Aerospace Manufacturing Industry Research Articles

Virtual prototyping of vision-based tactile sensors design for robotic-assisted precision machining

Vision-Based Tactile Sensors (VBTS) play a key role in enhancing the accuracy and efficiency of machining operations in robotic-assisted precision machining systems. Equipped with VBTS, these systems offer contact-based measurements, which are essential in machining accurate components for industries such as aerospace, automotive, medical devices, and electronics. This paper presents a novel approach to virtual prototyping of VBTS, specifically in perpendicularity measurements using Computer-Aided Design (CAD) generation of VBTS designs, Finite Element Analysis (FEA) simulations, and Sim2Real deep learning to achieve VBTS with high precision measurements. The virtual prototyping approach enables an understanding of the contact between VBTS with different designs and machined surfaces in terms of contact module shape, thickness, markers’ density. Additive manufacturing was employed to fabricate the molds of VBTS contact module, followed by experimental validation of the robotic arm to confirm the effectiveness of the optimized VBTS design. The results show that deviation from the hemispherical shape reduces the data quality captured by the camera, hence increasing the prediction errors. Additionally, reducing the thickness of the contact module enhances the precision of perpendicularity measurements. Importantly increasing markers’ distribution density significantly enhances the accuracy of up to 92 markers at which above it the rate of improvement becomes less pronounced. An VBTS with height of 20mm, thickness of 2mm, and 169 markers was found to be within the stringent perpendicularity standards of the aerospace manufacturing industry of 0.58∘ as a root mean square error, and 1.64° as a max absolute error around the roll and pitch axis of rotation. The established virtual prototyping methodology can be transferred to a wide variety of elastomer-based sensors.

Developing Bayesian EWMA chart for change detection in the shape parameter of Inverse Gaussian process.

Bayesian Control charts are emerging as the most efficient statistical tools for monitoring manufacturing processes and providing effective control over process variability. The Bayesian approach is particularly suitable for addressing parametric uncertainty in the manufacturing industry. In this study, we determine the monitoring threshold for the shape parameter of the Inverse Gaussian distribution (IGD) and design different exponentially-weighted-moving-average (EWMA) control charts based on different loss functions (LFs). The impact of hyperparameters is investigated on Bayes estimates (BEs) and posterior risks (PRs). The performance measures such as average run length (ARL), standard deviation of run length (SDRL), and median of run length (MRL) are employed to evaluate the suggested approach. The designed Bayesian charts are evaluated for different settings of smoothing constant of the EWMA chart, different sample sizes, and pre-specified false alarm rates. The simulative study demonstrates the effectiveness of the suggested Bayesian method-based EWMA charts as compared to the conventional classical setup-based EWMA charts. The proposed techniques of EWMA charts are highly efficient in detecting shifts in the shape parameter and outperform their classical counterpart in detecting faults quickly. The proposed technique is also applied to real-data case studies from the aerospace manufacturing industry. The quality characteristic of interest was selected as the monthly industrial production index of aircraft from January 1980 to December 2022. The real-data-based findings also validate the conclusions based on the simulative results.

Quasi-In Situ Observation of the Microstructural Response during Fatigue Crack Growth of Friction Stir Welded AA2024-T4 Joint.

The reliability of friction stir welded joints is a critical concern, particularly given their potential applications in the aerospace manufacturing industry. This study offers a quasi-in situ observation of the microstructural response during fatigue crack growth (FCG) of a friction stir welded AA2024-T4 joint, aiming to correlate fatigue crack growth behavior with mechanical properties investigated using electron backscatter diffraction (EBSD). Notched compact tension (CT) specimens corresponding to the morphology of the stir zone (SZ), advancing side (AS), and retreating side (RS) were meticulously designed. The findings indicate that the welding process enhances the joint's resistance to fatigue crack growth, with the base metal exhibiting a shorter fatigue life (i.e., ~105 cycles) compared to the welding zones (SZ ~ 3.5 × 105 cycles, AS ~ 2.5 × 105 cycles, and RS ~ 3.0 × 105 cycles). Crack propagation occurs within the stir zone, traversing refined grains, which primarily contribute to the highest fatigue life and lowest FCG rate. Additionally, cracks initiate in AS and RS, subsequently expanding into the base metal. Moreover, the study reveals a significant release of residual strain at the joint, particularly notable in the Structural-CT-RS (Str-CT-RS) sample compared to the Str-CT-AS sample during the FCG process. Consequently, the FCG rate of Str-CT-AS is higher than that of Str-CT-RS. These findings have significant implications for improving the reliability and performance of aerospace components.

Surveillance of noise exposure level in industrial enterprises-Jiangsu Province, China, 2022.

Occupational noise exposure is the most prominent problem in industrial enterprises in Jiangsu Province. Since 2019, China has established the National Surveillance System for Occupational Hazards in the workplace to grasp the current occupational hazards in critical industries, including occupational noise. According to the Work Plan for Surveillance of Occupational Hazards in the Workplace (2022) issued by the National Health Commission of the People's Republic of China, the noise exposure level of 3,142 enterprises in our province was monitored, the median and interquartile range (IQR) were calculated, and the distribution of noise exposure level was described by industry classification, enterprise-scale and ownership type of the enterprise. The railway, shipping, aerospace, and other transportation equipment manufacturing industries exhibited the highest proportion (42.9%) of individual noise exposure levels exceeding 85 dB(A), followed by the motor vehicles manufacturing industry (36.4%). The proportion of individual noise exposure levels exceeding 85 dB(A) was higher in medium and small enterprises, with rates of 28.1 and 28.6%, respectively. The highest proportion of personal noise exposure levels exceeding 85 dB(A) was observed in Hong Kong, Macao and Taiwan investment enterprises (37.5%), followed by incorporated companies (34.6%) and limited liability companies (28.1%), the lowest was state-owned enterprises(15.5%). The areas with excessive noise are primarily concentrated in grinding, welding, machining, cutting, and other related operations, accounting for 61.2% of the total. Among these operations, grinding accounts for 29.8%. The highest environmental noise and individual noise intensity were found in sandblasting and grinding positions, with individual noise intensities of 115.5 dB(A) and 108.4 dB(A), respectively. The noise exposure risk is so high that cannot be ignored in the manufacturing industry, especially in Hong Kong, Macao, and Taiwan investment enterprises, incorporated companies and medium and small enterprises.

Empirical Modeling and Analysis of Process Parameters in Laser Beam Cutting Process

The research has been originated based on the persuasive applications of Lasers in the field of various engineering industries, i.e., Aerospace, Automobile, Electronic and Heavy manufacturing industries to machine a variety of metals and alloys. Out of all the machining processes available, Laser Beam Machining is considered to be the best one, because of the following advantages, i.e., quick material removal, non-contact, non-wearing tool, involves highly localized heat input to the work piece, reduces distortion, and offers no tool wear, diminishes tendency of cracking. The present paper focused mainly on developing the empirical relationships between the input process parameters and the output responses in Laser beam cutting process. Laser power, Cutting Speed, Gas pressure and Focal distance are the input process parameters. The output responses considered are related to the quality of cut. Surface roughness is the first output responses considered and the second one is Burr height. Total number of experiments carried out is 27 based on the Taguchi Design of Experiments. Haste alloy C276 is the work material. Response Surface Methodology is applied for the Experimental data of 31 samples to derive the empirical relationships. Later ANOVA analysis is also carried out to check the adequacy of the derived equations. Based on the ANOVA analysis, the models are classified as significant or not significant. Further the significant models can be used for optimizing the Laser beam cutting process. Once the process is optimized, it can be automated, so that the process can be run very efficiently and economically.

Study and analysis of the PFMEA approach for the aerospace manufacturing industries: evidence from aircraft manufacturers

Study and analysis of the PFMEA approach for the aerospace manufacturing industries: evidence from aircraft manufacturers

Application Research of Tool Stability Based on Bayesian Theory

Due to high precision requirements and high machining value, the high-end aerospace manufacturing industry has put forward higher requirements for the stability of machining tools. In this paper, the Bayesian algorithm is used to obtain sample information through experiments, and the sample information and prior information are effectively fused to estimate the parameters. Finally, the stability of a domestic blade can be improved by 8.76%.

Enhancing the strength of Sc-containing Al-Cu-Li alloys by modifying the precipitation behavior through plastic deformation and heat treatment

Al-Cu-Li alloys are used extensively in the aerospace manufacturing industry for their outstanding properties, however, the addition of trace Sc elements will form high-temperature insoluble (Cu, Sc)-containing phases during homogenization leads to a decrease in age-strengthening, and there is a limited investigation on how to overcome this unfavorable factor. In this work, the effects of plastic deformation coupled with heat treatment on the microstructure and mechanical properties of Sc-containing Al-Cu-Li alloy were systematically investigated by using age-hardening curves and room-temperature tensile tests combined with characterization by TEM, EBSD, and SEM/EDS. The results show that plastic deformation before high-temperature treatment fragments and promotes the dissolution of coarse phases, reduces the development of (Cu, Sc)-containing enriched phases, and simultaneously increases the content of Cu atoms within the Al matrix. Among all precipitates (GPB zones, S phases, T1 phases) after T6 aging, T1 phases act as the dominant strengthening phase of the alloy. At the same time, we found that the decrease in the Cu-containing residual phase after solid solution treatment will result in a remarkably increasing number density and volume fraction of T1 phases at the peak aging. In a word, we obtain a good strength-ductility trade-off (the yield strength is ∼500 MPa while maintaining ∼10% elongation) Al-Cu-Li alloy with Sc element by optimizing the distribution of Cu elements and modulating the aging precipitation behavior. Our proposed process is expected to provide an experimental and theoretical guide toward the development of Al-Cu-Li alloys with superior properties.

Optimisation of laser welding parameters to maximise the joint strength of laser weld stainless steel joints using a GA for geothermal plants

ABSTRACTLaser beam welding is vital in high-temperature fields such as the aerospace, automobile, and gas turbine manufacturing industries. In this article, parametric studies are carried out on Nd:YAG laser weldments that influence stainless steel 430 L weldment quality. A series of trial runs are organised to investigate input parameters such as peak power, frequency, speed, and time that impact output responses such as yield strength, ultimate tensile strength, shear strength, and elongation simultaneously. Trail runs on martensitic stainless steel AISI 430 L are conducted based on Taguchi experiments, and a regression equation is established. To yield optimum results, the process parameters are optimised by using the genetic algorithm optimisation technique. By conducting experimentation with optimum parameters, the output responses are compared with the optimum results 95% confidence level was obtained. The optimum levels for process variables are identified for quality weld peak power 160 kW, frequency 9 Hz, speed 3.33 mm/ms, and time 2.53 ms. Optical microscopy reveals that refined grains are formed in the weld zone with a grain size of 2.909 µm, and a scanning electron microscopy test is performed to study the morphology of AISI 430 L weldment specimen failure takes place at the interface of the weld metal.

A Literature Review on The Evaluation and Improvement of The International Competitiveness of China's Aerospace Manufacturing Industry

Taking the international competitiveness of China's aerospace manufacturing industry as the research object (Hereinafter abbreviated as IC-AMI), this paper classifies and sorts out the relevant literature of industrial international competitiveness, China's aerospace manufacturing industry and China’s IC-AMI, and believes that the existing research still has expandable potential. First of all, no scholar has yet conducted a quantitative analysis of the factors influencing China’s IC-AMI. Second, there is a lack of international competitiveness assessment of China's aerospace manufacturing industry based on horizontal comparison. Finally, no scholars have used data from 2008 to study China's IC-AMI.

Photothermal NDE of UD/Epoxy-Based Carbon Fibre Reinforced Laminates for Quantitative Porosity Analysis

High strength and low density make epoxy-based CFRP a highly interesting construction material for the aerospace manufacturing industry. Porosity represents an unavoidable defect and significantly weakens strength values dominated by the matrix. To evaluate the quality of safety-relevant components, non-destructive evaluation and thus the characterization of porous structures is indispensable. Pulsed thermography represents a fast, large-area and non-contact testing method that enables efficient estimation of material parameters. In this work, the authors demonstrate the quantitative estimation of porosity by pulsed thermography on a multi-axial laminate fabricated from unidirectional Prepregs for the first time. The characteristic, extensive expansion of the pores in fiber direction, is addressed by the 3D microstructure characterization of Cone beam X-ray computed tomography data. Hence, the application of effective medium theories and thus the model based porosity estimation is enabled. After the investigation of the effect of pore expansion on the effective thermal diffusivity in 3D finite element simulations, the quantitative photothermal porosity estimation on a sample with a global volume porosity of Phi =1.51% is demonstrated. The accuracy of this fast and non-contact method for porosity estimation with pulsed thermography (Delta Phi =0.63%) is comparable to the standard ultrasonic method. Consequently, an efficient estimation of porosity for large, complex shaped UD/Epoxy composite components is enabled.

Study on the Mechanism and Countermeasures of Digital Transformation Affecting Enterprise Performance in Xi'an Aerospace Manufacturing Industry

Study on the Mechanism and Countermeasures of Digital Transformation Affecting Enterprise Performance in Xi'an Aerospace Manufacturing Industry

SUSTAINING COMPETITIVE ADVANTAGE DURING COVID-19 PANDEMIC: A PRELIMINARY CASE STUDY OF AEROSPACE MANUFACTURING INDUSTRY IN MALAYSIA

The coronavirus (Covid-19) hits the world at a stage where companies plans are affected due to unplanned business disruptions and operations and the aerospace manufacturing industry is one of the industries that was hit severely. This paper is a preliminary attempt to investigate the impact of COVID-19 on the competitive advantage of one of the aerospace manufacturing companies as a case study. Through a comprehensive literature study and survey, this paper presents an interpretation of competitive advantage theory where the research framework presents the impact of internal and external influences on a company’s competitive advantage and whether strategic management mediates the impact. It illustrates the general concepts and development of hypotheses using the internal and external influences and strategic management. Quantitative analysis using survey will be used to collect and analysis of data from 30 leaders and executives that have been chosen for this study using PLS SEM. It is expected that this study will present a guide that illustrates how theories, general concepts and processes can be managed, allowing strategic management personnel to understand their market position and, from there, identify where the future direction.

Investigation report of aero engine air die hole processing

At present, there are a variety of problems in the aerospace manufacturing industry, especially the machining of aero-engine air film holes. In this paper, by investigating the current research status of aero-engine gas film hole machining at home and abroad, the characteristics and difficulties of the current gas film hole machining are introduced, and the comparison between ordinary laser machining and femtosecond laser machining is made.

An artificial neural network and Taguchi prediction on wear characteristics of Kenaf–Kevlar fabric reinforced hybrid polyester composites

AbstractFiber‐reinforced composites have found their prominent place in various applications, including aerospace, automobile and marine manufacturing industries, because of outstanding properties obtained during composite preparation. One such aspect of improving the composite property is hybridization, where natural fibers (or both natural and synthetic fibers) are combined to obtain different composite structures for diverse applications. This research aims to hybridize the composite considering Kenaf fabric and Kevlar fabric reinforced in an unsaturated polyester matrix with different proportions. Three different laminate sequences (L1, L2, and L3) were developed by considering the fabric's stacking sequence, weave pattern, and orientation. The composite laminates prepared were tested where Taguchi's method (L9 orthogonal array) and artificial neural network were used to study influencing parameters for tribological behavior of the composite. From the practical information, a prediction model from the artificial neural network is applied to forecast the wear rate of the laminates at a broader range of operating factors beyond and within the test phase. The microstructures of the worn surfaces were investigated from a scanning electron microscope to confirm the wear principle of the laminates under different cases.

Analysis on wear patterns and mechanisms of carbide tool for face-hobbing of spiral bevel gear

Spiral bevel gear is widely used in the automotive and aerospace manufacturing industries, and the machining process is complex and the material is difficult to cut. The characteristics of high hardness, strong chemical reactivity and poor heat dissipation make the machinability of 20CrMnTi poor for face-hobbing machining of spiral bevel gear. In the process of cutting, there are some problems such as severe tool wear, poor machining quality and low machining efficiency caused by higher cutting force and higher cutting temperature. Therefore, it is necessary to study and analyze the wear experiment of the cutting tools of spiral bevel gear for face-hobbing deeply. Firstly, under the single factor experimental conditions, the wear patterns of inside blade and outside blade are observed and analyzed at different rotational speeds, and the tool wear conditions are detected and measured analysis. Secondly, the tool wear morphology and element distribution of rake face and flank face of inside blade and outside blade are analyzed by scanning electron microscope and energy spectrometer, and the tool wear mechanism for face-hobbing of spiral bevel gear is discussed in depth. The results demonstrate that chipping and fracture are the main patterns of tool wear; the tool wear mechanism are mainly embodied in adhesive wear, diffusion wear and oxidation wear. The tool wear is mainly distributed on the main cutting edge, top edge and corner radius, and the top edge and corner radius are more seriously worn. The research results can provide an effective basis for exploring the tool wear mechanism and improving the tool life, and provide technical support for the design and development of gear machining tools.

Closed-loop shot peen forming with in-process measurement and optimization

Shot peen forming is relied upon in the aerospace manufacturing industry to form thin metal panels into complex geometries. The accuracy and repeatability of the process depend on the initial stress state of the part. The measurement of residual stresses being costly or destructive leaves the field in want of a more efficient method to produce accurate parts. This work proposes a closed-loop method, based on in-process measurements, a finite element model, and optimization to reduce shot peen forming errors by iterative replanning. We demonstrate in an experimental test case of three sample plates that the proposed method can reduce the forming error below 0.2 mm, while the standard open-loop planning yielded errors from 0.333 mm to 0.667 mm, for samples of 1.04 mm thickness.

An IoT platform for production monitoring in the aerospace manufacturing industry

The current evolution and availability of IoT and CPS technologies is fostering a new industrial revolution, where manufacturing technologies and processes are leveraged by intelligent automation, data exchange and ubiquitous connectivity. In this context, enhancing the control and monitoring of production lines is of particular interest as a crucial management step regarding smart manufacturing and product delivery.Focusing on the demanding field of aerospace industry, the present work proposes an IoT-based solution for improving the quality of monitoring data assisting the production and assembly processes. The proposed architecture prototype integrates: (i) components to extend the manufacturing execution systems (MES); (ii) components of a scalable IoT platform; (iii) components for integrating and analysing production line data; and (iv) a new data visualisation application to assist production control. Aspects such as gathering detailed production data and measuring time per stage along the production lines are provided for controlling and optimising productivity, avoiding potential errors resulting from human-based monitoring methods. Consequently, the proposed solution contributes for a better management of production resources, enabling reduced production time, faster and more informed responses, and enhanced control over the production processes in general.

Laser Powder Bed Fusion of Aluminium Alloy 6061 for Ultra-High Vacuum Applications

As additive techniques such as laser powder bed fusion find increasing adoption industry, the ability to adapt these processes to industrially relevant materials is paramount. This adaptation can represent a significant challenge when working with wrought alloy feedstocks, which often result in brittle or porous parts lacking the mechanical properties of their conventionally wrought counterparts. One such alloy, aluminium 6061, is a highly used alloy in the aerospace, automotive, and semiconductor manufacturing industries. The conventionally manufactured components can have complex morphologies and may be assemblies of multiple individual components. As such, the ability to use an additive approach, and produce these as single parts can lead to significant benefits.In this work, we examine laser powder bed fusion of aluminium alloy 6061. The effects of process parameters such as laser power, beam scan speed, hatching distance, spot size was examined with a view towards developing an optimised process for this traditionally wrought alloy. Parts were examined for porosity and microstructure, with an aim to develop greater than 95% relative densities. To aid in process optimisation, in-situ pyrometry was deployed to understand the effects of the process parameters and develop a robust and repeatable process for producing 6061 components.

Microstructure and mechanical properties of ultra-high strength Al-Zn-Mg-Cu-Sc aluminum alloy fabricated by wire + arc additive manufacturing

Ultra-high strength 7xxx series aluminum alloys are widely used in aerospace applications due to their exceptional high specific strength. Wire + Arc Additive Manufacturing (WAAM) is a combination of arc and wire feeding additive manufacturing technology including either the gas tungsten arc (GTA) or the gas metal arc (GMA) process. And this technology has been applied in the aerospace manufacturing industry to reduce the time of product development and “buy-to-fly” ratios. However, the existing Al-Zn-Mg-Cu aluminum alloy filler wires are not suitable for WAAM process due to their high susceptibility to hot cracks. In this study, a novel Al-Zn-Mg-Cu-Sc aluminum alloy wire named 7A55-Sc with ultra-high strength and excellent hot-crack resistance has been successfully prepared by optimizing the composition of Al-Zn-Mg-Cu alloying elements and adding appropriate amounts of inoculants Sc and Zr elements during the smelting process. And then, thin-wall components without any hot cracks were successfully fabricated by using cold metal transfer (CMT) process. Results indicated that the microstructure of the as-deposited 7A55-Sc alloy consists of predominantly fine equiaxed grains and the average size of the grains is between 5.0 and 6.0 μm. The eutectics composed of α (Al), η phase and S phase were distributed along the grain boundaries. The Al3Sc and Al3 (Zr, Sc) particles precipitated within grains act as heterogeneous nucleation nuclei, promoting the formation of the equiaxed grains. After T6 heat treatment, most of the second phases distributed within grains and grain boundaries were dissolved into the α(Al) matrix. The distribution of alloy elements became more homogeneous. The average ultimate tensile strength, yield strength and elongation of T6 heat-treated 7A55-Sc alloy in the horizontal direction were 554 MPa, 488 MPa and 1.7% respectively, whereas 523 MPa, 469 MPa and 1.4% in the vertical direction. The lower ductility was considered due to the existence of a large number of pores in the 7A55-Sc alloy fabricated by the CMT process.