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When Robotics Meets Metal Additive Manufacturing

25th September 2019


The finished robotic stabiliser part The finished robotic stabiliser part
Autodesk Fusion 360: explore and comparison of the generated options Autodesk Fusion 360: explore and comparison of the generated options
SCUT robot with additive manufactured stabiliser during the competition SCUT robot with additive manufactured stabiliser during the competition
Original design and generative design by Autodesk Fusion 360 Original design and generative design by Autodesk Fusion 360

Chenlu Fang describes how a robotics team has sought new solutions for improved efficiency and workflow from design to manufacturing

Robotics is a multi-disciplinary science involving traditional fields including mechanical engineering, control systems, material science and IT, and the latest trends of computer science, bionics and advanced manufacturing.

The RoboMaster Robotics Competition provides a unique opportunity for young engineers to test their innovation and gain hands-on experience in the field of robotics. Marking its fifth year competing and having won two championships since 2017, the Robotic Team of South China University of Technology (SCUT) has been seeking new solutions for improved efficiency and quality workflow from design to manufacturing. These young luminaries took their opportunity using Autodesk software and Farsoon additive manufacturing (AM) technologies.

What Are The Challenges?

There are three main challenges: design iteration, weight reduction and strength requirements. Each year, RoboMaster announces requirements that each team needs to tailor their design accordingly for the final contest in eight months. To achieve the best performance of the robot, the design team had to make four to five complex “design-build-test” iterations, each cycle including mechanical design, dynamic analysis, structural analysis, assembly, programming and testing.

The object of focus is the stabiliser mount on the robot, a key component that connects the mobile system with the upper projectile system. It is designated to perform complex and rapid movements such as steering, aiming and shooting during the competition, of which the weight reduction of this component has been the key to achieving optimum performance. Meanwhile, the robot will experience various extreme conditions including collisions, pellet impact and vibration during the contest. The stabiliser mount requires extreme mechanical strength to avoid any damage on the contest field.

In previous designs, the stabiliser mount was limited by the production method, mainly produced by CNC machining with further assembling of up to 27 parts. The weight of these assembled parts could be up to 295g, resulting in slower reaction times and movement speeds. In addition, the assembled parts increased the potential for damage during impacts.

The Additive Manufacturing solution

In early 2019, the SCUT team began to adopt Autodesk software and Farsoon AM technology to improve the design and manufacturing process. The additive technology offers unprecedented freedom in flexibility of the geometry of design that suits best for the application.

Thanks to generative design, a key feature in Autodesk Fusion 360, the students are able to apply a variety of working conditions such as the extreme impact loads during competition to the part. They can then define the output options such as desired weight limit (lightweight target), engineering materials (including resin, nylon, aluminium), safety factor (up to eight) and potential processing method (CNC, milling, additive). This ensures the best performance of the part during the contest. All the options generated have been further explored and tested by the students so they could choose the optimal design for final manufacturing.
 

Three designs were chosen with different materials and processing methods for assembly and field validation: resin (stereolithography); nylon (plastic laser sintering); and aluminium (metal laser melting). The resin and nylon parts broke in the field impact, while the AlSi10Mg aluminium stabiliser mount produced by Farsoon FS271M metal laser melting technology stands out with its qualified strength, durability and performance.

This combination of generative design and AM completely overturns the concept of a traditional design process. It creates the optimal design in a very short time without the limitations of traditional processing and materials options.

The Results

The optimised additive manufacturing stabiliser mount achieved a final weight of 170g – a 42% weight reduction compared to the original CNC process. The lighter weight means a faster response to signals and improved mobility in the field. Simultaneously, by combining 27 parts to only one single part, it reduces the material waste while enhancing the strength by adding support, therefore reducing the mass of the robot while ensuring structural integrity.

This new workflow also helps accelerate design iteration from the development process to manufacturing. The traditional design by engineer is limited by his own experience, while generative design employs cloud computing to help generate and iterate the optimal result. Compared to traditional manufacturing, additive technology can build two sets of stabilisers in only two days. The whole workflow is simplified with improved efficiency and it also it offers the best solutions for application.

Faster design iteration helps the SCUT team to work more efficiently while reducing the cost of material and manufacturing. This year, the SCUT team achieved considerable cost reduction to research and development. For example, the mechanical team’s entire iterative cost was reduced by 80%, which would not have been possible before.

With the help of innovative additive technology, the SCUT team entered the RoboMaster (South-China area) contest on May 23, 2019. The optimised design and improved performance of the stabiliser mount enabled the SCUT team to win the championship again, despite some intense competition.

Chenlu Fang is with Farsoon Technologies

 







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