Additive Manufacturing Systems for Medical Applications: Case Studies

2018 ◽  
pp. 187-209 ◽  
Author(s):  
Henrique Amorim Almeida ◽  
Ana Filipa Costa ◽  
Carina Ramos ◽  
Carlos Torres ◽  
Mauricio Minondo ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Case Studies ◽  
Manufacturing Systems ◽  
Medical Applications

scholarly journals Control architectures for Industrial Additive Manufacturing Systems

2017 ◽  
Vol 232 (10) ◽  
pp. 1767-1777 ◽  
Author(s):  
Daniel Eyers
Keyword(s):  
Additive Manufacturing ◽  
Case Studies ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Sustainable Manufacturing ◽  
Emergent Technologies ◽  
Explicit Consideration ◽  
Research Gap ◽  
Manufacturing Environments

As the emergent technologies of Industrial Additive Manufacturing become increasingly employed in commercial manufacturing environments, challenges arise in terms of how resources of the manufacturing system should be marshalled and controlled for sustainable manufacturing. While control architectures are well established for conventional manufacturing, to-date there has been little explicit consideration for Industrial Additive Manufacturing. This article provides redress for this research gap by exploring four feasible control architectures employed in current manufacturing practice. Drawing upon 12 case studies and the operations of three companies, the relative merits, demerits, and challenges for each architecture are explored in terms of changeability criteria for sustainable manufacturing.

scholarly journals MODEL-BASED DESIGN OF AM COMPONENTS TO ENABLE DECENTRALIZED DIGITAL MANUFACTURING SYSTEMS

2021 ◽  
Vol 1 ◽  
pp. 2127-2136
Author(s):  
Olivia Borgue ◽  
John Stavridis ◽  
Tomas Vannucci ◽  
Panagiotis Stavropoulos ◽  
Harry Bikas ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Data Generation ◽  
Production Networks ◽  
Model Based ◽  
Manufacturing Technologies ◽  
Am Processes ◽  
Final Consumer

AbstractAdditive manufacturing (AM) is a versatile technology that could add flexibility in manufacturing processes, whether implemented alone or along other technologies. This technology enables on-demand production and decentralized production networks, as production facilities can be located around the world to manufacture products closer to the final consumer (decentralized manufacturing). However, the wide adoption of additive manufacturing technologies is hindered by the lack of experience on its implementation, the lack of repeatability among different manufacturers and a lack of integrated production systems. The later, hinders the traceability and quality assurance of printed components and limits the understanding and data generation of the AM processes and parameters. In this article, a design strategy is proposed to integrate the different phases of the development process into a model-based design platform for decentralized manufacturing. This platform is aimed at facilitating data traceability and product repeatability among different AM machines. The strategy is illustrated with a case study where a car steering knuckle is manufactured in three different facilities in Sweden and Italy.

scholarly journals Design, Materials, and Extrusion-Based Additive Manufacturing in Circular Economy Contexts: From Waste to New Products

2021 ◽  
Vol 13 (13) ◽  
pp. 7269
Author(s):  
Alessia Romani ◽  
Valentina Rognoli ◽  
Marinella Levi
Keyword(s):  
Additive Manufacturing ◽  
Case Studies ◽  
Circular Economy ◽  
Academic Research ◽  
Design Strategies ◽  
Academic Context ◽  
Application Fields ◽  
Research And Design ◽  
Specific Contribution ◽  
New Strategies

The transition toward circular economy models has been progressively promoted in the last few years. Different disciplines and strategies may significantly support this change. Although the specific contribution derived from design, material science, and additive manufacturing is well-established, their interdisciplinary relationship in circular economy contexts is relatively unexplored. This paper aims to review the main case studies related to new circular economy models for waste valorization through extrusion-based additive manufacturing, circular materials, and new design strategies. The general patterns were investigated through a comprehensive analysis of 74 case studies from academic research and design practice in the last six-year period (2015–2021), focusing on the application fields, the 3D printing technologies, and the materials. Further considerations and future trends were then included by looking at the relevant funded projects and case studies of 2021. A broader number of applications, circular materials, and technologies were explored by the academic context, concerning the practice-based scenario linked to more consolidated fields. Thanks to the development of new strategies and experiential tools, academic research and practice can be linked to foster new opportunities to implement circular economy models.

Analysis for understanding and standardization of additive manufacturing processes

2021 ◽  
Author(s):  
Alexander Matschinski ◽  
Tim Osswald ◽  
Klaus Drechsler
Keyword(s):  
Additive Manufacturing ◽  
High Performance ◽  
Manufacturing Systems ◽  
Polymer Melt ◽  
Thermal Shrinkage ◽  
Target Component ◽  
Associated Functions ◽  
Cooling Mechanism ◽  
Characteristic Values ◽  
As Stress

The market segment of additive manufacturing is showing an annual growth of more than ten percent, with extrusion-based processes being the larger segment of the market. The scope of use is limited to secondary structures. Equipment manufacturers try to guarantee constant material characteristics by closed systems. The characteristic values are up to 50% below the ones from injection molding. The processing of high-performance polymers with reinforcing fibers is an additional challenge. Further development requires an opening of the material and manufacturing systems. The guidelines and standardization for this are still missing. For this reason, a functional analysis (FA) according to TRIZ ("theory of the resolution of invention-related tasks") is performed within this study. This identifies the undesired functions and quantifies their coupling with process components and parameters. In the FA, the manufactured part is the target component in order to address its quality. This way the FA identifies five undesirable functions in the process. These are: deform, cool, weaken, swell and shape. For hightemperature thermoplastics, thermal shrinkage is the primary cause of geometric tolerance. Therefore, the deformation is largely dependent on the cooling mechanism. For a detailed analysis, the polymer melt is further disassembled. The results are six sub-components. The weakening is mainly due to the physical phase of the voids, which exists during the entire processing. The breakdown comprises physical fields such as stress, temperature and flow. These determine the output properties as well as the bonding between the layers. The associated functions are the swelling and shaping. In order to generate broadly applicable standardizations, research questions for further investigation are derived from this study.

Fractal Pattern Recognition of Image Profiles for Manufacturing Process Monitoring and Control

2018 ◽  
Author(s):  
Farhad Imani ◽  
Bing Yao ◽  
Ruimin Chen ◽  
Prahalada Rao ◽  
Hui Yang
Keyword(s):  
Additive Manufacturing ◽  
Process Monitoring ◽  
Manufacturing Process ◽  
Manufacturing Systems ◽  
Experimental Studies ◽  
Precision Machining ◽  
Monitoring And Control ◽  
Process Monitoring And Control ◽  
Ultra Precision ◽  
And Control

Nowadays manufacturing industry faces increasing demands to customize products according to personal needs. This trend leads to a proliferation of complex product designs. To cope with this complexity, manufacturing systems are equipped with advanced sensing capabilities. However, traditional statistical process control methods are not concerned with the stream of in-process imaging data. Also, very little has been done to investigate nonlinearity, irregularity, and inhomogeneity in image stream collected from manufacturing processes. This paper presents the multifractal spectrum and lacunarity measures to characterize irregular and inhomogeneous patterns of image profiles, as well as detect the hidden dynamics of the underlying manufacturing process. Experimental studies show that the proposed method not only effectively characterizes the surface finishes for quality control of ultra-precision machining but also provides an effective model to link process parameters with fractal characteristics of in-process images acquired from additive manufacturing. This, in turn, will allow a swift response to processes changes and consequently reduce the number of defective products. The proposed fractal method has strong potentials to be applied for process monitoring and control in a variety of domains such as ultra-precision machining, additive manufacturing, and biomanufacturing.

Solid-Based Additive Manufacturing Systems

2021 ◽  
pp. 75-88
Author(s):  
G.K. Awari ◽  
C.S. Thorat ◽  
Vishwjeet Ambade ◽  
D.P. Kothari
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Systems
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