. In this regard, industrial ecology and industrial symbiosis have emerged as effective strategy to eliminate industrial pollution. This principle requires the generated waste/by-products absorbed in the same or other industrial process cycles and thus the material cycle remains closed. Industrial pollution appears as a big problem in the global south countries, where industrialization is considered as the main thrust of economic development. Usually, in such countries formal pollution control approaches are primarily directed to the formal sectors (such as state owned and legally registered industries), informal sectors are often left behind. Although the role of informal sector is increasingly being recognized for sustainable development, their significance in pollution abatement is a less discussed topic. This article attempts to investigate the informal industrial sector in Dhaka, Bangladesh with empirical evidence. Adopting a qualitative approach with field investigation of the informal industries and detail interviews, this study identified that the informal industries are closely linked in clusters according to the manufacturing process and continue material/byproduct/waster exchange primarily from the need to minimize cost. The studied patterns of waste management practice indicate existence of industrial symbiosis without adequate academic/technical knowledge and designed efforts. This suggests that the informal sector can meaningfully contribute to sustainable development offering insights for the application of similar approaches in the formal sector.

Ultrasonic TFM imaging inspection of large complex rings using defect quantitative evaluation mappings

ABSTRACT Large complex rings are widely used in wind power energy, aerospace, large construction machinery. There are different scales of defects in the manufacturing process for large complex rings. Because of the complex cross-section and large thickness, it is difficult to quantitative evaluation of defects by conventional ultrasonic technology. Therefore, the ultrasonic total focusing method (TFM) defect quantitative inspection for large complex rings is proposed in this paper. First, the TFM inspection technology of large complex rings for simultaneous scanning of the end-face and side-face is designed. Then, the maximum amplitudes of defects are collected at each grid point of the imaging area by the TFM inspection of calibration specimens. The Φ1.5mm defect quantitative evaluation mappings are obtained by the interpolation fitting algorithm. Finally, the ultrasonic TFM and B-scan inspection experiments of the Φ3440mm large ring are carried out. The results show that the TFM quantitative evaluation mapping has higher accuracy compared to the conventional B-scan method. Especially for the Φ1.5mm defects, the average error of TFM quantitative evaluation is 2.92%. The proposed method can effectively identify defects of other sizes that exceed the calibration mapping. This work has industrial application value for developing ultrasonic TFM inspection of large complex components.

The Effect of Canal Curvature and Different Manufacturing Processes of Five Different NiTi Rotary Files on Cyclic Fatigue Resistance

Abstract Objectives The aim of this study was to evaluate the cyclic fatigue resistance of ProTaper Universal, ProTaper Next, E-FLEX EDGE, E-FLEX ONE, and ZenFlex nickel-titanium (NiTi) rotary files in 60 and 90 degrees of simulated canal curvature. Materials and Methods ProTaper Universal, ProTaper Next, E-FLEX EDGE, E-FLEX ONE, and ZenFlex were used in this study. Each system was divided into two groups testing in simulated canals with 60 and 90 degrees of curvature. Both groups were set to rotate under a controlled temperature at 37°C until fracture. The number of cycles to fracture (NCF) was recorded and two fractured files from each group were randomly selected to analyze the fractographic pattern using scanning electron microscopy (SEM). Statistical Analysis The NCF between the two groups was analyzed statistically using the Mann–Whitney U test. The statistical differences between each system at the same degree of artificial canal curvature were analyzed using the Kruskal–Wallis test. A significant difference was set at p < 0.05. Results E-FLEX ONE showed the highest mean NCF (p < 0.05) when performed in 60- and 90-degree curvatures. In addition, the file tested in a 60-degree curvature exhibited higher resistance to cyclic fatigue than the one tested in a 90-degree curvature in the mutual NiTi system (p < 0.05). The SEM micrographs exhibited a similar crack initiation area, which is the feature of cyclic fatigue failure. Conclusion E-FLEX ONE showed the greatest resistance to cyclic fatigue in both 60 and 90 degrees of curvature. This study implies that E-FLEX ONE is appropriate for severely curved canals.

Ultrasonic Levitation as a Handling Tool for In-Space Manufacturing Processes

Abstract 3D printing is one of the key technologies in space exploration. The disparity in gravitational forces between Earth and space presents both challenges and opportunities with regard to material handling. This article examines the potential of employing ultrasonic levitation as a handling tool for substrate-free additive manufacturing processes in microgravity environments. Through preliminary experiments, we demonstrate the feasibility of manipulating polymer powders using acoustic fields while concurrently melting the levitated material. Subsequent experiments conducted in our drop tower facility confirm our ability to manipulate particles with acoustic traps under microgravity conditions. Building upon these findings, we outline plans to further advance our research using an expanded acoustic levitation system capable of three-dimensional object manipulation. Our objectives include moving and orienting large components beyond the wavelength limit in microgravity, manipulating granular raw material while melting it in proximity to the print part, and achieving a semi-continuous fusion of print material with the print part. Therefore, we present an intelligent control strategy based on the results of a digital twin simulation. Furthermore, we utilize a stereo camera combined with computer vision as feedback for the control system to ensure precise handling of the manipulated objects and particles. This study represents a significant advance toward the realization of efficient substrate-free additive manufacturing processes in microgravity environments, with potential applications for in-space manufacturing. Ultimately, this could result in long-term space missions becoming less reliant on supply deliveries, thus reducing cost and additionally enabling faster response to unforeseen issues.

Heterogeneous Transfer Learning of Electrohydrodynamic Printing Under Zero-Gravity Toward In-Space Manufacturing

Abstract As we continue to commercialize space and mature in-space manufacturing (ISM) processes, there is a strong need to transfer the knowledge we learn from experiments on the ground to zero-gravity environments. Physics-motivated manufacturing processes, like additive manufacturing, experience a shift in fabrication parameters due to the absence of gravity and the change of environments. Thus, we found traditional machine learning methods are not capable of addressing this domain shift and present a transfer learning scheme as a solution in this paper. We tested a kernel ridge regression model built for heterogeneous transfer learning (KRR-HeITL) on data from the electrohydrodynamic inkjet printing (EHD printing) process. EHD printing is a process that uses electrical force to control material flows, thus achieving the fabrication of electronics without requiring gravity. Our team has successfully conducted three rounds of parabolic flights to validate this technology for ISM. We trained on multiple datasets built from on-ground experiments and tested using zero-gravity printing data obtained from parabolic flight tests. Measurements of the Taylor cone both on-ground and in zero-gravity were taken and exploited as a part of the training data. We found that our method obtains good interpolation accuracy (MAPE 3.85%) compared to traditional machine learning methods (MAPE 16.84%) for predicting the printed line width. We concluded that the KRR-HeITL method is well suited for zero-gravity domain shifts of EHD printing parameters. This study paves the way for future predictions of ISM parameters when there are only on-ground experiments or very limited zero-gravity datasets for a given process.

Effects of the manufacturing process on the flexural properties of EBMed lattice structures

AbstractLattice structures are very interesting since they present good mechanical properties coupled with lightness. Today, the maturity reached by additive manufacturing technologies allows the production of such structures. However, the mechanical properties of the constituting material can be affected by the process itself, because of the particular geometry. In fact, in a previous work, the mechanical characteristics of the bulk‐printed material were used for modelling the bending behavior of lattice‐cored specimens made of Ti6Al4V and produced through electron beam melting (EBM) process, but a certain discrepancy with experimental results was found. Therefore, in this work, a procedure was proposed to determine the mechanical properties of the material the lattice specimen is made of, in order to reduce the gap between the numerical and the experimental results. By considering the redetermined yield strength, such mismatch was reduced. Moreover, the metallographic analysis of the material found that the α laths of the α + β microstructure, typical of the studied alloy, were thinner than those of bulk specimens, and the presence of α′ martensite was discovered too. The fracture surface analysis determined a ductile failure mode for the lattice core while a fragile mode for the skins.

Additive Manufacturing of Waste Electrical and Electronic Equipment (WEEE) Produced From Acrylonitrile Butadiene Styrene (ABS)

Objective: To evaluate the feasibility of producing recycled acrylonitrile-butadiene-styrene (r-ABS) filaments from waste electrical and electronic equipment (W EEE) casings, specifically discarded monitors and televisions, and to compare their properties with those of virgin ABS. Theoretical Framework: The research was based on a literature review of additive manufacturing, WEEE recycling, and the thermal, mechanical, rheological, and microscopic characterizations of recycled polymers, with an emphasis on fused deposition modeling (FDM). Method: WEEE casings were collected and mechanically recycled to produce r-ABS filaments. These filaments were characterized and compared with virgin ABS filaments using infrared spectroscopy (FTIR), thermal analyses (TGA and DSC), rheological, mechanical, and microscopic evaluations. Results and Conclusion: The results indicated that r-ABS filaments exhibit properties comparable to those of virgin ABS. FTIR analysis revealed the presence of the main functional groups of ABS in the recycled samples. Thermal analysis showed similar behavior between the recycled and virgin materials, with a single thermal decomposition event. Rheological analysis demonstrated that r-ABS possesses viscoelastic properties suitable for the FDM process, and mechanical characterization showed that r-ABS exhibited tensile strength close to virgin ABS. Microscopic analysis revealed good layer adhesion and a low number of voids, factors that contribute to the quality of the printed objects. Research Implications: This study contributes to the valorization of polymeric waste, promoting the use of recycled materials in additive manufacturing processes, which can benefit both the environment and the 3D printing industry. Originality/Value: The research addresses a topic still underexplored in the literature, especially concerning the recycling of WEEE casings for the production of ABS filaments.

Solvent-Free Method of Polyacrylonitrile-Coated LLZTO Solid-State Electrolytes for Lithium Batteries

Solid-state electrolytes (SSEs), particularly garnet-type Li6.4La3Zr1.4Ta0.6O12 (LLZTO), offer high stability and a wide electrochemical window. However, their grain boundaries limit ionic conductivity, necessitating high-temperature sintering for improved performance. Yet, this process results in brittle electrolytes prone to fracture during manufacturing. To address these difficulties, solvent-free solid-state electrolytes with a polyacrylonitrile (PAN) coating on LLZTO particles are reported in this work. Most notably, the PAN-coated LLZTO (PAN@LLZTO) electrolyte demonstrates self-supporting characteristics, eliminating the need for high-temperature sintering. Importantly, the homogeneous polymeric PAN coating, synthesized via the described method, facilitates efficient Li+ transport between LLZTO particles. This electrolyte not only achieves an ionic conductivity of up to 2.11 × 10−3 S cm−1 but also exhibits excellent interfacial compatibility with lithium. Furthermore, a lithium metal battery incorporating 3% PAN@LLZTO-3%PTFE as the solid-state electrolyte and LiFePO4 as the cathode demonstrates a remarkable specific discharge capacity of 169 mAh g−1 at 0.1 °C. The strategy of organic polymer-coated LLZTO provides the possibility of a green manufacturing process for preparing room-temperature sinter-free solid-state electrolytes, which shows significant cost-effectiveness.

Direct Precursor Route for the Fabrication of LLZO Composite Cathodes for Solid-State Batteries.

Solid-state batteries based on Li7La3Zr2O12 (LLZO) garnet electrolyte are a robust and safe alternative to conventional lithium-ion batteries. However, the large-scale implementation of ceramic composite cathodes is still challenging due to a complex multistep manufacturing process. A new one-step route for the direct synthesis of LLZO during the manufacturing of LLZO/LiCoO2 (LCO) composite cathodes based on cheap precursors and utilizing the industrially established tape casting process is presented. It is shown that Al, Ta:LLZO can be formed directly in the presence of LCO from metal oxide precursors (LiOH, La2O3, ZrO2, Al2O3, and Ta2O5) by heating to 1050°C, eliminating the time- and energy-consuming synthesis of preformed LLZO powders. In addition, performance-optimized gradient microstructures can be produced by sequential casting of slurries with different compositions, resulting in dense and flat phase-pure cathodes without unwanted ion interdiffusion or secondary phase formation. Freestanding cathodes with a thickness of 85µm, a relative density of 95%, and an industrial relevant LCO loading of 15mg show an initial capacity of 82 mAh g-1 (63% of the theoretical capacity of LCO) in a solid-state cell with Li metal anodes, which is comparable to conventional LCO/LLZO cathodes and can be further improved in the future.

Emerging trends in large format additive manufacturing processes and hybrid techniques

AbstractLarge format additive manufacturing (LFAM) technologies are rapidly growing with significant potential for application in multiple technological sectors like aerospace, tooling, automotive, marine, construction, and energy. LFAM processes offer significant advantages including reduced lead time, cost, and material waste, which are further amplified due to the increased volume of the components. This review paper focuses on LFAM technologies with the highest technology readiness level, i.e., metal Directed Energy Deposition (DED), polymer extrusion, and solid-state deposition (i.e. cold spray additive manufacturing (CSAM)). Common system setups, the maximum deposition rate, and the range of processable materials, along with the achievable mechanical properties and geometrical characteristics, are outlined for each technology, both in individual and hybrid manufacturing formats. The main technological challenges are gathered and discussed to highlight the areas that require further development. Finally, the current industrial applications for LFAM technologies and the expected future developments are outlined. This review provides an overview of LFAM technologies’ current status and discusses their potential in improving the manufacturing of complex and large geometries, with a significant reduction in material and energy consumption, while ensuring high-quality and high-performance components.

Web tension AI modeling and reconstruction for digital twin of roll-to-roll system

AbstractDigital twins (DT) are gaining attention as an emerging technology in Smart manufacturing systems. These DTs comprise various units that enable simulation, monitoring, and prediction of the manufacturing process. This study introduces a predictive model for web tension and a tension reconstruction algorithm for the DT of the roll-to-roll (R2R) system. The observed web tension signals from tension sensors decomposed into a mean component, a sinusoidal wave, and a random noise. Utilizing deep neural networks, the predictive model integrated various sub-models to forecast statistical (mean, standard deviation) and frequency domain (main frequency, signal-to-noise ratio) features of the web tension signal. Through fivefold cross-validation, 23 model architectures were optimized, with selected architectures ranging from 16-32-32-1 to 16-32-64-32-1 nodes per layer. Overall, R2 scores on the test set ranged from approximately 52 to 100%. The proposed reconstruction algorithm generated tension signals from the model’s predictions that closely resemble the original tension signals, indicating credible reconstructions. The proposed predictive model and reconstruction algorithm were integrated into the DT of the R2R system, offering a valuable tool for monitoring and optimizing the R2R process.

Mechanisms, Applications, and Challenges of Utilizing Nanomaterials in Cryopreservation

Cryopreservation of biological samples, including cells, tissues, and organs, has become an essential component in various biomedical research and applications, such as cellular therapy, tissue engineering, organ transplantation, and conservation of endangered species. However, it faces critical challenges throughout the cryopreservation process, such as loading/unloading of cryoprotective agent (CPA), ice inhibition during cooling, and ultrafast and uniform heating during rewarming. Applying nanomaterials in cryopreservation has emerged as a promising solution to address these challenges in each step due to their unique properties. For instance, in order to deliver nonpermeating CPA into cells, some nanomaterials, such as polymeric nanocapsule, can carry nonpermeating CPA to penetrate into the cells, regulating the intracellular ice crystal. During cooling, some nanomaterials, such as graphene oxide, can bind to basal or prism planes of ice crystals, suppressing the ice growth. During rewarming, some nanomaterials, such as magnetic nanoparticles, can improve the heating performance, preventing devitrification and recrystallization during rewarming. However, challenges in nanomaterials‐assisted cryopreservation remain, including the need for comprehensive studies on nanomaterials toxicity and the development of scalable manufacturing processes for industrial applications. This review examines the role of nanomaterials in cryopreservation, focusing on their mechanisms, applications, and associated challenges.

Production-oriented approach for optimal mass-customisation of floor panel layouts in cross-laminated timber (CLT) buildings

PurposeThis study aims to develop a production-oriented approach for optimal mass-customisation of floor panel layouts in cross-laminated timber (CLT) buildings. The study enables meeting building clients’ unique floor plan requirements at an optimal cost and simultaneously enhances manufacturers’ profit by minimising material and manufacturing process waste.Design/methodology/approachThe present research uses a hybrid approach consisting of field data collection, mathematical modelling, development of a Genetic Algorithm (GA) and scenario analysis. Field data includes engineered timber production information, design data and building code requirements. The study adopts the Flexible Demand Assignment (FDA) technique to formulate a mathematical model for optimising the design of mass timber buildings and employs GA to identify optimal production solutions. Scenario analysis is performed to validate model outputs.FindingsThe proposed model successfully determines the load-bearing wall placement and building spans and specifications of floor panels that result in optimal production efficiency and the desired architectural layout. The results indicate that buildings made of a single category of thickness of panels but customised in various lengths to suit building layout are the most profitable scenario for CLT manufacturers and are a cost-effective option for clients.Originality/valueThe originality of the present study lies in its mathematical and model-driven approach towards implementing mass customisation in multi-storey buildings. The proposed model has been developed and validated based on a comprehensive set of real-world data and constraints.

Overview of research on additive manufacturing of hydrogel-assisted lab-on-chip platforms for cell engineering applications in photodynamic therapy research.

Lab-on-chips supported by hydrogel matrices are excellent solutions for cell culture; thus, this literature review presents examples of scientific research in this area. Several works are presenting the properties of biocompatible hydrogels that mimic the cellular environment published recently. Hydrogels can also be treated as cell transporters or as a structural component of microfluidic devices. The rapidly growing scientific sector of hydrogel additive manufacturing is also described herein, with attention paid to the appropriate mechanical and biological properties of the inks used to extrude the material, specifically for biomedical purposes. The paper focuses on protocols employed for additive manufacturing, e.g., 3D printing parameters, calibration, ink preparation, crosslinking processes, etc. The authors also mention potential problems concerning manufacturing processes and offer example solutions. As the novel trend for hydrogels enriched with several biocompatible additives has recently risen, the article presents examples of the use of high-quality carbon nanotubes in hydrogel research enhancing biocompatibility, mechanical stability, and cell viability. Moving forward, the article points out the high applicability of the hydrogel-assisted microfluidic platforms used for cancer research, especially for photodynamic therapy (PDT). This innovative treatment strategy can be investigated directly on the chip, which was first proposed by Jędrych E. et al. in 2011. Summarizing, this literature review highlights recent developments in the additive manufacturing of microfluidic devices supported by hydrogels, toward reliable cell culture experiments with a view to PDT research. This paper gathers the current knowledge in these intriguing and fast-growing research paths.

Biochemical Evaluation and Stability Assessment of Eye Drops Manufactured at Mengo Hospital: A Quality Control Study

This comprehensive study undertook a thorough evaluation of the biochemical composition and stability of eye drops manufactured at Mengo Hospital. A range of analytical tests were conducted to assess the eye drops' pH, osmolarity, viscosity, protein content, and susceptibility to microbial contamination. Additionally, stability testing was performed under various storage conditions to simulate real-world scenarios. The results of the study revealed that the eye drops manufactured at Mengo Hospital largely conformed to regulatory standards for pH and osmolarity. However, significant variations were observed in viscosity and protein content, indicating inconsistencies in the manufacturing process. Furthermore, stability testing under accelerated conditions demonstrated degradation of the eye drops, highlighting concerns regarding their shelf life and potency. Notably, microbial contamination was detected in some samples, raising concerns about the risk of eye infections and the need for improved sterilization protocols. A comparative analysis with commercial eye drops revealed similarities in biochemical composition but distinct differences in stability profiles. This suggests that while the Mengo Hospital eye drops may possess similar characteristics to commercial products, their stability and longevity may be compromised. The findings of this study have significant implications for quality improvement initiatives at Mengo Hospital. Recommendations include optimizing the manufacturing process to minimize variations in viscosity and protein content, implementing enhanced sterilization protocols to prevent microbial contamination, and conducting regular stability testing to ensure the eye drops' potency and shelf life. By addressing these areas, Mengo Hospital can enhance the quality and safety of its eye drops, ultimately benefiting patients and maintaining trust in its products.

Accurate Inspection and Super-Resolution Reconstruction for Additive Manufactured Defects Based on Stokes Vector Method and Deep Learning

Defects in additive manufacturing processes are closely related to the mechanical and physical properties of the components. However, the extreme conditions of high temperatures, intense light, and powder during the manufacturing process present significant challenges for defect detection. Additionally, the high reflectivity of metallic components can cause pixels in image sensors to become overexposed, resulting in the loss of many defect signals. Thus, this paper mainly focuses on proposing an accurate inspection and super-resolution reconstruction method for additive manufactured defects based on Stokes vector and deep learning, where the Stokes vectors, polarization degree, and polarization angles of the inspected defects are effectively utilized to suppress the high reflectivity of metallic surfaces, enhance the contrast of defect regions, and highlight the boundaries of defects. Furthermore, a modified SRGAN model designated SRGAN-H is presented by employing an additional convolutional layer and activation functions, including Harswish and Tanh, to accelerate the convergence of the SRGAN-H network and improve the reconstruction of the additive manufactured defect region. The experiment results demonstrated that the SRGAN-H model outperformed SRGAN and traditional SR reconstruction algorithms in terms of the images of Stokes vectors, polarization degree, and polarization angles. For the scratch and hole test sets, the PSNR values were 33.405 and 31.159, respectively, and the SSIM values were 0.890 and 0.896, respectively. These results reflect the effectiveness of the SRGAN-H model in super-resolution reconstruction of scratch and hole images. For the scratch and hole images chosen in this study, the PSNR values of SRGAN-H for single image super-resolution reconstruction ranged from 31.86786 to 43.82374, higher than the results obtained by the pre-improvement SRGAN algorithm.

Forming performance and environmental impact of bamboo fiber reinforced polypropylene composites based on injection molding process for automobiles

AbstractTo explore the potential application of plant fiber reinforced composites for automotive component applications, this study prepared bamboo fiber (BF)/nano‐talc/polypropylene (PP) composites based on the injection molding process, comprehensively evaluated the effect of reinforcement materials on the forming properties of composites, including thermal performance, mechanical properties, water absorption, etc. Furthermore, taking a certain automotive injection molded interior part as the object, a life‐cycle assessment from production to the gate was conducted based on the real energy and material consumption during the composite preparation process. The results indicate that adding BF and talc powder increased the thermal stability, density, hardness, viscosity, and crystallinity of the composites while reducing the water contact angle on the surface. Surface‐modified BF and PP showed good compatibility. Talc powder exhibited good dispersibility in PP, and the synergistic effect of BF and talc powder effectively enhanced the composite performance. The tensile, flexural, and impact strength of the composites were improved by 40.64%, 51.48%, and 66.51%, respectively, compared with pure PP. The modulus of the composite increased nearly 2 times compared with pure PP. Additionally, the composite demonstrated good friction and wear properties. The environmental impact of the BF composite manufacturing process was significantly higher than that of pure PP. The substantial consumption of electricity, chemicals, and water resources in the extraction and modification processes of BF were the main factors. The findings of this study contribute to achieving green, high‐performance BF composite manufacturing and the expansion of its applications.Highlights Composites have a higher environmental impact compared to PP. BF and talc can synergistically enhance the performance of composites. BF shows good compatibility with PP. Composites exhibit good friction and wear characteristics.

Development of a Novel Transonic Fan Casing Making Use of Rapid Prototyping and Additive Manufacturing

Additive manufacturing (AM) presents significant cost savings and lead time reductions because of features inherent to the manufacturing process. The technology lends itself to rapid prototyping due to the streamlined workflow of quickly implementing design changes. Compared to traditional machining, AM techniques are simpler in execution for design engineers because they do not require detailed engineering drawings and they typically make use of the nominal geometry in computer models. A novel transonic fan casing assembly has been developed that makes use of AM inserts surrounding the rotor to provide an opportunity to cost-effectively change the corresponding flowpath. The rapid prototyping design philosophy developed from this work will allow for numerous experimental studies into the effects that different design parameters of casing geometries have on fan aerodynamic performance. A fan stage representative of a small turbofan engine was successfully tested with smooth-walled, additively manufactured inserts as a baseline case for future configurations. Before installing the 3D printed casing assembly, computational thermal stress analysis was performed to reduce the risk in implementation due to the demanding environment associated with the rotor. AM components and materials typically have nonlinear mechanical properties, adding to the complexity of the structural analysis. As part of the research, steady aerodynamic performance was measured over the entire relevant operating range of the fan.