Use of additive manufacturing for polymer tooling: Case study from reaction injection molding

Author(s):  
Audun L. Storsanden ◽  
Marcus Vale ◽  
R. M. Chandima Ratnayake
2021 ◽  
Vol 1 ◽  
pp. 2127-2136
Author(s):  
Olivia Borgue ◽  
John Stavridis ◽  
Tomas Vannucci ◽  
Panagiotis Stavropoulos ◽  
Harry Bikas ◽  
...  

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.


2021 ◽  
Vol 11 (6) ◽  
pp. 2572
Author(s):  
Stefano Rosso ◽  
Federico Uriati ◽  
Luca Grigolato ◽  
Roberto Meneghello ◽  
Gianmaria Concheri ◽  
...  

Additive Manufacturing (AM) brought a revolution in parts design and production. It enables the possibility to obtain objects with complex geometries and to exploit structural optimization algorithms. Nevertheless, AM is far from being a mature technology and advances are still needed from different perspectives. Among these, the literature highlights the need of improving the frameworks that describe the design process and taking full advantage of the possibilities offered by AM. This work aims to propose a workflow for AM guiding the designer during the embodiment design phase, from the engineering requirements to the production of the final part. The main aspects are the optimization of the dimensions and the topology of the parts, to take into consideration functional and manufacturing requirements, and to validate the geometric model by computer-aided engineering software. Moreover, a case study dealing with the redesign of a piston rod is presented, in which the proposed workflow is adopted. Results show the effectiveness of the workflow when applied to cases in which structural optimization could bring an advantage in the design of a part and the pros and cons of the choices made during the design phases were highlighted.


2015 ◽  
Vol 137 (11) ◽  
Author(s):  
Kaci E. Madden ◽  
Ashish D. Deshpande

The field of rehabilitation robotics has emerged to address the growing desire to improve therapy modalities after neurological disorders, such as a stroke. For rehabilitation robots to be successful as clinical devices, a number of mechanical design challenges must be addressed, including ergonomic interactions, weight and size minimization, and cost–time optimization. We present additive manufacturing (AM) as a compelling solution to these challenges by demonstrating how the integration of AM into the development process of a hand exoskeleton leads to critical design improvements and substantially reduces prototyping cost and time.


2021 ◽  
Author(s):  
Heena Noh ◽  
Kijung Park ◽  
Kiwon Park ◽  
Gül E. Okudan Kremer

Abstract Traditional plaster casts often cause dermatitis due to disadvantages in usability and wearability. Additive manufacturing (AM) can fabricate customized casts to have light-weight, high strength, and better air permeability. Although existing studies have provided design for additive manufacturing (DfAM) guidelines to facilitate design applications for AM, most relevant studies focused on the mechanical properties of outputs and too general/specific design guidelines; novice designers may still have difficulty understanding trade-offs between functional and operational performance of various DfAM aspects for medical casts. As a response, this study proposes a DfAM worksheet for medical casts to effectively guide novice designers. First, important DfAM criteria and their possible solutions for medical casts are examined through a literature review to construct a basic DfAM framework for medical casts. Next, a scoring system that considers relative criteria importance and criteria evaluation from both functional and operational perspectives is developed to identify the overall suitability of a medical cast design for AM. A case study of finger cast designs was performed to identify the DfAM performance of the sample designs along with redesign requirements suggested by the worksheet. The proposed worksheet would be used to achieve rapid medical cast design by objectively assessing its suitability for AM.


Author(s):  
Yuanbin Wang ◽  
Robert Blache ◽  
Xun Xu

Additive manufacturing (AM) has experienced a phenomenal expansion in recent years and new technologies and materials rapidly emerge in the market. Design for Additive Manufacturing (DfAM) becomes more and more important to take full advantage of the capabilities provided by AM. However, most people still have limited knowledge to make informed decisions in the design stage. Therefore, an interactive DfAM system in the cloud platform is proposed to enable people sharing the knowledge in this field and guide the designers to utilize AM efficiently. There are two major modules in the system, decision support module and knowledge management module. A case study is presented to illustrate how this system can help the designers understand the capabilities of AM processes and make rational decisions.


2018 ◽  
Vol 8 (7) ◽  
pp. 1200 ◽  
Author(s):  
Alfonso González ◽  
David Salgado ◽  
Lorenzo García Moruno ◽  
Alonso Sánchez Ríos

A study was carried out with 135 surgeons to obtain a surgical laparoscopic grasper handle design that adapts to the size of each surgeon’s hand, in a functionally appropriate way, and has the sufficient ergonomics to avoid generating the problems detected nowadays. The main conclusion of the work is the practical 3D parametric design obtained for a laparoscopic surgical graspers handle that is scalable to fit each particular surgeon's hand size. In addition, it has been possible to determine that the anthropometric measure of the surgeon's hand defined as Palm Length Measured (PLM) allows the design of the 3D parametric model of the surgical handle to be conveniently scaled. The results show that both additive manufacturing and the application of ergonomics criterion provide an efficient method for the custom design and manufacture of this type of specialised tool, with potential application in other sectors.


2018 ◽  
Vol 24 (7) ◽  
pp. 1178-1192 ◽  
Author(s):  
Siavash H. Khajavi ◽  
Jan Holmström ◽  
Jouni Partanen

PurposeInnovative startups have begun a trend using laser sintering (LS) technology patents expiration, namely, by introducing LS additive manufacturing (AM) machines that can overcome utilization barriers, such as the costliness of machines and productivity limitation. The recent rise of this trend has led the authors to investigate this new class of machines in novel settings, including hub configuration. There are various supply chain configurations to supply spare parts in industrial operations. This paper aims to explore the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it.Design/methodology/approachThis study quantitatively examines the feasibility of different AM-enabled spare parts supply chain configurations. Using cost data extracted from a case study, three scenarios per AM machine technology are modeled and compared.FindingsResults suggest that hub production configuration depending on the utilized AM machines can provide economic efficiency and effectiveness to reduce equipment downtime. While previous studies have suggested the need for AM machines with efficiency for single part production for a distributed supply chain, the findings in this research illustrate the positive relationship between multi-part production capability and the feasibility of a hub manufacturing configuration establishment.Originality/valueThis study explores the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it. Although the existing body of knowledge contains research on production decentralization, research on various levels of decentralization is lacking. Using a real-world case study, this study aims to compare the feasibility of different levels of decentralization for AM-enabled spare parts supply chains.


2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Hari P. N. Nagarajan ◽  
Hossein Mokhtarian ◽  
Hesam Jafarian ◽  
Saoussen Dimassi ◽  
Shahriar Bakrani-Balani ◽  
...  

Additive manufacturing (AM) continues to rise in popularity due to its various advantages over traditional manufacturing processes. AM interests industry, but achieving repeatable production quality remains problematic for many AM technologies. Thus, modeling different process variables in AM using machine learning can be highly beneficial in creating useful knowledge of the process. Such developed artificial neural network (ANN) models would aid designers and manufacturers to make informed decisions about their products and processes. However, it is challenging to define an appropriate ANN topology that captures the AM system behavior. Toward that goal, an approach combining dimensional analysis conceptual modeling (DACM) and classical ANNs is proposed to create a new type of knowledge-based ANN (KB-ANN). This approach integrates existing literature and expert knowledge of the AM process to define a topology for the KB-ANN model. The proposed KB-ANN is a hybrid learning network that encompasses topological zones derived from knowledge of the process and other zones where missing knowledge is modeled using classical ANNs. The usefulness of the method is demonstrated using a case study to model wall thickness, part height, and total part mass in a fused deposition modeling (FDM) process. The KB-ANN-based model for FDM has the same performance with better generalization capabilities using fewer weights trained, when compared to a classical ANN.


Sign in / Sign up

Export Citation Format

Share Document