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Topic Review
Factors Related to Surface Roughness in Machining
Understanding surface roughness generation in machining is critical to estimate the final quality of the part, optimize cutting conditions, reduce costs and improve manufacturing sustainability in industry.
  • 64
  • 25 Mar 2024
Topic Review
Weld Pool Formation in Keyhole Plasma Arc Welding
The Keyhole Plasma Arc Welding (KPAW) process utilizes arc plasma highly constricted by a water-cooled cupper nozzle to produce great arc pressure for opening a keyhole in the weld pool, achieving full penetration to the thick plate. However, advanced control of welding is known to still be difficult due to the complexity of the process mechanism, in which thermal and dynamic interactions among the arc, keyhole, and weld pool are critically important. In KPAW, two large eddies are generally formed in the weld pool behind the keyhole by plasma shear force as the dominant driving force. These govern the heat transport process in the weld pool and have a strong influence on the weld pool formation process. The weld pool flow velocity is much faster than those of other welding processes such as Tungsten Inert Gas (TIG) welding and Gas Metal Arc (GMA) welding, enhancing the heat transport to lower the weld pool surface temperature. Since the strength and direction of this shear force strongly depend on the keyhole shape, it is possible to control the weld pool formation process by changing the keyhole shape by adjusting the torch design and operating parameters. If the lower eddy is relatively stronger, the heat transport to the bottom side increases and the penetration increases. However, burn-through is more likely to occur, and heat transport to the top side decreases, causing undercut. In order to realize further sophistication of KPAW, a deep theoretical understanding of the process mechanism is essential. 
  • 73
  • 21 Mar 2024
Topic Review
Machine Learning, Mechatronics, and Stretch Forming
The complexity of machine learning, mechatronics, and stretching forming is well known. Combining them was, is, and will be a necessity as they are closely interconnected disciplines within the field of manufacturing. It is a fact that in any industry, high productivity is achieved with the use of automated manufacturing processes. Intensive work was conducted throughout the year, and extraordinary techniques, equipment, and processes were upgraded or developed. Nevertheless, there are still issues that require optimal solutions.
  • 68
  • 18 Mar 2024
Topic Review
Industry 4.0 and Smart Manufacturing
The manufacturing industry often faces challenges related to customer satisfaction, system degradation, product sustainability, inventory, and operation management. If not addressed, these challenges can be substantially harmful and costly for the sustainability of manufacturing plants. Paradigms, e.g., Industry 4.0 and smart manufacturing, provide effective and innovative solutions, aiming at managing manufacturing operations, and controlling the quality of completed goods offered to the customers.
  • 80
  • 18 Mar 2024
Topic Review
Musical Instruments Made of Composites and Alternative Materials
The evolution of musical instrument manufacturing has been a dynamic process, with traditional materials such as wood playing a predominant role for centuries. However, the need for innovation in the musical industry has driven researchers and manufacturers to explore alternative materials that offer enhanced performance, sustainability, and versatility. The demand for different materials arises from various challenges faced by the musical instruments industry, including the lack of high-quality tonewoods, the significant variations in both mechanical and acoustical properties of wood internally within a single piece or across the same species, environmental concerns, and the quest for achieving specific acoustic properties. Composite materials, such as carbon- and graphite fiber-reinforced plastics (CFRPs and GFRPs), ceramic polymers, and nanocomposites, constitute promising alternatives that not only address these challenges, but also offer unique advantages in terms of durability, weight reduction, and customizable acoustic characteristics. 
  • 141
  • 14 Mar 2024
Topic Review
Crucial Technologies of Digital Thread Implementation
The digital thread is identified as an integrated information flow using recognized authoritative data sources (e.g., requirements, system architecture, technical data packages (TDP), 3D CAD models) connecting all stages of the product lifecycle. The objective of the digital thread is to establish an integrated framework that consolidates all stages of the product lifecycle and systems, facilitating efficient and effective lifecycle measurements and supporting a data-driven approach.
  • 90
  • 11 Mar 2024
Topic Review
Fundamentals of Laser Shock Peening
With the rapid development of the advanced manufacturing industry, equipment requirements are becoming increasingly stringent. Since metallic materials often present failure problems resulting from wear due to extreme service conditions, researchers have developed various methods to improve their properties. Laser shock peening (LSP) is a highly efficacious mechanical surface modification technique utilized to enhance the microstructure of the near-surface layer of metallic materials, which improves mechanical properties such as wear resistance and solves failure problems.
  • 70
  • 29 Feb 2024
Topic Review
Machine Learning Design for High-Entropy Alloys
High-entropy alloys (HEAs) have attracted worldwide interest due to their excellent properties and vast compositional space for design. However, obtaining HEAs with low density and high properties through experimental trial-and-error methods results in low efficiency and high costs. Although high-throughput calculation (HTC) improves the design efficiency of HEAs, the accuracy of prediction is limited owing to the indirect correlation between the theoretical calculation values and performances. Machine learning (ML) from real data has attracted increasing attention to assist in material design, which is closely related to performance. 
  • 75
  • 29 Feb 2024
Topic Review Peer Reviewed
Smart Factories for Mass Individualization
With the rise of individualism as a social trend and the wide use of the Internet and social media, today’s customers increasingly want to design and build unique products that fit their individual preferences and needs. Mass individualization is defined as a manufacturing paradigm that aims to produce individualized products cost-effectively. This paradigm differs from the previous paradigms in which the manufacturing company designed and manufactured the products, and the customer chose a product. In the mass individualization paradigm, the customers will be actively involved in product design, and the manufacturer will produce a unique product for each customer at a reasonable cost and of reliable quality. Due to the need for smooth communication and interactions between the buyer and the factory, new factories for individualized products will be located near potential buyers, which will have a significant impact on local economies. This entry explores the relationship between mass individualization and other emerging manufacturing paradigms and concepts in the Industry 4.0/5.0 era, and discusses how smart factories can improve manufacturing efficiency and facilitate the realization of the mass individualization paradigm.
  • 321
  • 27 Feb 2024
Topic Review
Deep Learning for Automated Visual Inspection
This article evaluates the state of the art of deep-learning-based automated visual inspection in manufacturing and maintenance applications and contrasts it to academic research in the field of computer vision. By doing so itidentifies to what extent computer vision innovations are already being used and which potential improvements could be realized by further transferring promising concepts. Existing work is either focused on specific industry sectors or methodologies but not on industrial VI as a whole or is outdated by almost two decades. We surveyed 196 open access publications from 2010 to March 2023 from the fields of manufacturing and maintenance with no restriction regarding industries. Our main findings were: The vast majority of publications utilize supervised learning approaches on relatively small datasets with convolutional neural networks. The timegap between publication of new approaches in deep learning-based computer vision and its first application in industrial visual inspection is approximately three years First vision transformer models emerge in 2022 and seem to outperform established models but their excellent self-supervised learning capabilities are not explored to date
  • 100
  • 26 Feb 2024
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