3D Printing with Carbon Fiber: Tracing the Lifecycle Thread

Engineering.com | May 06, 2019

3D Printing with Carbon Fiber: Tracing the Lifecycle Thread
3D-printing carbon fiber is now a mainstay of the additive manufacturing (AM) industry. While companies like Impossible Objects seek to make large-scale carbon fiber a reality, Markforged and a number of filament suppliers have made 3D printing with this tough material commonplace. In this article, we will trace the carbon fiber that has been woven into the industry from its roots to its final applications and possible future.
About 90 percent of carbon fiber starts as a polymer called polyacrylonitrile (PAN), while the remaining 10 percent comes from rayon or petroleum pitch. PAN is derived via free radical polymerization of acrylonitrile, which is in turn a derivative of the hydrocarbon propylene, a byproduct of oil refining and the processing of natural gas.
To create the fiber, the initial material, known as a precursor, is heated in air to a temperature of about 300°C in order to stabilize it for the next step, a process known as carbonization.

Spotlight

Once a year, the internal expert conference on Additive Manufacturing takes place, with the aim of transforming research and development in into new business models and accelerating the industrialization of additive manufacturing.

Spotlight

Once a year, the internal expert conference on Additive Manufacturing takes place, with the aim of transforming research and development in into new business models and accelerating the industrialization of additive manufacturing.

Related News

It's Showtime! Has 3D Printing Finally Matured?

IndustryWeek | June 12, 2020

In many ways, the COVID-19 pandemic has put manufacturing under a microscope. It has enabled the whole world to see glaring instances of inadequacies and a general lack of preparedness as supply chains seemingly crumbled overnight. Of course, it has also shown amazing strengths in leadership, innovation, determination and collaboration as a growing number of manufacturers leveraged internal capabilities and external partnerships to dynamically pivot operations to meet the dire needs of patients and people on the frontlines. Throughout the entire response, one industry fully embraced the opportunity to thrive. Simply put, the pandemic created a perfect storm for 3D printing/additive manufacturing. The crisis opened the door for a young – yet rapidly maturing -- industry as its growing community of passionate users and advocates embraced the challenge to demonstrate the technology’s potential. As such, 3D printing’s potential has taken center stage – giving manufacturers who may have not seriously considered the technology as an option the opportunity to see it in action

Read More

LandingLens to Help Manufacturers Build and Deploy Visual Inspection Systems Using AI

Landing AI | October 22, 2020

As organizations manufacture goods, human inspectors survey them for abandons. Think about a scratch on cell phone glass or a shortcoming in crude steel that could have an effect downstream when it gets transformed into something different. Landing AI, the organization began by previous Google and Baidu AI master Andrew Ng, needs to utilize AI innovation to recognize these imperfections, and today the organization dispatched another visual investigation stage called LandingLens. “We’re announcing LandingLens, which is an end-to-end visual inspection platform to help manufacturers build and deploy visual inspection systems [using AI],” Ng told TechCrunch. He says the company’s goal is to bring AI to manufacturing companies, but he couldn’t simply repackage what he had learned at Google and Baidu, partly because it involved a different set of consumer use cases, and partly because there is just much less data to work with in a manufacturing setting. Adding to the level of trouble here, each setting is novel, and there is no standard playbook you can fundamentally apply over every vertical. This implied Landing AI needed to concoct an overall toolbox that each organization could use for the extraordinary necessities of their manufacturing process. Ng says to place this trend-setting innovation under the control of these clients and apply AI to visual investigation, his organization has made a visual interface where organizations can work through a characterized cycle to train models to see every client's assessment needs. The manner in which it works is you take pictures of what a decent completed item resembles, and what a damaged item could resemble. It's not as simple as it would sound, since human specialists can differ over what comprises a deformity. The producer makes what's known as an imperfection book, where the examiner specialists cooperate to figure out what that deformity resembles through an image, and resolve contradictions when they occur. This is done through the LandingLens interface. Whenever investigators have settled upon a lot of marks, they can start emphasizing on a model in the Model Iteration Module, where the organization can train and run models to get to a condition of settled upon progress where the AI is getting the imperfections consistently. As clients run these tests, the product creates a report on the condition of the model, and clients can refine the models varying dependent on the data in the report. Ng says that his company is trying to bring in sophisticated software to help solve a big problem for manufacturing customers. “The bottleneck [for them] is building the deep learning algorithm, really the machine learning software. They can take the picture and render judgment as to whether this part is okay, or whether it is defective, and that’s what our platform helps with,” he said. He thinks this technology could ultimately help recast how goods are manufactured in the future. “I think deep learning is poised to transform how inspection is done, which is really the key step. Inspection is really the last line of defense against quality defects in manufacturing. So I’m excited to release this platform to help manufacturers do inspections more accurately,” he said.

Read More

Symphony IndustrialAI Takes over Savigent to Speed-Up Digital Factory and AI initiatives in Manufacturing

Symphony IndustrialAI | March 09, 2021

Symphony IndustrialAI announced the acquisition of Savigent, the IIoT, and digital workflow orchestration leader. This acquisition aims further to advance Symphony IndustrialAI's leadership into plant and supply chain processes. The combination of Savigent connected factory and process optimization capabilities and Symphony IndustrialAI solutions based on its advanced EurekaAI technology platform. It will assist the process and discrete manufacturing customers significantly to develop process efficiency, quality, and energy consumption. Customers do understand tremendous value through Savigent's easy and quick-connect disparate systems and equipment within factories. Through this, it will provide the required visibility to enable improved decision-making and drive costly variability and inefficiencies out of a vast array of manufacturing processes. Symphony IndustrialAI further enhances Savigent's low-code platform, real-time IoT data capture, and work orchestration technologies with AI optimization technologies. This way, Savigent will drive additional value for Symphony IndustrialAI's existing condition monitoring, asset performance management, and predictive maintenance solutions. On this, Symphony IndustrialAI Chief Executive Officer Dominic Gallello mentioned that Savigent had experienced tremendous growth over the last few years. The combination of the Savigent process optimization platform and Symphony IndustrialAI's EurekaAI platform and solutions will augment value for Savigent customers in the future. Mutually, we will deliver additional optimization and analytics capabilities and hasten our global expansion. The solutions we can provide our customers, partners, and the industrial community are very persuasive." In addition, Savigent CEO Dean Truitt continues saying that "the Savigent platform is a critical component in driving IT-OT convergence. It is because it provides the required visibility across manufacturing operations and delivers higher-value applications. The demand for solutions to transform manufacturing operations and achieve measurable benefits has never been better. "The potential to improve process operations through Symphony IndustrialAI technologies and AI capabilities is an essential component of next-generation digital manufacturing." John Dyck, CEO of CESMII, the Clean Energy Smart Manufacturing Innovation Institute, further mentions that this is a tremendously exciting opportunity for both Savigent and Symphony IndustrialAI that will strengthen manufacturers' ability to deliver on the promise of Industry 4.0. This combination will extensively extend Savigent's next-generation manufacturing operations capabilities into machine learning, AI, process optimization, and manufacturing materials."

Read More