Development Of Manufacturing Technology Research Articles

Learning accurate and efficient three-finger grasp generation in clutters with an auto-annotated large-scale dataset

With the development of intelligent manufacturing and robotic technologies, the capability of grasping unknown objects in unstructured environments is becoming more prominent for robots with extensive applications. However, current robotic three-finger grasping studies only focus on grasp generation for single objects or scattered scenes, and suffer from high time expenditure to label grasp ground truth, making them incapable of predicting grasp poses for cluttered objects or generating large-scale datasets. To address such limitations, we first introduce a novel three-finger grasp representation with fewer prediction dimensions, which balances the training difficulty and representation accuracy to obtain efficient grasp performance. Based on this representation, we develop an auto-annotation pipeline and contribute a large-scale three-finger grasp dataset (TF-Grasp Dataset). Our dataset contains 222,720 RGB-D images with over 2 billion grasp annotations in cluttered scenes. In addition, we also propose a three-finger grasp pose detection network (TF-GPD), which detects globally while fine-tuning locally to predict high-quality collision-free grasps from a single-view point cloud. In sum, our work addresses the issue of high-quality collision-free three-finger grasp generation in cluttered scenes based on the proposed pipeline. Extensive comparative experiments show that our proposed methodology outperforms previous methods and improves the grasp quality and efficiency in clutters. The superior results in real-world robot grasping experiments not only prove the reliability of our grasp model but also pave the way for practical applications of three-finger grasping. Our dataset and source code will be released.

Advances and Challenges in Biomanufacturing of Glycosylation of Natural Products

Glycosylation is one of the most common and important modifications in natural products (NPs), which can alter the biological activities and properties of NPs, effectively increase structural diversity, and improve pharmacological activities. The biosynthesis of glycosylation in natural products involves multiple complex biological processes, which are coordinated by many enzymes. UDP-glycosyltransferases (UGTs) play a crucial role in glycosylation modification, and have attracted long-term and widespread research attention. UGTs can catalyze the O-, C-, S-, and N-glycosylation of different substrates, producing a variety of glycosides with broad biological activity, while improving the solubility, stability, bioavailability, pharmacological activity, and other functions of NPs. In recent years, the rapid development of synthetic biology and advanced manufacturing technologies, especially the widespread application of artificial intelligence in the field of synthetic biology, has led to a series of new discoveries in the biosynthesis of NP glycosides by UGT. This work summarizes the latest progress and challenges in the field of NP glycosylation, covering the research results and potential applications of glycosylated derivatives of terpenes, flavonoids, polyphenols, aromatic compounds, and other compounds in terms of biogenesis. Looking to the future, research may leverage artificial intelligence-driven synthetic biology techniques to decipher genes related to the synthetic pathway, which is expected to further promote the large-scale synthesis and application of glycosylated NPs, and increase the diversity of NPs in the pharmaceutical, functional food, and cosmetic industries.

Advances and Challenges in Biomanufacturing of Glycosylation of Natural Products

Glycosylation is one of the most common and important modifications in natural products (NPs), which can alter the biological activities and properties of NPs, effectively increase structural diversity, and improve pharmacological activities. The biosynthesis of glycosylation in natural products involves multiple complex biological processes, which are coordinated by many enzymes. UDP-glycosyltransferases (UGTs) play a crucial role in glycosylation modification, and have attracted long-term and widespread research attention. UGTs can catalyze the O-, C-, S-, and N-glycosylation of different substrates, producing a variety of glycosides with broad biological activity, while improving the solubility, stability, bioavailability, pharmacological activity, and other functions of NPs. In recent years, the rapid development of synthetic biology and advanced manufacturing technologies, especially the widespread application of artificial intelligence in the field of synthetic biology, has led to a series of new discoveries in the biosynthesis of NP glycosides by UGT. This work summarizes the latest progress and challenges in the field of NP glycosylation, covering the research results and potential applications of glycosylated derivatives of terpenes, flavonoids, polyphenols, aromatic compounds, and other compounds in terms of biogenesis. Looking to the future, research may leverage artificial intelligence-driven synthetic biology techniques to decipher genes related to the synthetic pathway, which is expected to further promote the large-scale synthesis and application of glycosylated NPs, and increase the diversity of NPs in the pharmaceutical, functional food, and cosmetic industries.

COMPUTER PRODUCTION OF FACIAL EPITHETS

BACKGROUND: The issue of rehabilitation of patients with facial defects is extremely acute. In addition to the annual increase in the number of patients with cancer of the maxillofacial region, in recent years the number of people with shrapnel and gunshot wounds to the face has increased as a result of local wars and conflicts. Traditional methods of orthopedic rehabilitation of patients and the manufacture of facial epitheses are quite a complex and lengthy process. In the postoperative period, there is a sharp decrease in the quality of life of this category of patients, a violation of the basic body functions necessary for vital activity and poor social adaptation. Direct prosthetics of the face in the postoperative period was impossible due to the lack of necessary digital modeling technologies and structural materials for additive or subtractive production methods. The production of temporary or permanent facial epitheses using digital technologies is an urgent task that can improve the social and functional living conditions of patients. AIMS: Development of 3D modeling technology for additive manufacturing of facial epithets. METHODS: To achieve this goal, the first task was to develop specialized three-dimensional software for modeling defects in the facial area. The functionality of the program should allow you to virtually simulate the missing parts of the face (ear, eye, nose, orbit). To create a digital platform together with IT specialists, it was decided to use the following programming languages: C++ - Writing the software core, writing UI/UX interaction modules, interacting with the Windows operating system; C# - Complex assembly of the entire project; Python is an automated assembly of virtual library modules; OpenGL HSLS is a shader language for graphical visualization of objects; C is the creation of functions for interacting with shaders that require high speed. RESULTS: A specialized computer program has been developed for 3D modeling of prostheses in patients with defects in the middle zone of the face using combined facial scanning and computed tomography data (Computer program. Apresyan S.V., Stepanov A.G. "A program for 3D modeling of facial epitheses. Registration number (certificate) 2023663490, Registration date: 07/04/2023). Instead of obtaining analog impressions with plaster or silicone material, the developed technology uses a special 3D facial scanner, which greatly eases the suffering of patients. A virtual three-dimensional database of ears, noses, orbits, and zygomatic bones of patients of various ages and gender is integrated into the developed program. This allows the specialist to select the most adaptive part of the face to make up for the defect. Built-in modeling tools allow you to personalize a 3D model of a part of the face, based on the structural features of the maxillofacial region of a person. The finished three-dimensional model of a part of the face can be exported in various formats CONCLUSIONS: The developed 3D program for modeling defects allows to avoid invasive prosthetics approaches, to coordinate the shape of future structures with the patient. The built-in library of structures with a database provides remote manufacturing of the prosthesis without the presence of the patient, in case of a need to replace it. Among the undeniable advantages of the technology, it is important to include the fact that prostheses can be made directly on the day of surgery to remove part of the face, completely restoring lost functions and providing rapid social adaptation.

Development and Implementation of Die Forging Technology Eliminating Flange Welding Operations in Conveyor Driver Forging.

This article presents research results regarding the development of a new manufacturing technology for an element assigned to belt conveyor flights in the extractive industry through hot die forging (of a forging with a double-sided flange) instead of the currently realized process of producing such an element by welding two flanges onto a sleeve or one flange onto a flange forging. The studies were conducted to design an innovative and low-waste technology, mainly with the use of numerical modelling and simulations, partially based on the current technology of producing a flange forging. Additionally, during the development of the forging process, the aspect of robotization was considered, both in respect of the forging tools and the process of transportation and relocation of forging between the impressions and the forging aggregates. A thermo-mechanical model of the process of producing a belt conveyor flight forging with deformable tools was elaborated by means of the Forge 3NxT program. The results of the conducted numerical modelling made it possible, among other things, to develop models of forging tools ensuring the proper manner of material flow and filling of the impressions, as well as temperature and plastic deformation distributions in the forging and also the detection of possible forging defects. For the technology elaborated this way, the tools were built together with a special instrument for flanging in the metal, and technological tests were performed under industrial conditions. The produced forgings were verified through a measurement of the geometry, by way of 3D scanning, as well as the hardness, which definitively confirmed the properness of the developed technology. The obtained technological test results made it possible to confirm that the elaborated construction, as well as the tool impressions, ensure the possibility of implementing the designed technology with the use of robotization and automatization of the forging process.

Development of an Alternative Manufacturing Technology for Niobium Components.

Due to their physical and mechanical properties, niobium products are used in the nuclear power industry, chemical industry, electronics, medicine and in the defence industry. Traditional manufacturing technology for these products is characterized by long production cycles and significant material losses during their surface machining. This paper presents the results of a study on the fabrication of niobium products by Spark Plasma Sintering (SPS). Structural and mechanical tests were conducted on the products obtained, as well as a comparative analysis with the properties of products obtained using traditional technology. Based on the analysis of the test results obtained, recommendations were made for the sintering of Nb powders. It was found that the optimum temperature for sintering the powder is 2000 °C as the density of the material obtained is close to the theoretical density. The microstructure obtained is comparable to samples obtained by the traditional method after recrystallization annealing. Samples obtained according to the new technology are characterized by higher mechanical properties Rp0.2 and Rm and the highest hardness.

Overview of the development of chip manufacturing technology

With the rapid progress of modern science and technology, the manufacturing process of chips, which serves as the core of microelectronics technology, plays a crucial role in both producing and improving electronic products. With the advancement of science and technology and the continuous growth of market demand, the research and development of the chip manufacturing process has become more and more critical. This paper explores the historical development, essential technologies, and prospects related to chip manufacturing. It provides a comprehensive understanding of this field through six sections including an introduction, overview of the process, application areas, key technologies, future trends, and concluding remarks. This study offers valuable guidance and reference for related industries and research fields. It is found that the chip process has an important position and broad application prospects in the field of modern science and technology. In the future, chip manufacturing processes will move towards smaller feature sizes. Future chip manufacturing processes will pay more attention to process optimization, and improve the process flow to reduce loss and waste, in order to improve the efficiency and reliability of chip production.

Optimization of ultra-precision CBN turning of AISI D2 using hybrid GA-RSM and Taguchi-GRA statistic tools

Ultra-precision turning is a crucial process in the manufacturing industry as it helps to produce parts with high dimensional accuracy, surface finish, and tolerance. The process is similar to traditional turning but is carried out under special circumstances to achieve greater precision and surface finish. The process can be applied to conventional structural materials, but the demand for machining hardened steels is increasing. The optimization of ultra-precision turning of AISI D2 using cubic boron nitride (CBN) tools is a crucial aspect in the field of high-quality machining. This study aims to evaluate the performance of the process and identify the optimal parameters that result in the best quality components while using a CBN tool's ultra-precision turning of AISI D2. Ultra-precision turning process factors such as cutting speed, feed, and depth of cut were experimentally investigated to enhance the response output, such as surface roughness and cutting force components. The full factorial experimental design was used for determining the process characteristics under different conditions, and experimental results were applied to search for the optimum response of machining performance. The optimization process was done by combining the hybrid genetic algorithm-response surface methodology (GA-RSM) and the Taguchi-grey relational analysis (GRA) statistical tools. These methods are useful in situations where the relationship between the input variables and the output responses is complex and non-linear. The results showed that a hybrid GA-RSM approach, combined with Taguchi-GRA statistical analysis, can effectively find optimal process parameters, leading to the best combination of surface roughness and cutting force. In hybrid Taguchi - GRA, the optimal cutting conditions were found to be a cutting speed of 175 m/min, a feed of 0.025 mm, and a depth of cut of 0.06 mm. The findings of this study provide valuable insights for the optimization of ultra-precision CBN turning operations, contribute to the development of precision manufacturing technology, and can be used as a reference for similar machining processes.

Tensile, flexural and fracture properties of MEX-printed PLA-based composites

Due to the continuous development of material extrusion-additive manufacturing (MEX-AM) technology, the fracture behavior of polymeric parts, and especially of their associated composites, presents some shortcomings and also a challenge in the field. In this paper, the fracture properties of non-reinforced (NR) and reinforced Polylactic Acid (PLA) samples manufactured by MEX-AM process are investigated through tensile, flexural and fracture mechanics tests. The samples are reinforced with glass fibers (GF-PLA), carbon fibers (CF-PLA) and bronze particles (BP-PLA), and tested parallel (named FLAT for all tests) and normal (named UPRIGHT for tensile test, and ON-EDGE for flexural and fracture mechanics tests) to the layer growth (LG). It was found that regardless of the type of test, the LG and the material significantly influence the mechanical properties and collapse modes of the MEX-printed samples. It was obtained that the parallel-LG load is favorable for the tensile and flexural tests, and the normal-LG for the fracture mechanics tests. Overall, the NR-PLA material gives the best strength, strain and energy absorption properties, CF-PLA stands out as the stiffest material, while BP-PLA presents the minimum performances for almost all properties. The macroscopic analyzes of the fractured samples clearly highlight distinct failure mechanisms associated with each type of test, material and LG. From the analysis of the mechanical behavior and macrostructural images, CF-PLA was identified as the most brittle material, and NR-PLA the most ductile.

High-accuracy ultrasonic imaging of the defects in the complex-surface components by the search-vector imaging condition

Complex-surface components play more and more significant roles in engineering practice because of the development of manufacturing technology and requirements from various industries. Void and crack defects inside the components greatly deteriorate the mechanical properties, and ultrasonic full-matrix imaging is a promising method to detect the defects. However, the research on high-quality full-matrix imaging for complex-surface components is limited. In this paper, a full-matrix imaging method based on the search-vector imaging condition is proposed to detect the defects in complex-surface components with high accuracy. Herein, the search-vector imaging condition is established based on waveform inversion, which employs the first-order derivative vector and approximated Hessian matrix to obtain the high-accuracy images of defects. The proposed imaging condition does not make assumptions about the wavefield and is more rigorous than the conventional excitation-time imaging condition. Furthermore, the proposed method can highlight defects throughout the measurement area, so it is very convenient for locating defects in large measurement structures. In the simulation and experiments, defects in complex sound speed models are the measurement targets, and the proposed method has significantly improved the imaging accuracy, resolution and signal-to-noise ratio (SNR) in all cases compared with the conventional methods, where all the void and crack defects are highlighted clearly in the whole image. In addition, the proposed method is not sensitive to the influencing factors and has strong robustness. Therefore, the proposed method has great potential in defect detection for complex-surface components in various fields.

Direct FE[formula omitted] failure prediction of fused-filament fabricated parts

The rapid development of additive manufacturing technology and the consequential microstructural variations have brought the simulation aspects into focus. To capture an accurate mechanical response, multiscale methods are used to determine the macroscopic constitutive behaviour. Among these methods, the recently introduced Direct FE2 (DFE2) technique has shown some success in predicting material behaviour via the direct incorporation of representative microstructure volumes into the macroscopic structure. The present study highlights the predictive modelling capabilities of DFE2 linked with an element elimination technique (EET) in investigating the performance of fused-filament fabrication (FFF) samples under tension and compression. Parts were manufactured by FFF with various raster angles to vary the failure characteristics. Their mechanical responses and fracture behaviours were simulated by DFE2 and benchmarked against conventional finite element (FE) analysis, highlighting that the results of DFE2 were competitive against FE. Most importantly, the combination of EET with DFE2 resulted in predictive insights regarding changes in the failure surface for samples with varying raster angles.

Fracture of four semi-regular lattices regulated by T-stress in modified boundary layer models

The development of additive manufacturing technology has promoted the rise of various lattice metamaterials, and evaluating their fracture properties is critical for both application and safety. Here, by conducting finite element simulations on four types of elastic-brittle semi-regular lattices (kagome, snub-trihexagonal, elongated-triangular, and snub-square), we indicate that the fracture toughness of lattice metamaterials is not solely determined by the crack-tip singular term, i.e., the critical stress intensity factor, but is also influenced by the non-singular T-stress term. T-stress regulates fracture toughness by modulating geometrical distortions and force-carrying modes of lattice bars around the crack front. This regulation effect depends on the lattice topology and becomes weaker under mixed-mode loading. As the relative density of lattices decreases, T-stress can force elastic buckling of bars around the crack front, which may deteriorate the fracture toughness. Additionally, positive T-stress tends to promote the crack deflection and negative T-stress tends to inhibit. Our results offer new insights into the structure-property relationships in the presence of T-stress, which may contribute to design the geometry of micro/nano-lattice metamaterials.

Mechanical and thermal properties of Gyroid-based W[sbnd]Cu composites produced via laser powder bed fusion assisted by infiltration

Plasma-facing components for thermonuclear fusion reactors require the introduction of new materials due to outstanding demands in mechanical, thermal, and thermal cycle fatigue resistivity properties. One promising solution is the WCu composite material or multimaterial that combines the properties of both components. In the present work, WCu samples were obtained by laser powder bed fusion (LPBF) consolidation of a tungsten porous matrix followed by copper infiltration. A design of structures with ordered porosity was achieved by translation of skeletal gyroid unit cell (triply periodic minimal surface). A relative density of 96.7% was achieved for solid pure tungsten samples with optimized LPBF process conditions. As-built W gyroid samples had a 15–20% ultimate compressive strength (UCS) of the solid sample. After the infiltration with copper, the ductility of WCu composites increased drastically, i.e. the samples did not fracture at a strain of 35%. It was found that UCS, yield strength (YS), and thermal diffusivity were sensitive to gyroid unit cell size. The sample with the smallest cell size of 2 mm had superior YS of 626 MPa and thermal diffusivity of 76.4 mm2/s. The obtained results will shed light on the possibilities for further development of WCu manufacturing technology based on the LPBF method combined with subsequent infiltration.

An optimization method of wall thickness distributions in T-shaped tube compound-forming method with unconventional tube blank

The thin-walled T-shaped tube is widely applied in aviation pipeline systems with the development of lightweight manufacturing technology. However, the severe wall thickness thickening is a bottleneck problem restricting the application of T-shaped tubes. In order to avoid excessive thickening and improve the overall performance of the formed parts, an optimization method of wall thickness distributions in T-shaped tube compound forming by using optimized unconventional tube blank is proposed. The strain spline method is adopted to investigate the stress-strain state and deformation mechanism of T-shaped compound forming. The optimization model of tube blank is established and includes two parts: the initial optimization based on the geometric analytic method and the iterative optimization based on the incremental finite element method. The optimal tube blank is achieved through two-step optimizations. The numerical simulations and experiments of T-shaped tube compound forming using conventional and optimized tube blanks are carried out to investigate the forming height and the wall thickness distributions. The simulation and experimental results agree with a no more than 20 % relative error. The optimal tube blank could effectively improve the wall thickness distributions compared with the T-shaped tube compound using the conventional tube blank. The final experimental results show that the maximum thickening rate decreases from 48.67 % to 28.67 %, the maximum thinning rate decreases from 25.33 % to 18 %, and the maximum difference in the wall thickness decreases from 1.11 mm to 0.7 mm. The comparison results are further verified to be the correctness of the optimization method and the effectiveness of the T-shaped tube compound forming method with unconventional tube blank in the actual experiments.

A comprehensive review on surface modifications of polymer‐based 3D‐printed structures: Metal coating prospects and challenges

AbstractThe production of complex structures out of a variety of materials has undergone a revolution due to the rapid development of additive manufacturing (AM) technology. Initially confined to applications such as magnetic actuators and two‐dimensional electric or electronic circuits, the convergence of 3D printing and metallization methods has emerged as a revolutionary approach. This synergy facilitates the creation of functional and customizable metal‐polymer hybrid structures characterized by high strength, lightweight properties, intricate geometric designs, and superior surface finish. These structures also exhibit enhanced electrical and thermal conductivity, as well as optical reflectivity. This paper reviews techniques to improve the effectiveness of 3D‐printed polymer antennas and structures by using various techniques of metallization. The metallization processes are examined, and a classification based on the materials employed is presented to facilitate comparisons that highlight the optimal utilization of materials for the fabrication of 3D‐printed polymer structures. The main emphasis here is on the effectiveness of different processes in terms of deposition, bonding strength, electrical conductivity, and various characteristics of metallic coatings developed on polymers. This review contributes an in‐depth analysis of the latest developments in 3D printing and metallization techniques specifically applied to polymer antennas and structures. The exploration extends to potential applications, challenges encountered, and future prospects within this dynamic field. As AM and metallization continue to evolve, this study aims to provide a comprehensive understanding of the state‐of‐the‐art methodologies and their implications for the future of polymer‐based structures and antennas.

Pharmaco-technological research and stability of the drug for the treat-ment and prevention of vitamin and trace element deficiency in animals

The article presents the research results on the Development of manufacturing technology and the study of the stability of a solution for oral use based on carnitine hydrochloride, vitamins – E, B12, choline chloride, selenium, and zinc. “Devivit Carnitine” oral is used for the prevention of diseases of liver and muscle tissue metabolism in farm animals and poultry, nephrosis, myocarditis, prevention of stress (heat, transport, sound, food, post-vaccination, etc.), and prevention of vitamin and hypovitaminosis. When developing the drug technology, experimentally obtained pharmaco-technological properties of active substances and excipients were taken into account. The technological process of preparing an oral solution consists of four technological stages: preparation of canisters for filling, preparation of the solution, filling containers with medicine and packaging. The stability and shelf life of “Devivit Carnitine” (solution for oral use) in plastic canisters were determined. It was established that the drug sample in plastic canisters was stable, according to all quality control methods indicators, during the entire period of the study. The shelf life of the medicinal product with carnitine hydrochloride, vitamins E and B12, choline chloride, selenium, and zinc is 12 months. In the future, a study of preclinical data is planned to verify whether the drug does not reveal a particular hazard for animals based on conventional studies of safety pharmacology, repeated dose toxicity, genotoxicity, carcinogenicity, and developmental toxicity.

Challenges and opportunities for the built environment in a carbon-constrained world for the next 100 years and beyond

Today, the built environment, including infrastructure for tunnels, bridges, highways, subways, railroads, harbors, buildings and airports, is responsible for a significant portion of the energy consumption, natural resource utilization, waste generation as well as CO2 and other environmentally harmful emissions in the United States and around the world. There is no silver bullet solution to achieve the ambitious goal of zero carbon buildings and a city infrastructure with significantly reduced CO2 emissions. Thus, multifaceted solutions should be developed. Another challenge associated with the built environment is aging and a large economic burden to upgrade and maintain the outdated infrastructure. The current status of the U.S. built environment is far below sustainable condition. Rapidly deteriorating infrastructure that must be replaced provides us with the unique opportunity to rethink where and how we should live in the future. In addition, current challenges related to economic and societal inequality in the United States and other global communities also force us to re-evaluate how humanity is connected and how we share resources for a sustainable and healthy future while keeping the Earth safe. The engineering solutions for our future built environment include, but are not limited to, the design and synthesis of new infrastructure materials with low carbon intensity, the development of new manufacturing options and technologies, and the integration of innovative functionalities into building envelopes.

ADAPTIVE PROCESS MANAGEMENT USING DEEP LEARNING ON A PROGRAMMABLE LOGIC CONTROLLER (PLC)

In the era of Industry 4.0, the integration of advanced digital technologies into manufacturing processes has become paramount for enhancing operational efficiency and adaptability. This study introduces a groundbreaking approach to adaptive process management through the integration of deep learning algorithms within Programmable Logic Controllers (PLCs), thus addressing the limitations of traditional PLCs in dynamically adjusting to new operational conditions without manual intervention. By leveraging the inherent capabilities of deep learning for realtime data analysis and decision-making, this research develops a novel framework that enables PLCs to autonomously learn from process data, adapt control strategies in real-time, and optimize manufacturing operations. The methodology encompasses the design and implementation of deep learning models tailored for PLC environments, the development of a data-driven learning mechanism directly on the PLC, and a comprehensive evaluation of the system’s adaptability, efficiency, and performance in real-world industrial settings. The findings reveal significant improvements in process efficiency, reduction in downtime, and enhanced adaptability to changing operational conditions, demonstrating the potential of combining deep learning with PLC-based systems for fostering intelligent and flexible manufacturing processes. This study not only provides a viable solution to the challenges of static PLC programming but also opens new ways for research and development in smart manufacturing technologies, offering insights into the practical implications of deploying intelligent automation systems in Industry 4.0.

Experimental investigation on a lightweight, efficient, counter-rotating fan with and without boundary layer ingestion

AbstractThe experimental investigations on the counter-rotating CRISPmulti fan with boundary layer ingestion are presented in this paper. The Counter Rotating Integrated Shrouded Propfan (CRISP) was designed, aerodynamically optimized and manufactured in lightweight material by the German Aerospace Center (DLR). The main task was to maximize the aerodynamic efficiency under restricted static, dynamic and acoustic properties of the blade designed with lightweight carbon-fiber material and to apply it as a demonstrator for the development of a new innovative blade manufacturing technology. The rotors were manufactured at the DLR Institute of Structures and Design and tested on the Multi-stage 2-shaft Compressor Test Facility (M2VP) at the DLR Institute of Propulsion Technology. The instrumentation enabled the measurement of the aerodynamic, static, dynamic and acoustic behavior of the fan. In general, the targets of the experimental investigation were to validate the optimization results, the numerical calculational methods and the acoustic tools. Additionally, inlet distortion measurements were carried out on the fan rig to investigate the effect of the boundary layer ingestion on a real counter-rotating propfan. A radially traversable disturbance body, designed to simulate the boundary layer of the aircraft fuselage on an aircraft architecture with embedded engines, enables a comprehensive measurement program to be carried out for both undisturbed and disturbed inflow.

DSCU-Net: MEMS Defect Detection Using Dense Skip-Connection U-Net

With the rapid development of intelligent manufacturing and electronic information technology, integrated circuits play a vital role in high-end chips. The semiconductor chip manufacturing process requires precise operation and strict control to ensure chip quality. The traditional manual visual inspection method has a high workforce cost and intense subjectivity and is accompanied by a high level of misdetection and leakage. Computer vision-based wafer defect detection technology is gaining popularity in the industry. However, previous methods still find it challenging to meet the production requirements regarding accuracy. To solve the problem, we propose a defect detection network based on a coding and decoding structure, Dense Skip-Connection U-Net (DSCU-Net), which optimizes the skip connection between the encoder and decoder and enhances the profound fusion of high-level semantics and low-level semantics to improve accuracy. To verify the effectiveness of DSCU-Net, we validate it in actual microelectromechanical systems (MEMS) data, and the results show that DSCU-Net reaches an optimal level. Therefore, the DSCU-Net proposed in this paper effectively solves the defect detection problem in semiconductor chip manufacturing. This method reduces workforce cost and subjectivity interference and improves inspection efficiency and accuracy. It will help to promote further development in the field of intelligent manufacturing and electronic information technology.