The Applications of Ultra-Thin Nanofilm for Aerospace Advanced Manufacturing Technology

With the development of industrial civilization, advanced manufacturing technology has attracted widespread concern, including in the aerospace industry. In this paper, we report the applications of ultra-thin atomic layer deposition nanofilm in the advanced aerospace manufacturing industry, including aluminum anti-oxidation and secondary electron suppression, which are critical in high-power and miniaturization development. The compact and uniform aluminum oxide film, which is formed by thermal atomic layer deposition (ALD), can prevent the deep surface oxidation of aluminum during storage, avoiding the waste of material and energy in repetitive production. The total secondary electron yield of the C/TiN component nanofilm, deposited through plasma-enhanced atomic layer deposition, decreases 25% compared with an uncoated surface. The suppression of secondary electron emission is of great importance in solving the multipactor for high-power microwave components in space. Moreover, the controllable, ultra-thin uniform composite nanofilm can be deposited directly on the complex surface of devices without any transfer process, which is critical for many different applications. The ALD nanofilm shows potential for promoting system performance and resource consumption in the advanced aerospace manufacturing industry.

Ergonomic Risk Reduction Method in Aerospace Manufacturing

In the aerospace manufacturing, lots of processes cannot be automated and are performed manually by skilled workers. Because there exist some human error mistakes in such manual working processes, root cause investigations of these mistakes are indispensable and measures are implemented in working processes for preventing repetition of the same mistakes. Although skilled workers have strong confidence that they can complete their work with no mistake, there exist some cases that they cannot recognize their mistakes in practice. In such cases, root cause investigations cannot be performed and no measure is implemented. Such situation may become a serious risk in aerospace manufacturing because a tiny mistake can cause the serious mission failure of aviation system. To reduce such situation, the ergonomic risk reduction method is proposed. Skilled workers try to avoid frustration in performing their tasks and make mistakes through careless behavior. The cause of the frustration is discovered by ergonomic risk reduction method. Work risks can be removed by the progress of the working environment. Such risk reduction method contributes manufacturing organization resiliency. In this paper, we propose an ergonomic human error risk reduction method for skilled workers in Japanese domestic liquid rocket engine manufacturing.

Unfolding the Linkage Between SCM Practices and Customer Responsiveness in Indian Automotive and Aerospace Manufacturing Firms

The study examines how the supply chain management (SCM) practices impact customer responsiveness, and the same has been tested empirically with the help of a conceptual framework based on a literature review. Previous studies on the relationship between supply chain variables and competitive advantage have been presented earlier with variables including customer satisfaction, quality and flexibility. Still, there is a shortage of literature on customer responsiveness. This study attempts to conduct a structured study well supported by the existing literature to establish the mentioned linkage. The study sample includes 433 employees from 10 Indian automobile and aerospace manufacturing organizations, and the responses have been analysed with structural equation modelling (SEM) and bivariate regression. The study establishes the linkage between SCM practices and customer responsiveness. The results infer that supply chain practices are antecedents to customer responsiveness. The study has also scrutinized the specific items of SCM practices construct that highly influences customer responsiveness. This study also highlights and identifies the research on the linkage between SCM practices and customer responsiveness in the Indian context. For practitioners, this study offers advice for effective policymaking to have more excellent customer responsiveness by concentrating on the specific elements of each SCM practice.

State Monitoring Method for Tool Wear in Aerospace Manufacturing Processes Based on a Convolutional Neural Network (CNN)

In the aerospace manufacturing field, tool conditions are essential to ensure the production quality for aerospace parts and reduce processing failures. Therefore, it is extremely necessary to develop a suitable tool condition monitoring method. Thus, we propose a tool wear process state monitoring method for aerospace manufacturing processes based on convolutional neural networks to recognize intermediate abnormal states in multi-stage processes. There are two innovations and advantages of the proposed approach: one is that the criteria for judging abnormal conditions are extended, which is more useful for practical application. The other is that the proposed approach solved the influence of feature-to-recognition stability. Firstly, the tool wear level was divided into different state modes according to the probability density interval based on the kernel density estimation (KDE), and the corresponding state modes were connected to obtain the point-to-point control limit. Then, the state recognition model based on a convolutional neural network (CNN) was developed, and the sensitivity of the monitoring window was considered in the model. Finally, open-source datasets were used to verify the feasibility of the proposed method, and the results demonstrated the applicability of the proposed method in practice for tool condition monitoring.

Data-Driven Analysis of Friction Stir Welding for Aerospace Applications

Industry 4.0 and the digitalization of the manufacturing processes have brought new opportunities and strategies for process control and optimization. Friction Stir Welding is becoming a relevant manufacturing technology for several applications, among them the aerospace sector. This work presents the first data analysis and characterization of the Friction Stir Welding process of the Pre-Final Assembly Line of the new Ariane 6 launcher. Process monitoring data is captured and analyzed to provide predictive quality solutions for improving manufacturing key performance indicators and bring smart manufacturing and Industry 4.0 digitalization into the aerospace manufacturing sector. The results show promising performance for abnormal behavior detection, leveraging on a tailored data manipulation approach for this unique use case.

Autonomous Mobile Robots in High Occupancy Aerospace Manufacturing

Using a combination of active Radio-Frequency Identification tracking and staff interviews with members from an aerospace manufacturing company, it was uncovered that over 80 hours per week was spent in the manual movement of goods between departments. On a site of over 1000 employees that uses dedicated build cells in separated departments, this mixed-use facility proves challenging for the adoption of an autonomous delivery system due to its narrow corridors and high occupancy, however by investigating the concerns of employees and suggesting low-cost retroactive solutions, this project seeks to justify the transition from manual to automated onsite logistics. The conclusion found that indeed the company does have the transport yields to justify the use of Autonomous Mobile Robots, that the robots would supplement rather than replace workers and that safety was a key factor to address when using robots on a site of this configuration.

Collaborative approach to digital transformation (CADT) model for manufacturing SMEs

PurposeThis paper aims to propose a collaborative approach model developed based on observations of two aerospace manufacturing small and medium-sized enterprises (SMEs) pursuing their digital transformation toward Industry 4.0.Design/methodology/approachThis research focuses on two manufacturing SMEs in North America, and data were collected using longitudinal case study and research intervention method. Data collection was performed through observation and intervention within the collaborative projects over 18 months.FindingsA model of a collaborative approach to digital transformation (CADT) for manufacturing SMEs was produced. Based on the study findings, the collaboration manifests itself at various stages of the transformation projects, such as the business needs alignment, project portfolio creation, technology solution selection and post-mortem phase.Research limitations/implicationsResearch using the case study method has a limitation in the generalization of the model. The CADT model generated in this study might be specific to the aerospace manufacturing industry and collaboration patterns between manufacturing SMEs. The results could vary in different contexts.Practical implicationsThe proposed CADT model is particularly relevant for manufacturing SMEs' managers and consultants working on digital transformation projects. By adopting this approach, they could better plan and guide their collaboration approach during their Industry 4.0 transformation.Originality/valueThis research provides a new perspective to digital transformation approaches in the aerospace industry. It can be integrated into other research findings to formulate a more integrated and comprehensive CADT model in industries where SMEs are significant players.

Automated Robotic Systems for Nondestructive Testing of Aerospace Composite Structures

Automated robotic systems are becoming prevalent in many aerospace manufacturing applications, such as laser ablation, sanding, drilling, final assembly, and painting. There are significant advantages to using automated robotic systems for inspection purposes as well: versatility, speed, and repeatability, to name a few. This paper explores using an automated robotic system for the nondestructive testing (NDT) of composite parts. It has a focus on phased array ultrasonic testing (PAUT) but highlights modularity principles in the system that are not coupled to a single inspection method. Because of the articulation inherent in multi-axis robots, inspections of contoured structures become straightforward if the system modules are designed correctly. Examples of such modules, and their advantages when interfaced to an automated robotic system, are included in this paper. It is the author’s intent to show how these system modules might maximize robot capabilities for a broad range of aerospace inspections while keeping a simplistic design that is modular, fast, and straightforward to use. When compared to other aerospace manufacturing processes already using automated robotic systems, the use of robots for NDT seems not only prudent but a favorable goal. This paper offers practical building blocks for achieving this goal.