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Additive MAnufacturing - Additive Micro-manufacturing Technology:

30/9/2019

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The additive micromanufacturing technology (µAM), which has been developed by Exaddon, is based on electrochemical deposition; A small printing nozzle, called an iontip, is immersed in a supporting electrolyte bath. A precisely regulated air-pressure pushes the metal ion containing liquid through a microchannel inside the iontip. The liquid flow is very small and can be as low as femtoliters per second. At the end of the microchannel, the ion containing liquid will be released onto the surface. The dissolved metal ions are then electrodeposited into solid metal atoms. These metal atoms are growing together into small building blocks, so called voxels. Optical force feedback registers the completion of each voxel until all voxels are printed and the complete object is constructed. The electrochemical printing process takes place at room temperature. The process leads to very high-quality metal structures that do not need any post-processing, they are immediately ready for their application. 

The acting forces on the iontip can be measured optically and used as feedback. This allows to detect which voxels of the object have already been printed. This optical force feedback provides real-time process control.

The following video explains the process:

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تقنية التصنيع بالإضافة المايكروية (µAM) - مبدأ الترسيب الإلكتروميكانيكي

تقنيات التصنيع بالإضافة -|22|- تقنيات التصنيع بالإضافة - تقنية التصنيع بالإضافة المايكروية (µAM) - مبدأ الترسيب الإلكتروميكانيكي تقوم تقنية التصنيع بالإضافة المايكروية Additive Micromanufacturing المطورة من قبل شركة Exaddon السويسرية على مبدأ الترسيب الإلكتروميكانيكي Electromechanical Deposition وذلك عن طريق فوهة صغيرة جداً تسمى بالرأس الأيوني Iontip، حيث تكون هذه الفوهة مغمورة في حمّام إلكتروليتي داعم، ومن ثم يتم دفع أيونات المعدن الحاوية على السائل ضمن قناة مايكروية داخل الرأس الأيوني وذلك عن بواسطة ضغط هوائي مضبوط بدقة عالية، ويكون تدفق السائل قليلاً جداً بحيث لا يتجاوز بضعة فيمتوليترات في الثنية الواحدة (الفيمتو هو 10 أس 15-). وعند نهاية القناة المايكروية يثق الإيونات الحاوية على السائل على سطح البناء، وعند ذلك يحدث الترسيب الإلكتروميكانيكي عن طريق تموضع أيونات المعدن المذاب على ذرات المعدن الصلبة، وبالتالي تنمو ذرات المعدن تلك على هيئة وحدات بنائية يطلق عليها اسم الفوكسل Voxel. وتقوم واجهة بصرية ذات تغذية راجعة بإرسال تسجيلات اكتمال كل فوكسل بشكل دوري حتى يتم الانتهاء من طباعة كل الفوكسلات وبالتالي بناء الجسم. مبدأ الترسيب الإلكتروميكانيكي يمكن أن يتم في درجة حرارة الغرفة، والعملية تنتج في نهاية المطاف بنى معدنية ذات جودة عالية جداً حيث أنها لا تتطلب أية عمليات لاحقة وتكون جاهزة للاستثمار المباشر ضمن التطبيقات التي خصصت لها. ويمكن التحكم بسطوح التفاعل على الرأس الأيوني وقياسها بصرياً حيث يستفاد من معلوماتها كتغذية راجعة، وهذا يسمح بالتحديد الدقيق للفوكسلات التي تم بناؤها بالفعل، وهذه المعلومات المرجعية من السطوح البصرية تفيد في التحكم والمعالجة بالزمن الحقيقي Real-Time Process Control. الفيديو التالي يشرح العملية. م. رامي خليل

Posted by Eng. Rami Khalil on Saturday, September 28, 2019
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Machine Design - Generative Design and Future of Manufacturing

17/11/2018

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​Generative design technology is now available through Autodesk Fusion 360 environment (it is available in Autodesk Inventor 2019 Professional).
As it was mentioned before, each design engineer knows that the design process begins from some information, data, constrains, and parameters that are modeled by means of the computer to get the desired purpose of the design. However, the design procedure is driven by the design engineer. Consequently, the number of design solutions according to those constrains and parameters is only subject to the ability of the design engineer to generate the design solutions which may partly all totally fullfit the design data and its purpose. And even if the design is complete and complies with the design parameters, it may not be perfect as the design is based on the abilities of the design engineer who leads the design process.

This new methodology in design depends on entering as inputs all information, parameters, and design constrains in the design software, then using a generating algorithm driven by cloud computing related to Autodesk Fusion 360, all possible potential deigns are generated based on the input data. After that, the software itself, and by supervision of the design engineer, tests each design to see if it is comply with the design parameters or not depending on the available machining possibilities and other factors such as the weight, for instance. Through this procedure, FEA is used to verify and evaluate each design solution until we get the best solution. And so, the design solution is not limited with one or two solutions made by the design engineer, rather with thousands or millions of solutions that sorted and addressed to get the best of them.

This new approach in design is extremely useful if it comes together with Additive Manufacturing technologies (i.e. a massive number of solutions with the ability to manufacture any of them beyond the traditional manufacturing means limitations).

The following video practically explains the generative design approach in choosing the best solution for the brakes and fuel base, the result is creating only one part instead of 86 parts that may be used in case of following the traditional design method.

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التصميم التوليدي ومستقبل التصنيع.

تصميم الآلات -|8|- تصميم الآلات - التصميم التوليدي ومستقبل التصنيع ------------------------------------------- التصميم التوليدي أو ما يعرف بالإنكليزية بـ "Generative Design" أصبح الآن متاحاً عبر بيئة Autodesk Fusion 360 (يمكن الولوج إلى هذه البيئة من خلال برنامج Autodesk Inventor 2019 Professional). كنا قد ذكرنا سابقاً، فإن كل مهندس تصميم يعلم أن عملية التصميم التقليدية تبدأ من معلومات ومعطيات ومحددات وبارامترات تتم نمذجتها باستخدام الحاسب بغية الوصول إلى الهدف المرجو من التصميم، لكن هذه الآلية التصميمة تدار بواسطة قدرة مهندس التصميم القائد لها، مما يعني أن عدد الحلول التصميمة وفقاً للبارامترات والمحددات التصميمية ستكون خاضعة لقدرة مهندس التصميم وحده على توليد الحلول التصميمة والتي قد تنسجم كلياً أو جزئياً مع معطيات التصميم وهدفه. ومع ذلك، وحتى لو كان التصميم متكاملاً وموافقاً للبارامترات التصميمة إلا أنه قد لا يكون مثالياً خالصاً لأن ذلك يعتمد على قدرة المهندس القائد للعملية التصميمة نفسه. وهذه المنهجية الجديدة في التصميم (التصميم التوليدي، والذي أصبحت متوفرة الآن) تعتمد على إدخال كل المعلومات والبارامترات والقيود التصميمة في برنامج التصميم التوليدي ومن ثم، وعن طريق خوارزمية توليد تدار بواسطة الحوسبة السحابية "Cloud Computing" والخاصة ببيئة Autodesk Fusion 360، يتم توليد "كل" الاحتمالات الممكنة للتصميم بناء على معطيات الدخل، وبعد ذلك يقوم البرنامج نفسه بإدارة مهندس التصميم باختبار كل تصميم في حال كان موافقاً لبرامترات التصميم أم لا وتبعاً لإمكانيات التشغيل المتاحة وغير ذلك من العوامل المؤثرة كالوزن مثلاً، ويستخدم خلال ذلك تحليل العناصر المنتهية Finite Element Analysis FEA للتحقق من جودة كل حل، وهكذا حتى يقع الاختيار على التصميم الأمثل. وبالتالي، لا ينحصر الحل التصميمي على حل واحد أو إثنين صادرين من مهندس التصميم، بل على آلاف بل ملايين الحلول التي تتم "غربلتها" حتى نصل للأمثل منها. هذه المنهجية الجديدة في التصميم ستكون فعالة جداً إذا ما اقترنت مع تقنيات التصنيع بالإضافة "Additive Manufacturing" ( أي عدد كبير جداً من الحلول مع إمكانية تصنيع أي منها بعيداً عن مقيدات طرائق التصنيع التقليدية). الفيديو التالي يوضح مثالاً عملياً لتنفيذ منهجية التصميم التوليدي من اختيار التصميم الأفضل لقاعدة دواسات المكابح والوقود، حيث أدت هذه الطريقة إلى إيجاد القاعدة كقطعة واحدة (بدلاً من 86 قطعة فيما لو تم التصميم بالطرق التقليدية). م. رامي خليل ----------------------------------- Machine Design -|8|- Machin Design - Generative Design and Future of Manufacturing --------------------------------------------------- Generative design technology is now available through Autodesk Fusion 360 environment (it is available in Autodesk Inventor 2019 Professional). As it was mentioned before, each design engineer knows that the design process begins from some information, data, constrains, and parameters that are modeled by means of the computer to get the desired purpose of the design. However, the design procedure is driven by the design engineer. Consequently, the number of design solutions according to those constrains and parameters is only subject to the ability of the design engineer to generate the design solutions which may partly all totally fullfit the design data and its purpose. And even if the design is complete and complies with the design parameters, it may not be perfect as the design is based on the abilities of the design engineer who leads the design process. This new methodology in design depends on entering as inputs all information, parameters, and design constrains in the design software, then using a generating althorithm driven by cloud computing related to Autodesk Fusion 360, all possible potential deeigns are generated based on the input data. After that, the software itself, and by supervision of the design engineer, tests each design to see if it is comply with the desing parameters or not depending on the availble machining possibilities and other factors such as the weight, for instance. Through this procedure, FEA is used to varify and evaluate each design solution until we get the best solution. And so, the design solution is not limitted with one or two solutions made by the design engineer, rather with thousands or millions of solutions that sorted and addressed to get the best of them. This new approach in design is extremely usefull if it comes together with Additive Manufacturing technologies (i.e. a massive number of solutions with the ability to manufacture any of them beyound the traditional manufacturing means limitations). The following video practically explains the generative design approach in choosing the best solution for the brakes and fuel base, the result is creating only one part instead of 86 parts that may be used in case of following the traditional design method. Eng. Rami Khalil

Posted by Eng. Rami Khalil on Friday, November 16, 2018
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Machine Learning “Fixes” 3D-Printed Metal Parts Before They’re Built

12/10/2018

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For years, engineers at Lawrence Livermore National Laboratory  have used sensors and imaging techniques to analyze the physics and processes behind metal 3D printing in order to build high-quality metal parts the first time, every time. Now, they are leveraging machine learning to process data obtained during 3D builds in real time, detecting within milliseconds whether a build will be high quality. More precisely, they are developing convolutional neural networks (CNNs), a type of algorithm commonly used to process images and videos, to predict whether a part will be good by looking at as little as 10 milliseconds of video.

Until now, analysis of sensor data taken while 3D printing a metal parts was done after the part was finished and it was expensive. And part quality could only be determined long after, explains principal investigator and LLNL researcher Brian Giera. With parts that take days to weeks to print, CNNs help engineers better understanding the printing process and let them correct or adjust the process in real time if necessary.

For years, engineers at Lawrence Livermore National Laboratory  have used sensors and imaging techniques to analyze the physics and processes behind metal 3D printing in order to build high-quality metal parts the first time, every time. Now, they are leveraging machine learning to process data obtained during 3D builds in real time, detecting within milliseconds whether a build will be high quality. More precisely, they are developing convolutional neural networks (CNNs), a type of algorithm commonly used to process images and videos, to predict whether a part will be good by looking at as little as 10 milliseconds of video.

Until now, analysis of sensor data taken while 3D printing a metal parts was done after the part was finished and it was expensive. And part quality could only be determined long after, explains principal investigator and LLNL researcher Brian Giera. With parts that take days to weeks to print, CNNs help engineers better understanding the printing process and let them correct or adjust the process in real time if necessary.

LLNL researchers developed the neural networks using about 2,000 video clips of melted laser tracks under varying conditions, such as speed or power. They scanned part surfaces with a tool that generated 3D height maps, using that information to train the algorithms to analyze sections of video frames (each section called a convolution). The process is too difficult and time-consuming for humans, according to Giera.

The algorithms that label the height maps of each build then use the same model to predict the build track’s width and standard deviation. As well as whether the track was broken was developed by LLNL researcher Bodi Yuan. Using the algorithms, researchers could video parts being printed and determine if it would have acceptable quality. The neural networks detected whether parts would be continuous with 93% accuracy.

Some researchers at LLNL had spent years collecting various forms of real-time data on the laser powder-bed fusion metal 3D-printing process, including video, optical tomography, and acoustic data. While working with that group to analyze the data, Giera concluded it wouldn’t be possible to do all the data analysis manually and wanted to see if neural networks could simplify the task.

The neural networks they developed could theoretically be used in other 3D printing systems, Giera said. Other researchers should be able to follow the same formula, creating parts under different conditions, collecting video, and scanning them with a height map to generate information that could be used with standard machine-learning techniques.

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تقنيات التصنيع بالإضافة -|21|- التصنيع بالإضافة – تقنية تعلم الآلة Machine Learning تقوم "بإصلاح" القطع المعدنية...

Posted by Eng. Rami Khalil on Friday, October 12, 2018
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Additive Manufacturing – Multi Jet Fusion (MJF) Technology

5/8/2018

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​HP's multi jet fusion technology produces quality functional parts at a production speed which is up to ten times faster than today's competing products. Unlike the slow point processes of some current technologies, HP's multi jet fusion technology processes parts in two fast area-wide passes to achieve top speed part production. The process begins by applying a layer of material in a work area in the opposite direction in one continuous pass we print fusing and detailing agents across the full working area, this pass combines the printing with the fusing energy and the process is then completed. HP's proprietary architecture is capable of printing 30 million drops per second along every single inch of bed width enabling extreme precision and dimensional accuracy.

To produce truly functional parts, it's important to ensure that the material has been properly fused and that part edges are smooth and well-defined. To achieve part quality at speed, HP invented a multi agent printing process; in this process, a fusing agent is applied on a material layer where the particles are meant to fuse together, a detailing agent is applied to modify fusing and create fine detail and smooth surfaces, the area is exposed to energy and reactions between the agents and the material cause the material to selectively fuse together to form the part. The fusing process requires accurate temperature control across the entire material layer. HP multi jet fusion closed-loop thermal control system does this by measuring temperatures at hundreds of points on the material bed, this information then determines which areas receive more energy to raise the temperature and which areas are cooled allowing for control of thermal bleed and layer to layer fusing and cooling. The result is full control over mechanical properties, dimensional accuracy, and repeatability. The process is then repeated until a complete quality truly functional part has been formed.

The HP multi jet fusion technology achieves new levels of part quality at these breakthrough speeds. In 3D design and printing, a voxel represents a value on a regular grid in a three-dimensional space like a pixel with volume. By controlling the properties of each individual voxel through agents, HP multi jet fusion can produce parts that can't be made by other methods; taking advantage of HP's in-depth knowledge of color science, HP's 3d printers could in the future selectively print a different color at each volumetric pixel, a single 3d printed part could have literally millions of colors but more than just full-color printing of functional parts. HP's multi-agent system enables a fundamentally different approach that could unlock the full potential of 3d printing at each voxel; HP transforming agents could control surface texture wear, and friction enabling single parts with multiple textures or the monitoring of part performance. The transforming agents could control the translucency of each voxel enabling the printing of lenses or sensors. We could also optimize the strength and stiffness in portions of a part and print elastic voxels in other portions of the part. The conductivity of certain voxels could also be controlled enabling embedded electronics. HP transforming agents could also be used to enable the printing of new advanced materials or enable emulating different materials at each voxel. HP's multi jet fusion technology could enable design and manufacturing possibilities that surpass the limits of our imagination.

​Explaining Video for the process:

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تقنيات التصنيع بالإضافة -|20|- التصنيع بالإضافة – تقنية الانصهار النفاث المتعدد (Multi Jet Fusion -...

Posted by Eng. Rami Khalil on Sunday, August 5, 2018
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Additive Manufacturing – NanoParticle Jetting (NPJ) Technology:

3/12/2017

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NanoParticle Jetting technology produces high strength metal parts with the ease and versatility of the Inkjet based additive manufacturing. The technology is based on enabling metal to be deposited in liquid form so it can be jetted from standard inkjet nozzles, to do this, the system uses nano sized metal particles suspended within special liquid formula eliminating inefficient lasers, this metal liquid formula can be jetted from standard printing head. The material are packaged with specially adapted cartridges that are loaded easily by hand into the system.

Because there is no powder VAT, the system uses only the material that you need saving space and eliminating the need to handle metal powders.
​
The print heads deposit a fine layer of metal liquid droplets onto the system build tray, with each pass of the print heads the metal part is built up as the tray descends the metal liquid formula which is jetted from many thousands of printing nozzles synchronously in a process that is up to five times faster than laser metal printer. Within the system build enveloped, a temperature of up to 550 degrees Fahrenheit or 300 degrees Celsius cause the liquid jacket around the metal nanoparticles to elaborate allowing the stochastic metal particles to bind strongly and with virtually the same metallic and density as traditional made metal parts. With layer thickness under 2 microns, the result is never before seen levels of detailed surface finish and accuracy with no compromise on speed or build time.

Explaining Video for the process:

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تقنيات التصنيع بالإضافة -|19|- التصنيع بالإضافة – تقنية بثق الجزيئات النانوية (NanoParticle Jetting –...

Posted by Eng. Rami Khalil on Sunday, December 3, 2017
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