Aeronautical Manufacturing Research Articles

3D printing and blockchain: aeronautical manufacturing in the digital era

ABSTRACT This research highlights the incorporation of 3D printing and blockchain technology into aeronautical manufacturing and certification procedures with an aim to increase operational efficiency. The integration of 3D printing allows for streamlined production, while the immutable features of blockchain provide traceability and certification advantages, thus offering the potential for transformative impacts within the aviation supply chain. This study primarily focuses on investigating the implications and multiple benefits of this integration into the aviation industry. Furthermore, given the absence of economic assessments priorly conducted on this integration, the study also includes a mathematical formulation that provides a quantifiable measure of the achievable return on investment. Two distinct case studies provide real data as evidence supporting the efficacy of this proposed integrated model. The outcome suggests a new paradigm for the supply chain ecosystem, leading to operational improvements and economic benefits.

An analytical model for pressure distribution in automated fiber placement on irregular surfaces and its application in aeronautical manufacturing

Automated fiber placement (AFP) is a key technology in the fabrication of composite aeronautical components, but the layup defects associated with uneven and insufficient contact pressure limit its application on irregular surfaces. Existing methods for pressure optimization in AFP are mostly based on extensive compaction experiments, which lacks theoretical basis and is not applicable to complex surfaces. In this paper, an analytical model of pressure distribution in AFP is proposed, which is suitable for any irregular surfaces. The influence of mechanical properties of contact materials and the mold curvatures on the calculation of contact pressure is taken into consideration. The Hertz theory is also extended to the three-dimensional contact area to suit the practical needs. Furthermore, an algorithm for pressure calculation along any layup path is proposed to rapid construct the pressure field. Then three sets of experiments are carried out on two aeronautical molds to validate the proposed model. The results show that the model can accurately calculate the contact pressure distribution in AFP, and compared with the previous model, the comprehensive prediction accuracy of the peak pressure is improved by 27.25 %. Combined with the layup path information, this model can be used to analyze the mechanical mechanism of layup defects, which provides a theoretical basis for the optimization of AFP parameters based on pressure distribution.

Early detection of tool wear in electromechanical broaching machines by monitoring main stroke servomotors

This paper aims to provide researchers and engineers with evidence that sensorless machine variable monitoring can achieve tool wear monitoring in broaching in real production environments, reducing production errors, enhancing product quality, and facilitating zero-defect manufacturing. Additionally, broaching plays a crucial role in improving the quality of manufacturing products and processes. These aspects are especially pertinent in aeronautical manufacturing, which serves as the experimental case in this study.The research presents findings that establish a correlation between the variables of a broaching machine’s servomotors and the condition of the broaching tools. The authors propose an effective method for measuring broaching tool wear without external sensors and provide a detailed explanation of the methodology, enabling reproducibility of similar results. The results stem from three trials conducted on an electromechanical vertical broaching machine, utilizing cemented carbide grade broaching tools to broach a superalloy Inconel 718 test piece. The machine data collected facilitated the training of a set of machine learning models, accurately estimating tool wear on the broaches. Each model demonstrates high predictive accuracy, with a coefficient of determination surpassing 0.9.

A Low-Code Edge Computing-based Predicting Scheme For Aero-Engine Components to Enable Intelligent Aeronautical Manufacture

A Low-Code Edge Computing-based Predicting Scheme For Aero-Engine Components to Enable Intelligent Aeronautical Manufacture

Pose estimation and robotic insertion tasks based on YOLO and layout features

In this study, we proposed a practical scheme for the challenging robotic cable insertion task. In general, the applied architecture is based on two YOLOs, vision-based pose estimation and admittance control. A precise and effective method was developed to estimate the pose of a manipulated connector. Our method uses a deep convolutional neural network to detect the relevant regions in the image. The characteristics of these relevant regions along with the pins’ layout manifold are combined to conduct the estimation. Practical problems such as error examination and time efficiency were considered in the proposed method for real applications. An admittance controller is introduced to experimentally validate the performance of pose estimation and provide compliant insertion by the proposed architecture. Our method is only based on less prior layout knowledge and does not require a precise model, which facilitates modeling and deployment. In addition, our method is robust to image quality and has low computational complexity, which makes it highly suitable for online manipulation. Besides, our method can handle multiple connector types which can cover most cases in aeronautical manufacturing and guide the design of connectors in the production process. The advantages of our method were demonstrated by extensive testing using both synthetic data and experiments. We also designed an insertion controller and realized a complete insertion task using a PC with a 12 GB RTX 3060 GPU and 32 GB RAM. These experimental results show that our method can achieve precise and reliable estimation with mean absolute errors less than 0.44 deg and 0.36 mm, an estimation accuracy of over 99%, and a successful manipulation rate of over 94%. This reveals that the proposed method displays potential for the challenging robotic cable insertion task.

Towards an improved compression after impact response of thin plies using ply grade hybridization and unsymmetrical laminate designs

With thin structures used in the aircrafts, aeronautical manufacturers are worried about the response of these thin laminates towards impact and post impact loads. Thin laminates studied to show reduced compression after impact strengths with thin plies and hence continues to be a primary concern to the aeronautical industries. In this work, we aim to use ply grade hybridization (mixing different ply grades) and unsymmetrical laminate designs as an effort to improve the low velocity impact response and compression after impact strength of thin laminates. Using different materials, uni-directional and non-crimp fabrics, through experimental, numerical and optimization methods, we demonstrate that hybridization along with unsymmetrical designs can improve the CAI strength by upto 40% over the thin ply baseline laminates.

Test frame misalignment effect on CFRPs mechanical properties

Traditionally, major aircraft manufacturers have shown great interest in ensuring a high degree of alignment in the load train of test machines that determine the mechanical properties of the CFRP materials being tested. This is manifested in the definition of stringent requirements as far as alignment is concerned in the actual testing regulations of these manufacturers, being the main reference standard ASTM E1012. This standard establishes different categories or classes, depending on the deformation recorded on a test piece instrumentalized with strain gauges. Specifically, the standard defines classes 5, 8 and 10, and it is common to establish class 5 for static tests on CFRPs, whereas these same tests on metallic materials usually require class 10. The present work aims to quantify the influence of the misalignment of the test frames on the mechanical properties of CFRPs subjected to static tensile testing (maximum tensile strength and modulus). In addition, the influence on the mechanical properties of the application of corrections of the test specimen has been studied when determining the degree of alignment based on the reference standard ASTM E1012. This last aspect is currently being studied by aeronautical manufacturers in the discussion forum of the NADCAP accreditation program, in its NMMT commodity. The present work shows the methodology used, as well as the results obtained for its discussion.

Experimental study of thermal behaviour of face grinding with alumina angular wheels considering the effect of wheel wear

The grinding industry is a high added-value manufacturing sector that is subject to ongoing improvements due to the increasing demands for productivity, accuracy and surface integrity. Although angular wheels are commonly used for face grinding in both automotive and aeronautical manufacturing, there is little information available regarding the specific details of applying this process. For this particular process, the effect of the wheel angle on process performance, the influence of kinematic parameters during the appearance of grinding burn or wheel wear is still unknown. This paper presents an experimental study of the thermal behaviour of face grinding with alumina angular wheels when considering the effect of wheel wear. The effect of grinding parameters has been examined using the concept of aggressiveness, which has been adapted to the kinematics of the process of face grinding with angular wheels. Special attention has been paid to the effect of the geometry of the wheel and to the dressing conditions. Through an extensive experimental study of power measurements and acid etching surface inspections complemented with temperature simulations, the behaviour of this process in response to grinding burn has been analysed in order to optimize the wheel duration towards grinding burn.

Benefits of Hydrogen in a Segmented-Anode Plasma Torch in Suspension Plasma Spraying

Suspension plasma spraying (SPS) enables the production of various coating microstructures with unique mechanical and thermal properties. Aeronautical manufacturers have been working for fifty years to improve the thermal barrier coating (TBC) performances in gas turbines. Commercial plasma torches with a segmented anode that are characterized by stable plasma jets should enable a better control of the TBC microstructure. The addition of diatomic gases such as hydrogen in the plasma-forming gas affects the plasma jet formation and causes some instabilities. However, it enhances the thermal conductivity of the gas flow, the plasma mass enthalpy and the heat transfer to particles. This study aims to characterise and describe the coating microstructure changes of yttria-stabilised zirconia when gradually adding hydrogen with argon into the plasma gas mixture. The effect of hydrogen is weighted out due to the gas mass enthalpy, mean velocity at the nozzle exit and “hot zone” length of the plasma jet. The coating microstructures, which depend on these plasma jet parameters, will be mapped from feathery and porous to dense and cracked deposits depending on the spraying conditions.

MÉTODO PARA EL DISEÑO DE PUESTOS DE TRABAJO PARA PERSONAS CON TRASTORNO DEL ESPECTRO AUTISTA EN LA INDUSTRIA 4.0

The increase of studies in recent years on Autism Spectrum Disorder and its employability, is an opportunity for research focused on social and occupational inclusion of this group. The lack of inclusive jobs for this population is partly due to the absence of frameworks, methodologies and tools that allow the development of solutions for their adaptation. The main contribution is focused on the development of a model for the design of jobs for the empowerment of workers and articulated from the enactive paradigm in the context of Vygotsky's Activity Theory (AT), Ashby Variety Law (VL) and, supported by the Design for X (DfX) with a proposal of application to a case study for the industry 4.0. The proposed case study focuses on the design for the adaptation of an accessible workplace within an aeronautical component manufacturing plant that incorporates workers with ASD, with the intention of promoting the socio-labour development and inclusion of these individuals in an industrial, technological and innovative environment. KeyWords: Autism spectrum disorder (ASD); inclusive workplace design; Activity Theory (AT); Required Variety Law (RVL); occupational environment; design for ASD 4.0; design for X (DfX).

Proposal and application of a procedure for analysis of idleness and wastes in an aircraft company

Este estudo analisa o desempenho dos trabalhadores em uma empresa aeronáutica. Porosidade (ociosidade) foi definida como desperdícios referentes a comportamentos contraproducentes no trabalho, e a taxa de agregação de valor será analisada testando quatro hipóteses: diferenças entre técnicas de coleta de dados; diferenças entre os tipos de desperdícios medidos; variação da taxa de agregação de valor durante o dia de trabalho e relação entre ociosidade e informações sobre o perfil do operador. Os dados coletados do Sistema de Gestão Integrada (SGI) da empresa foram superiores aos observados, a ociosidade apresentou o maior valor dentre outros desperdícios, a parte da manhã teve maior valor agregado do que a parte da tarde (especialmente no final da manhã) e os trabalhadores que eram casados e tinham filhos apresentaram menor ociosidade. Este artigo mostra como a ociosidade é importante nas análises Lean no gerenciamento de operações e como o procedimento pode diminuir a ociosidade.

Detection and Classification of Aircraft Fixation Elements during Manufacturing Processes Using a Convolutional Neural Network

The aerospace sector is one of the main economic drivers that strengthens our present, constitutes our future and is a source of competitiveness and innovation with great technological development capacity. In particular, the objective of manufacturers on assembly lines is to automate the entire process by using digital technologies as part of the transition toward Industry 4.0. In advanced manufacturing processes, artificial vision systems are interesting because their performance influences the liability and productivity of manufacturing processes. Therefore, developing and validating accurate, reliable and flexible vision systems in uncontrolled industrial environments is a critical issue. This research deals with the detection and classification of fasteners in a real, uncontrolled environment for an aeronautical manufacturing process, using machine learning techniques based on convolutional neural networks. Our system achieves 98.3% accuracy in a processing time of 0.8 ms per image. The results reveal that the machine learning paradigm based on a neural network in an industrial environment is capable of accurately and reliably estimating mechanical parameters to improve the performance and flexibility of advanced manufacturing processing of large parts with structural responsibility.

Outcomes of Meaningful Work in the Context of Indian Blue-collar Employees: The Moderating Role of Relational Identification and Organisation-based Self-esteem

The study investigates the moderating effect of relational identification and organisation-based self-esteem (OBSE) on the relationship between meaningful work and prudence, as well as meaningful work and civic virtue behaviour, in the context of blue-collar employees working in the Indian aeronautical manufacturing sector (IAMS). Survey data collected from 312 blue-collar employees showed that meaningful work has a positive influence on prudence as well as civic virtue behavior only at high levels of relational identification and OBSE. These relationships were insignificant at the lower level of the moderators. The findings of the study hold significant research, practice, and societal implications, because meaningful work in the context of blue-collar employees of the aeronautical industry has not been studied before, though this industry has high growth potential.

Comparison of the performance of three domain transform filters for radiographic contrast enhancement of welded objects

Weld quality inspection using industrial radiography is considered to be one of the most important processes in critical industries such as aeronautical manufacturing. The quality of radiographic images of welded industrial parts may suffer from poor signal-to-noise ratio (SNR), the main cause of which is the unavoidable detection of scattered X-rays. Image processing methods may be used to enhance image contrast and achieve improved defect detection. In this study, the outcomes from three different image contrast enhancement spatial domain transform algorithms are analysed and compared. The three algorithms used are normalised convolution (NC), interpolated convolution (IC) and recursive filtering (RF). Based on the results of qualitative operator perception, the study shows that the application of all three methods results in improved image contrast, enabling enhanced visualisation of image detail. Subtle differences in performance between the outputs from the different algorithms are noted, especially around the edges of image features. Furthermore, it is found that RF is approximately two orders of magnitude quicker than the other algorithms, making it more suitable for online weld inspection lines.

Could self-centrism rust the glitter of meaningful work? Exploring the darker sides of the construct

PurposeThe paper explores if individuals experiencing deeply meaningful work turn self-centric and therein they negatively affect people around them. It also discusses ways to attenuate this darker effect of meaningful work.Design/methodology/approachSemi-structured interviews were conducted with supervisors, peers, subordinates, and family of 24 executives in the Indian Aeronautical Manufacturing Sector who scored high on the Meaningful Work scale in another empirical study carried out by the authors in early 2019.FindingsIndividuals experiencing deeply Meaningful Work get self-centric, at times, where nothing beyond work appeals to them. This negatively affects their camaraderie at work and family ties.Originality/valueThe paper adds to the scarce literature on the darker side of Meaningful Work by exploring its effect on breeding self-centrism using an Indian sample.

Development Trend of NC Machining Accuracy Control Technology for Aeronautical Structural Parts

High-performance five-axis computer numerical control machine tools are widely used in the processing of Aeronautical Structural parts. With the increase of service life, the precision of CNC machine tools equipped by aeronautical manufacturing enterprises is declining day by day, while the new generation of aircraft structural parts are developing towards integration, large-scale, complexity, thin-walled and lightweight. It is very easy to produce dimension overshoot and surface quality defects due to unstable processing technology. The machining accuracy of aircraft structural parts is also affected by complex factors such as cutting load, cutting stability, tool error, workpiece deformation, fixture deformation, etc. Because of the complexity of structure and characteristics of Aeronautical Structural parts, the consistency and stability of cutting process are poor. It is easy to cause machining accuracy problems due to tool wear, breakage and cutting chatter. Relevant scholars have carried out a lot of basic research on NC machining accuracy control and achieved fruitful results, but the research on NC machining accuracy control of Aeronautical structural parts is still less. This paper elaborates from three aspects: error modeling method of NC machine tools, error compensation method, prediction and control of machining accuracy, and combines the characteristics of Aeronautical Structural parts, the development trend and demand of NC machining accuracy control technology are put forward.

Elliptical model for surface topography prediction in five-axis flank milling

In five-axis flank milling operations, the intersecting surfaces of different cutting edges create roughness on the milled surfaces that cannot be ignored in situations with strict requirements, especially in aeronautical manufacturing. To focus on motion problems in milling operations, this paper presents a new model that utilizes elliptical paths as cutting edge trajectories on 3D surface topography machined by peripheral milling. First, the cutter parallel axis offset and location angle are considered, which change the location of the ellipse center and intersection point of the cutting edges. Then, through the proposed model, the predicted surface topography is obtained, and the factors that affect the development tendency of roughness are analyzed. Next, the effects of the cutter location position (CLP) geometric parameters, cutter parallel axis offset and curvature on the roughness are evaluated by a numerical simulation. Finally, machining tests are carried out to validate the model predictions, and the results show that the surface topography predictions correspond well with the experimental results.

Design for Automation within the aeronautical domain

Worldwide air traffic has been increasing through the last years, and recent researches indicate that the demand for new aircraft will continue to rise over next few decades. Even today, aeronautical manufacturing involves a large proportion of manual labour which directly affects the production capacity of the industry. Thus, in order to meet the market demand and reach the dynamism that the industry must have to compensate the changes that are driven by customers, the automation of the production lines has become increasingly necessary to guarantee the competitiveness of the aircraft manufacturing companies. On this context, this work presents the development of a Design for Automation designing tool—DFAut—that aims at clarifying the automation requirements of a product at the conceptual design phase. Through this study, it has been verified that the use of the DFAut method has yielded automation requirements that were not feasible to be accomplished by a competitive product to the market. However, within the Integrated Product Design concept, the DFAut results could be adjusted to render the product automation configuration feasible. The DFAut tool has been successfully applied to the design of a wing box, and the results are fully discussed herein.

Evolution stages of aircraft manufacturing firms

AbstractAeronautics is one of the highest value‐adding industrial sectors in an economy, and many regions have sought to develop aeronautics industries for economic diversification. Aircraft production, however, is complex and capital‐intensive, and efforts to establish aircraft manufacturing firms have led to mixed results. Here, we present a study of development of six international aeronautical manufacturing firms, across four continents, using a mixed‐method approach. Using empirical quantitative data and results from 103 semistructured interviews with senior executives and policy makers, we identify a set of discrete stages: inception, base production, competitive growth, inventive development, and maturity that characterize the evolution pathways of aeronautics firms. We find that firms do not necessarily follow a linear development path, and they can jump and skip stages or may regress back to earlier stages under financial or other pressures. We find that aeronautics firms are more likely to reach a self‐sustaining maturity stage once they establish independent contracts with multiple partners and are able to develop their own technologies. The results indicate that firms should establish strategies to acquire independent contracts through competitive bidding and should plan for achieving innovation capabilities early on as this is crucial for their long‐term viability.

Corrosion Behavior of AA7075-T73 Aluminum Alloy During Machining of Aeronautical Components

Corrosion of AA7075-T73 aluminum alloy during machining process was studied. An experimental device was proposed in order to simulate machining procedure. A design of experiments - DOE was used in order to evaluate what process parameter is significant. Some electrochemical tests based on open-circuit potential vs time measurements and potentiodynamic polarization were performed in machining fluid of low and high chloride concentrations. Results from DOE showed that the chloride concentration in machining fluid and the presence or not of a zinc coating on the bench vice jaw material in the machining system, along with the interaction between these both factors are significant. OCP results showed oxide growth with time in low and high chloride concentration machining fluid. Passivity breakdown was only observed in high chloride concentration machining fluid. Best fitted parameters were applied to a large scale aeronautical manufacturing company, achieving 95 % reduction in corrosion appearance on the manufactured parts.