3D软件

Authentise and Addiguru partner to merge in-situ process monitoring and workflow management

Authentise, a developer of additive manufacturing workflow software, has announced a partnership withAddiguru,实时过程监视系统的开发人员,以推动身份验证的制造执行系统(AMES)。

Together, the duo will integrate computer vision and AI-based in-situ monitoring functionality into AMES, allowing for real time actions alongside the digitized workflow management currently offered.

Authentise首席执行官Andre Wegner解释说:“与Addiguru的合作是成功的,因为每个方带来了独特的技能:Authentise提供了对数字线程和对机器数据的访问的连贯控制,Addiguru可以添加视觉检查和智能分析。我们与Addiguru的合作证明了Authentise的开放性和创业社区的持续创造力。”

该软件主要用于金属3D印刷零件,例如EOS P450。通过EOS North America的照片。
该软件主要用于金属3D印刷零件,例如EOS P450。通过EOS North America的照片。

The merging of technicality and management

该项目最终是为了简化the additive manufacturing monitoring process, enabling users to save costs on failed parts. Addiguru’s algorithms will create real-time notifications in the Authentise app and web interface to alert the user of potential issues with the build. AMES will then display relevant images of the part while visually marking the alert within the full workflow view. The full set of findings will be automatically added to the real-time traceability alert for later viewing, and a new analytics section will be generated specifically for that build.

Admes名称旁边显示了Addiguru警报。图像通过身份验证。
Admes名称旁边显示了Addiguru警报。图像通过身份验证。

Once the build is complete or cancelled, users will then be able to overlay the detected anomalies with the corresponding sensor data taken directly from the machine. Additionally, this data can be used to create custom alerts, reports, and dashboards for further analysis and diagnosis. Since Addiguru’s technology is “machine brand agnostic”, it can easily be integrated into existing 3D printers with varying sensor setups, including a whole host of powder bed fusion machines.

Shuchi Khurana, CEO of Addiguru, adds: “Existing in-process monitoring tools either require the user to have spent days setting up trial prints or to click through every image to detect potential flaws. The combination of our AI-driven insight and Authentise’s workflow tools enables the user to gain practical benefit in a system they love by having all data and notifications in one place. This initiative with Authentise also moves us closer to our goal of an open architecture framework.”

AMES中的警报细节带有相应的图像提要显示缺陷。图像通过身份验证。
AMES中的警报细节带有相应的图像提要显示缺陷。图像通过身份验证。

Artificial intelligence in the 3D printing industry

In recent years, AI-based quality control systems have started to emerge in the additive manufacturing industry. Just last month,Purdue Universityreceived an $800,000 grant from the我们部门of Energy加速世界第一个的发展3D打印的核反应堆核心。The capital will allow the University’s engineers to create a novel AI model to ensure nuclear-grade quality of the microreactor’s critical components.

在其他地方,在密歇根技术大学, Dr. Joshua Pearce recently launched an open-source, computer vision-based software algorithm capable of打印故障检测和校正for the FFF process. The code leverages just a single webcam pointed at the build plate to track printing errors and generate any actions it deems necessary to improve reliability and print success rates.

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特色图片显示金属零件3D在EOS P 450上打印。通过EOS北美的照片。