Manufacturing Applications Research Articles

GEOMETRIC AND FLOW CHARACTERIZATION OF ADDITIVELY MANUFACTURED TURBINE BLADES WITH DRILLED FILM COOLING HOLES

Abstract As designers investigate new cooling technologies to advance future gas turbine engines, manufacturing methods that are fast and accurate are needed. Additive manufacturing facilitates the rapid prototyping of parts at a cost lower than conventional casting, but is challenged in accurately reproducing small features such as turbulators, pin fins and film cooling holes. This study explores the potential application of additive manufacturing and advanced hole drill methods as tools to investigate cooling technologies for future turbine blade designs. Data from computed tomography scans are used to non-destructively evaluate each of the cooling features in the blade. The resulting flow performance of these parts is further related to the manufacturing through benchtop flow testing. Results show that while flow through the entire blade is consistent throughout a full wheel of the additively manufactured cooled blades, flow through smaller regions show larger variations. Shaped film cooling holes manufactured using a high-speed electrical discharge machining method are within tolerance in the metering section but do not expand at the specified angle in the diffuser even though design tolerances are met. In contrast to high-speed EDM, conventional EDM holes are undersized throughout the length of the hole. The roughness results show high levels on thin walls, particularly at the trailing edge and on downskin surfaces. Internal surface roughness is higher than external roughness at most locations on the blade. The results of this study confirm that additive manufacturing along with advanced hole drilling techniques offer faster development of blade cooling designs.

Synthesizing ternary filler of multi-walled carbon nanotubes/silica/carbon for heightening fluororubber’s mechanical performance

Fluororubber (FKM) is recognized for its outstanding performance, yet there is a pressing need for materials with superior mechanical, thermal, and electromagnetic shielding properties to meet the demands of high-tech industries. The existing research is limited by the lack of a filler that can significantly enhance these properties without trade-offs. This study introduces the innovative synthesis of a ternary composite filler, multi-walled carbon nanotubes/ silica/amorphous carbon (MWCNTs@SiO2-C), through an in-situ polymerization and carbonization method, which is incorporated into FKM to systematically improve its performance. The unique silicon-coated MWCNTs@SiO2-C, optimized at 7 phr (parts per hundred parts of resin), has been shown to increase tensile strength by 206 % and reduce compression set by 17 %, while also elevating the initial decomposition temperature and achieving maximum electromagnetic interference shielding effectiveness in the X-band. Plasma treatment further enhances these properties, with a 175 % increase in tensile strength and improved surface wettability. The integration of MWCNTs@SiO2-C thus addresses a critical gap in material science, offering a substantial advancement for applications in aerospace, military, and semiconductor manufacturing where high-performance materials are essential.

The electrodynamic analysis and manipulation of PEGDA semicircular tubular structures based on optically induced dielectrophoresis

The manipulation of micron-scale semicircular tubular structures has wide applications in micro-nano processing, device manufacturing, biomedicine, and micron sensing and measurement. Here, we propose a method to fabricate and manipulate semicircular tubular structures based on optically induced dielectrophoresis (ODEP). First, electric field intensity simulations are performed for polyethylene glycol diacrylate (PEGDA) semicircular tubular structures with different conductivities and of different heights. In addition, the polarization model based on slender rods reveals that the semicircular tubular structure is subject to a negative dielectrophoretic force and tends to move along the vertical direction of the central axis. Finally, according to the maximum movement speed of the semicircular tubular structure, the resistance and dielectrophoretic force it receives are characterized. This allows for the realization of the translation and rotation operations of semicircular tubular structures of different lengths, and the assembly of multiple structures into different shapes. This assembly method holds significant promise for applications in biomedicine and the manufacturing and processing of micro-nano devices.

Exploring the superior adsorption capacity of multi-layer graphene/alginate granules for the removal of methylene blue dye from water

Graphene-based materials are gaining increasing attention towards their use in manufacturing and environmental applications. In this context, multi-layer graphene (MG) has been recently applied for the adsorption of contaminants from water resulting in promising results. However, the extreme lightness of this material often makes it difficult to handle due to its potential dispersion in the surrounding environment as well as to its transport and loss with the effluent. In this study, a novel granular material was synthesized by embedding MG into an alginate matrix, resulting in the so-called granular MG (GMG). This material was tested for the adsorption of methylene blue (MB) from water, which is a typical dye used in textile industries and must be removed from the effluent. GMG materials with different MG contents (5 and 20 %) were compared with MG and a commercial adsorbent to assess their adsorption capacity and the most performing material was selected for in-depth physical and chemical characterization. The structural, surface, kinetic, isotherm, and thermodynamic properties, the pH and temperature dependence, as well as the regeneration and reuse of GMG 5% were investigated through batch adsorption tests under different operating conditions. The study reveals that GMG 5% has a superior adsorption capacity compared to the tested materials and can be considered as a promising alternative to commercial carbon-based materials according to techno-economic considerations.

Research on vector bending sensors based on taper-drawn seven-core fiber Bragg grating

We present a novel vector bending sensor that enables simultaneous measurement of the bending response in six outer cores of a seven-core fiber (SCF) without the need for fan-in/fan-out configurations. Utilizing femtosecond laser technology, we inscribe seven Fiber Bragg Gratings (FBGs) with distinct wavelengths across the SCF cores. The sensor’s tapering process, tailored for the bending sensing scenario, effectively combines the reflection peaks of the FBGs into one detection channel, thereby substantially improving the measurement efficiency. Our experimental results demonstrate a strong directional dependence of the bending response, with a maximum sensitivity of 127 pm/m−1. The bending angle and curvature magnitude are reconstructed by analyzing the wavelength shifts of any two non-diagonal outer cores, offering a versatile solution for real-time monitoring applications. This sensor design, by eliminating the need for additional fan-in/fan-out devices, simplifies the system architecture and reduces both measurement time and sensor size, making it highly suitable for applications in precision manufacturing, environmental monitoring, and robotics.

Carcinomembrane-Camouflaged Perfluorochemical Dual-Layer Nanopolymersomes Bearing Indocyanine Green and Camptothecin Effectuate Targeting Photochemotherapy of Cancer.

Photochemotherapy has been recognized as a promising combinational modality for cancer treatment. However, difficulties such as off-target drug delivery, systemic toxicity, and the hypoxic nature of the tumor microenvironment remain hindrances to its application. To overcome these challenges, cancer cell membrane camouflaged perfluorooctyl bromide (PFOB) dual-layer nanopolymersomes bearing indocyanine green (ICG) and camptothecin (CPT), named MICFNS, were developed in this study, and melanoma was exploited as the model for MICFNS manufacture and therapeutic application. Our data showed that MICFNS were able to stabilize both ICG and CPT in the nanocarriers and can be quickly internalized by B16F10 cells due to melanoma membrane-mediated homology. Upon NIR irradiation, MICFNS can trigger hyperthermia and offer enhanced singlet oxygen production due to the incorporation of PFOB. With ≥10/2.5 μM ICG/CPT, MICFNS + NIR can provide comparable in vitro cancericidal effects to those caused by using an 8-fold higher dose of encapsulated CPT alone. Through the animal study, we further demonstrated that MICFNS can be quickly brought to tumors and have a longer retention time than those of free agents in vivo. Moreover, the MICFNS with 40/10 μM ICG/CPT in combination with 30 s NIR irradiation can successfully inhibit tumor growth without systemic toxicity in mice within the 14 day treatment. We speculate that such an antitumoral effect was achieved by phototherapy followed by chemotherapy, a two-stage tumoricidal process performed by MICFNS. Taken together, we anticipate that MICFNS, a photochemotherapeutic nanoplatform, has high potential for use in clinical anticancer treatment.

Long living human-machine systems in construction and production enabled by digital twins

Abstract In the industrial sector, products evolve significantly over their operational life. A key challenge has been maintaining precise, relevant engineering data. This paper explores the digital twin concept, merging engineering and operational data to enhance product information updates. It examines digital twin applications in construction, material flow, manufacturing and production, citing battery production and additive manufacturing. Digital twins aid in analyzing, experimenting with, and refining a system’s design and its operation, offering insights across product and system lifecycles. This includes tackling data management and model-data consistency challenges, as well as the recognition of synergies. This paper emphasizes sustainable, efficient management of engineering information, reflecting shifts in product longevity and documentation in industrial products and machinery.

Power estimation models of a 7-axis robotic arm with simulated manufacturing applications

Power estimation models of a 7-axis robotic arm with simulated manufacturing applications

Research on reconfigurable systems in discrete manufacturing workshops

Abstract With the development of smart manufacturing, the demand for personalized production has made reconfigurable systems in the manufacturing industry a focal point of research and application in high-end manufacturing. The paper analyzes the current status of the manufacturing industry and the challenges of reconfigurable technology. Furthermore, it designs and develops a reconfigurable system for discrete manufacturing of automotive components. The paper focuses on issues such as creating reconfigurable models, designing adaptive reconfiguration algorithms, accomplishing the creation of multi-layered models, the design of rule libraries, and algorithm implementation. The reconfiguration result scheme can be input into commercial software for performance simulation, and can directly integrate with production systems to complete production planning. This demonstrates the rationality of the reconfigurable models in the system, the correctness of the reconfiguration algorithms, and the effectiveness of the system, providing a theoretical basis for reconfigurable production lines.

A novel tooling-free carbon fibre reinforced polymer (CFRP) manufacturing method, double point incremental forming (DPIF) with direct electrical curing (DEC)

Carbon fibre-reinforced polymers (CFRPs) are essential in various industries due to their exceptional specific mechanical properties. However, conventional CFRP manufacturing involves significant costs related to moulds, ovens, and autoclaves, rendering it expensive for low-volume production and prototyping. This study introduces a novel method, Double-Point Incremental Forming with Direct Electric Curing (DPIF-DEC), which enables CFRP fabrication without the need for moulds, directly from CAD models, but it is not suited for mass production. This technique, enhanced by the addition of 2 wt.% carbon black to the epoxy resin matrix, improves through-thickness electrical conductivity, allowing uniform and rapid curing. DPIF-DEC demonstrates rapid localised curing, real-time process monitoring, and achieves mechanical properties comparable to traditional methods. Additionally, it reduces energy consumption, presenting a cost-effective and environmentally sustainable solution for low-volume and prototype CFRP production, laying the groundwork for future applications in continuous-fibre composite manufacturing directly from CAD models.

Innovative Metal Powder Production Using CFD with Convergent-Divergent Nozzles in Wire Arc Atomization

This study aims to enhance the production of metal powders using a novel approach that integrates computational fluid dynamics (CFD) with convergent-divergent (C-D) nozzles in wire arc spraying atomization (WASA). The primary objective is to investigate the influence of nozzle design on particle size distribution and production efficiency. Utilizing the ANSYS CFD Fluent program, simulations were conducted to analyze the effects of various parameters, including throat diameter and divergent angles, on gas dynamics and metal droplet behavior. The findings reveal that C-D nozzles facilitate the acceleration of gas flow to supersonic speeds, significantly improving the shear force acting on the molten metal, thereby promoting the fragmentation of droplets into smaller particles. Notably, the optimized nozzle configuration achieved a median particle size (D50) of 44.42 µm, suitable for additive manufacturing applications. The novelty of this work lies in its comprehensive simulation framework that allows for rapid virtual testing, potentially leading to significant improvements in the efficiency and quality of metal powder production processes. This research addresses critical gaps in the existing literature and provides a robust foundation for future studies in the field of metal powder manufacturing. Doi: 10.28991/HIJ-2024-05-03-02 Full Text: PDF

Bibliometric Analysis on the Application of IoT in Smart Manufacturing System in Industry 4.0

The rapid integration of Internet of Things (IoT) technologies in smart manufacturing systems has been a pivotal development within the framework of Industry 4.0. This study conducts a comprehensive bibliometric analysis to examine the evolution, current trends, and emerging research areas related to IoT applications in smart manufacturing. By analyzing data from a decade of scholarly publications, this research identifies key themes, influential authors, and collaborative networks that have shaped the field. The findings reveal that foundational technologies such as the internet, cloud computing, and big data are central to the development of smart manufacturing, while newer innovations like digital twins and blockchain are gaining prominence. The study also emphasizes the importance of strategic collaboration among researchers and industry professionals in advancing IoT adoption. The practical implications suggest that manufacturers should prioritize both foundational digital infrastructure and emerging IoT applications to enhance efficiency, security, and sustainability. This analysis provides a roadmap for future research and practical implementation, highlighting the critical areas where IoT can further revolutionize smart manufacturing systems.

Impact of AI on Manufacturing and Quality Assurance in Medical Device and Pharmaceuticals Industry

Global health and well-being largely depend on the pharmaceutical and medical device industries. Manufacturing and quality assurance (QA) processes are crucial to maintaining product efficacy, safety, and regulatory compliance in these sectors. Artificial intelligence (AI) integration presents ground-breaking opportunities to enhance these processes. This study aims to systematically assess the impact of AI on manufacturing and QA in these pharmaceutical and medical device industries. It examines the benefits, challenges, and ethical and legal implications of integrating AI. It offers a thorough understanding of how AI technology can and has been successfully integrated to enhance business operations. An extensive literature analysis was carried out to investigate AI's application, role, benefits, and challenges in manufacturing and quality assurance processes in both industries. Research was also conducted on emerging trends, future developments, and regulatory issues. Increased productivity, early detection of defects, safer and higher-quality goods, improved regulatory compliance, reduced costs, and more flexibility and scalability are some advantages of AI technologies. However, significant obstacles are also to overcome, such as high capital costs, data quality and availability issues, legacy system integration, ethical concerns about bias and data privacy, difficulties with regulatory compliance, and a lack of AI-skilled workers. Case studies show how AI has been utilized to guarantee regulatory compliance and optimize processes. AI integration has much to offer the pharmaceutical and medical device industries in terms of improved manufacturing and quality assurance procedures. By addressing restrictions and seizing novel opportunities, these industries can use AI's transformative potential to support innovation, enhance product quality and safety, ensure regulatory compliance, and improve global health outcomes.

Flexible Job-shop Scheduling Problem with parallel operations using Reinforcement Learning: An approach based on Heterogeneous Graph Attention Networks

The Flexible Job-shop Scheduling Problem (FJSP) has received considerable scholarly attention as a classic problem. However, in practical industrial manufacturing scenarios, it is common for an operation to have multiple preceding parallel operations. This not only necessitates adhering to the sequential relationships inherent in FJSP but also requires ensuring that preceding operations are completed simultaneously whenever feasible. We term this scenario as the Flexible Job-shop Scheduling Problem with Parallel Operations (FJSP-PO), a pervasive challenge encountered across nearly every production line in real-world discrete manufacturing applications. Despite its prevalence, there is a noticeable scarcity of research on FJSP-PO in existing literature. Given the objective of synchronizing multiple preceding operations, FJSP-PO presents a broader solution space and more intricate optimization challenges compared to traditional FJSP. To address this, we propose an Attention Restart method based on Heterogeneous Graph Attention Networks (AR-HGAT). Leveraging a heterogeneous graph network structure and reinforcement learning, AR-HGAT learns the implicit features of operations and machines through node-level and semantic-level attention mechanisms. The AR mechanism is utilized to determine the optimal scheduling of operations at specific time slots. Compared to existing FJSP methods, our AR-HGAT approach demonstrates superior performance in terms of inference time and solution effectiveness. Furthermore, we conducted a comparative analysis using authentic operational data from companies and contrasted it with results obtained from an online tree search algorithm, thereby providing empirical validation of the effectiveness of the proposed AR-HGAT method.

Prime number-based multistep measurement for separation of roundness errors

Roundness measurement is critical in manufacturing, as it ensures that products conform to precise design specifications. However, traditional multistep measurements for roundness error separation are time-consuming and limited in their ability to separate specific Fourier components. In this study, we propose a novel combined multistep measurement method with prime numbers that overcomes these limitations. We demonstrate this method through three experimental cases, achieving high levels of Fourier components in error separation with a limited number of measurements. Our method combines two ( p and q) or three ( p, q, and r) steps of prime numbers to achieve high levels of Fourier components for error separation, compared to traditional multistep measurements that require more steps. In the first experimental case, we use a 2-step and 5-step measurement to achieve traditional multistep measurement in ten steps. In the second case, we use 3-step and 5-step measurements, and in the third, we combine the 2-step, 3-step, and 5-step measurements. We achieve roundness deviations (RONt) of 12.7, 7.8, and 9.9 nm, respectively, and maximum En-values of 0.8, 0.8, and 0.7, respectively. Our proposed combined multistep measurement method using prime numbers has practical applications in manufacturing, as it reduces the time and resources required for roundness error separation while achieving a higher level of Fourier components. Our results demonstrate the effectiveness of our method and its potential to revolutionize roundness measurement in industry.

Research Status and Development Trend of Wire Arc Additive Manufacturing Technology for Aluminum Alloys

It is difficult for traditional aluminum alloy manufacturing technology to meet the requirements of large-scale and high-precision complex shape structural parts. Wire Arc additive manufacturing technology (WAAM) is an innovative production method that presents the unique advantages of high material utilization, a large degree of design freedom, fast prototyping speed, and low cast. As a result, WAAM is suitable for near-net forming of large-scale complex industrial production and has a wide range of applications in aerospace, automobile manufacturing, and marine engineering fields. In order to serve as a reference for the further development of WAAM technology, this paper provides an overview of the current developments in WAAM both from the digital control system and processing parameters in summary of the recent research progress. This work firstly summarized the principle of simulation layering and path planning and discussed the influence of relative technological parameters, such as current, wire feeding speed, welding speed, shielding gas, and so on. It can be seen that both the welding current and wire feeding speed are directly proportional to the heat input while the travel speed is inversely proportional to the heat input. This process regulation is an important means to improve the quality of deposited parts. This paper then summarized various methods including heat input, alloy composition, and heat treatment. The results showed that in the process of WAAM, it is necessary to control the appropriate heat input to achieve minimum heat accumulation and improve the performance of the deposited parts. To obtain higher mechanical properties (tensile strength has been increased by 28%–45%), aluminum matrix composites by WAAM have proved to be an effective method. The corresponding proper heat treatment can also increase the tensile strength of WAAM Al alloy by 104.3%. In addition, mechanical properties are always assessed to evaluate the quality of deposited parts. The mechanical properties including the tensile strength, yield strength, and hardness of the deposited parts under different processing conditions have been summarized to provide a reference for the quality evaluation of the deposition. Examples of industrial products fabricated by WAAM are also introduced. Finally, the application status of WAAM aluminum alloy is summarized and the corresponding future research direction is prospected.

Theoretical analysis and technical application of mechanical intelligent manufacturing based on system digital-driven technology

With the accelerating process of global industrialization, the automated fabrication industry, as an important part of the industry, is also developing rapidly. Due to the low efficiency and high resource consumption of traditional manufacturing, it is more important to improve the production efficiency of conventional manufacturing and realize the resource-saving development mode. Due to the characteristics of system digital-driven technology, it can promote the intelligent development of the manufacturing industry. Therefore, the deep integration of system digital-driven technology and manufacturing is conducive to the intelligent promotion of manufacturing. Comparing the difference between the traditional manufacturing industry and the intelligent manufacturing industry, the application potential of system digitalization technology in the manufacturing field is analyzed. Based on the analysis of the theoretical basis of the system digital-driven technology and the application of the system digital technology in the main fields, the importance of the technology for the improvement of the accuracy index in the manufacturing process is emphatically analyzed. The maximum increase can be 5.3%, and the minimum increase can be 3.3%. It can be seen that the deep integration of digital-driven technology and manufacturing can not only improve the intelligent level of manufacturing, realize the intensive development of the industry, but also realize the data sharing of the entire industrial chain.

Assessment of the environmental impacts of utilizing coal ashes and OPC for soil stabilization applications: Leachate analysis in response to rainfall interaction

The construction industry is a leading sector for coal ashes utilization, including in cement manufacturing and soil stabilization applications. In soil stabilization, coal ashes, alongside Ordinary Portland Cement (OPC), are the most commonly used materials. However, the environmental impact of coal ashes, particularly the leaching of heavy metals from stabilized soil when exposed to rainfall, remains underexplored. There is a notable gap in assessing the environmental impacts of this utilization, particularly when the stabilized soil interacts with rainfall in real-world scenarios. Therefore, this study aimed to contribute to filling this gap. Accordingly, in this study, peat soil was stabilized by using fly ash, bottom ash, and OPC. The characterization of soil mixture materials, including physicochemical and engineering properties, was established and studied first. Following the environmental impact, simulations were conducted using a column to study soil leachate under different conditions and seasons (dry and wet) in response to its interaction with rainfall. The leachate was analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to measure the concentrations of heavy metals, including copper (Cu), aluminum (Al), manganese (Mn), iron (Fe), and zinc (Zn). Additionally, Ion Chromatography (IC) was employed to determine the concentrations of major anions, including fluoride (F⁻), chloride (Cl⁻), nitrate (NO₃⁻), phosphate (PO₄³⁻), and sulfate (SO₄²⁻). The findings revealed the complex interaction of the chemical stabilization processes and environmental factors with the leaching behavior of heavy metals and anions, highlighting the significant impact of stabilization on leaching patterns. To conclude, this study provides a valuable contribution to understanding the environmental and engineering implications of utilizing coal ashes in soil stabilization.

Unveiling the cocoa-carob flavour gap in dark chocolates via instrumental and descriptive sensory analyses

Roasted carob pulp (Ceratonia siliqua) is a cocoa substitute known for its faint cocoa-like resemblance. However, the cocoa-carob flavour gap remains poorly uncharacterised. This study aimed to elucidate the sensory and molecular aspects of this flavour gap in a 70 % dark chocolate formulation via a two-pronged instrumental-sensorial approach. Descriptive Sensory Analysis (DSA) revealed carob-based chocolate was significantly sweeter, less sour and astringent than conventional dark chocolate due to the high total sugar content (45–50 % DM; HPLC/RID), low titratable acidity and tannin content, respectively. As for aroma, a distinct, albeit weak, cocoa-like aroma was present in carob-based chocolate. HS-SPME-GC-MS/FID revealed this was attributed to branched-chain Strecker aldehyde generation during roasting (2-methylbutanal, 1.17 μg/g; 3-methylbutanal, 2.89 μg/g). Notably, there was a distinct lack of alkylpyrazines. Additionally, a distinct woody, tree bark-like odour was uniquely associated with carob-based chocolates. This was due to furfural generation during roasting (2.33 μg/g). In conclusion, the aroma and taste gap between cocoa and carob was successfully characterised in this study. These findings substantiate the potential of carob application in chocolate manufacturing, thus empowering confectioners to make evidence-based decisions when evaluating cocoa substitutes.

A novel method for fully penetrated U-rib-to-deck joints: Single-sided oscillating laser arc hybrid welding

U-rib-to-deck (RTD) joints represent one of the most critical and vulnerable welding details of orthotropic steel decks. Aiming for full penetration and high-level service performance, a novel method with single-sided oscillating laser-arc hybrid welding (OLAHW) technique was proposed for the RTD joint. The weld formation, microstructure and mechanical properties were extensively investigated. The results indicated that the porosity and lack of fusion (LoF) defects effectively suppressed with the beam oscillation during LAHW process. The OLAHW technique has good spatial accessibility with larger laser beam incidence angle of 20° Beam oscillation led to an increase in acicular ferrite in the fusion zone (FZ) while simultaneously a reduction of martensite in the heat effected zone (HAZ). This was related to the cooling time, and the thermal simulation results revealed that the OLAHW sample demonstrated comparable cooling times in both the Laser-FZ and arc-FZ. Consequently, beam oscillation can generated more homogeneous microstructures and microhardness. Although the microhardness of the OLAHW sample in the FZ was increased compared to the conventional arc welding (CAW) and LAHW sample, the highest microhardness value remained within acceptable limits (380 HV). Moreover, the ultimate tensile strength of the OLAHW weld sample increased by 7 % compared to the CAW weld sample. The application of the OLAHW technique demonstrates its feasibility for engineering applications in orthotropic steel decks manufacturing.