scholarly journals Multiphysics Modeling and Numerical Simulation in Computer-Aided Manufacturing Processes

Metals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 175
Author(s):  
Tomasz Trzepieciński ◽  
Francesco dell’Isola ◽  
Hirpa G. Lemu
Keyword(s):  
Industry 4.0 ◽  
Physical World ◽  
Intelligent Manufacturing ◽  
Manufacturing Processes ◽  
Computer Aided Manufacturing ◽  
Multi Scale ◽  
Current State ◽  
Common Term ◽  
Computer Aided ◽  
Manufacturing Techniques

The concept of Industry 4.0 is defined as a common term for technology and the concept of new digital tools to optimize the manufacturing process. Within this framework of modular smart factories, cyber-physical systems monitor physical processes creating a virtual copy of the physical world and making decentralized decisions. This article presents a review of the literature on virtual methods of computer-aided manufacturing processes. Numerical modeling is used to predict stress and temperature distribution, springback, material flow, and prediction of phase transformations, as well as for determining forming forces and the locations of potential wrinkling and cracking. The scope of the review has been limited to the last ten years, with an emphasis on the current state of knowledge. Intelligent production driven by the concept of Industry 4.0 and the demand for high-quality equipment in the aerospace and automotive industries forces the development of manufacturing techniques to progress towards intelligent manufacturing and ecological production. Multi-scale approaches that tend to move from macro- to micro- parameters become very important in numerical optimization programs. The software requirements for optimizing a fully coupled thermo-mechanical microstructure then increase rapidly. The highly advanced simulation programs based on our knowledge of physical and mechanical phenomena occurring in non-homogeneous materials allow a significant acceleration of the introduction of new products and the optimization of existing processes.

scholarly journals Editorial for the Special Issue: Computer-Aided Manufacturing and Design

2020 ◽  
Vol 10 (16) ◽  
pp. 5650
Author(s):  
Qi Zhou ◽  
Seung-Kyum Choi ◽  
Recep M. Gorguluarslan
Keyword(s):  
Production Process ◽  
Computer Technology ◽  
Integrated Design ◽  
Manufacturing Processes ◽  
Special Issue ◽  
Direct Control ◽  
Computer Aided Manufacturing ◽  
Computer Aided ◽  
Design And Manufacturing ◽  
Computer Based

Recent advancements in computer technology have allowed designers to have direct control over the production process through the help of computer-based tools, creating the possibility of completely integrated design and manufacturing processes [...]

Misfit evaluation of dental implant-supported metal frameworks manufactured with different techniques: Photoelastic and strain gauge measurements

2016 ◽  
Vol 230 (12) ◽  
pp. 1106-1116 ◽  
Author(s):  
Roberto Montanini ◽  
Michele Scafidi ◽  
Giorgio Staiti ◽  
Antonia Marcianò ◽  
Leonardo D’Acquisto ◽  
...  
Keyword(s):  
Computer Aided Design ◽  
Cost Benefit ◽  
Resin Cement ◽  
Computer Aided Manufacturing ◽  
Significant Difference ◽  
Computer Aided ◽  
Manufacturing Techniques ◽  
Aided Design ◽  
Supported Metal

This study aims to compare in-vitro the fitting accuracy of implant-supported metal frameworks used for full-arch orthodontic restoration. The hypotheses tested were as follows: (1) for a fixed implant morphology, strains developed within the framework depend on how the framework had been fabricated and (2) stresses transferred to the implant–bone interface are related to the amount of framework misfit. Metal frameworks were fabricated using four different manufacturing techniques: conventional lost-wax casting, resin cement luting, electrospark erosion, and computer-aided design/computer-aided manufacturing milling. Each framework was instrumented with three strain gauges to measure strains developed because of prosthetic misfit, while quantitative photoelastic analysis was used to assess the effect of misfit at the implant–resin interface. All the tested frameworks presented stress polarization around the fixtures. After screw tightening, significantly greater strains were observed in the lost-wax superstructure, while the lowest strains were observed in the luted framework, demonstrating consistent adaptation and passive fitting. No significant difference in stress distribution and marginal fit was found for bars fabricated by either computer-aided design/computer-aided manufacturing or spark erosion. This study suggested that, in spite of known limitations of in-vitro testing, direct luting of mesostructures and abutments should be the first clinical option for the treatment of complete edentulism, ensuring consistent passive fitting and effective cost–benefit ratio.

scholarly journals Introduction to Intelligent Quality Management

2020 ◽  
Author(s):  
Ercan Oztemel
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Intelligent Manufacturing ◽  
General Information ◽  
Manufacturing Processes ◽  
Intelligent Manufacturing Systems ◽  
Industrial Operations ◽  
Control And Management ◽  
Industrial Societies ◽  
Rapid Transformation

Intelligent manufacturing is becoming more and more attractive for industrial societies especially after the introduction of industry 4.0 where most of industrial operations are to be carried by robots equipped with intelligent capabilities. This explicitly implies that the manufacturing systems will entirely be integrated and all manufacturing functions including quality control and management will have to be made as much intelligent as possible in operating with minimum human intervention. This Chapter will present a brief overview of some implications about intelligent quality systems. It intends to provide the readers of the book to understand how the concept of artificial intelligence is to be embedded into quality functions. It is known that the interoperability is the rapid transformation requirement of industry specific operations. This requires the integration of quality functions to other manufacturing functions for sharing the quality related knowledge with other manufacturing functions in order to sustain total intelligent collaboration. Achieving this, on the other hand, ensures the improvement of manufacturing processes for better performance in an integrated manner. Note that, although some general information about intelligent manufacturing systems are given, this chapter is particularly focused on discussing intelligent quality related issues.

scholarly journals Computer aided manufacturing of compression garments used for rehabilitation of burn and post-operative scars

Mechanik ◽  
2019 ◽  
Vol 92 (1) ◽  
pp. 55-57
Author(s):  
Michał Karpiuk ◽  
Maciej Malik ◽  
Magdalena Przytocka ◽  
Katarzyna Czajkowska-Sabat ◽  
Witold Sujka
Keyword(s):  
3D Scanning ◽  
Manufacturing Processes ◽  
Control Parameters ◽  
Computer Aided Manufacturing ◽  
Compression Garments ◽  
Stl File ◽  
Cutting Machine ◽  
Computer Aided

The article describes a computer-aided manufacturing of compression garments used for rehabilitation of burn and post-operative scars implemented in Tricomed S.A company. Steps of manufacturing processes include 3D scanning, obtaining control parameters for a self-generating CAD templates from STL file, conversion control parameters depending on the degree of compression and type of knitwear, generating DXF files for the cutting machine, sewing.

Biomedical Manufacturing: A Review of the Emerging Research and Applications

2020 ◽  
Vol 142 (11) ◽  
Author(s):  
Roland Chen ◽  
Robert C. Chang ◽  
Bruce Tai ◽  
Yong Huang ◽  
Burak Ozdoganlar ◽  
...  
Keyword(s):  
Healthcare Services ◽  
Research Area ◽  
Future Research ◽  
Manufacturing Processes ◽  
Quality Cost ◽  
Multi Scale ◽  
Research Activities ◽  
Current State ◽  
Integral Role ◽  
Comprehensive Survey

Abstract Biomedical manufacturing, which has seen rapid growth over the past decade, is an emerging research area for the manufacturing community. This growth trajectory is exemplified and coupled with a broadening scope of applications with biomedical manufacturing technology, including advancements in the safety, quality, cost, efficiency, and speed of healthcare service and research. The goal of this topical review is to offer a comprehensive survey of the current state-of-the-art in biomedical manufacturing and to summarize existing opportunities and challenges as a basis to guide future research activities in this emerging area. This article categorizes the key manufacturing process types that are currently being leveraged for the biomedical field of use, including machining, joining, additive manufacturing, and micro-/multi-scale manufacturing. For each of these manufacturing processes, notable applications are cited and discussed to provide insights and perspectives into how manufacturing processes can play an integral role in creating new and more sophisticated healthcare services and products.

scholarly journals Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6783
Author(s):  
Tahera Kalsoom ◽  
Naeem Ramzan ◽  
Shehzad Ahmed ◽  
Masood Ur-Rehman
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Low Cost ◽  
Intelligent Manufacturing ◽  
Smart Factory ◽  
Future Research ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Different Types ◽  
Smart Factories

The evolution of intelligent manufacturing has had a profound and lasting effect on the future of global manufacturing. Industry 4.0 based smart factories merge physical and cyber technologies, making the involved technologies more intricate and accurate; improving the performance, quality, controllability, management, and transparency of manufacturing processes in the era of the internet-of-things (IoT). Advanced low-cost sensor technologies are essential for gathering data and utilizing it for effective performance by manufacturing companies and supply chains. Different types of low power/low cost sensors allow for greatly expanded data collection on different devices across the manufacturing processes. While a lot of research has been carried out with a focus on analyzing the performance, processes, and implementation of smart factories, most firms still lack in-depth insight into the difference between traditional and smart factory systems, as well as the wide set of different sensor technologies associated with Industry 4.0. This paper identifies the different available sensor technologies of Industry 4.0, and identifies the differences between traditional and smart factories. In addition, this paper reviews existing research that has been done on the smart factory; and therefore provides a broad overview of the extant literature on smart factories, summarizes the variations between traditional and smart factories, outlines different types of sensors used in a smart factory, and creates an agenda for future research that encompasses the vigorous evolution of Industry 4.0 based smart factories.

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