Introduction to Advanced Manufacturing Processes and Optimization Methodologies

Author(s):  
Apoorva Shastri ◽  
Aniket Nargundkar ◽  
Anand J. Kulkarni
2020 ◽  
Vol 10 (19) ◽  
pp. 6856 ◽  
Author(s):  
Leandro Ruiz ◽  
Manuel Torres ◽  
Alejandro Gómez ◽  
Sebastián Díaz ◽  
José M. González ◽  
...  

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.


Author(s):  
Arvind Shankar Raman ◽  
Dustin Harper ◽  
Karl R. Haapala ◽  
Barbara S. Linke ◽  
William Z. Bernstein ◽  
...  

Abstract A workshop on Challenges in Representing Manufacturing Processes for Systematic Sustainability Assessments, jointly sponsored by the U.S. National Science Foundation, the U.S. National Institute of Standards and Technology, ASTM International, the American Society of Mechanical Engineers, and the Society of Manufacturing Engineers, was held in College Station, Texas on June 21, 2018. The goals of the workshop were to identify research needs supporting manufacturing process characterization, define limitations in associated education practices, and emphasize on challenges to be pursued by the advanced manufacturing research community. An important aspect surrounded the introduction and development of reusable abstractions of manufacturing processes (RAMP), which are standard representations of unit manufacturing processes to support the development of metrics, methods, and tools for the analysis of manufacturing processes and systems. This paper reports on the workshop activities and findings, which span the improvement of engineering education, the understanding of process physics and the influence of novel materials and manufacturing processes on energy and environmental impacts, and approaches for optimization and decision-making in the design of manufacturing systems. A nominal group technique was used to identify metrics, methods, and tools critical to advanced manufacturing industry as well as highlight the associated research challenges and barriers. Workshop outcomes provide a number of research directions that can be pursued to address the identified challenges and barriers.


Author(s):  
Francisco Brocal ◽  
Miguel A. Sebastián ◽  
Cristina González

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