Matthew Averill's Engineering Portfolio
© Matthew Averill

Automated Assembly Line

Using collaborative robotics to create an efficient product assembly line.

Fully

Automated

This video shows, from start to finish, the automated assembly line created by my team and me. The purpose of the assembly line was to manufacture and assemble a two part product, which in our case was a calculator holder. One of the roles I played was designing the product for milling operations using SolidWorks.

The challenge of designing these parts was due to the constraints introduced by the CNC mill and assembly procedure. With this in mind, I designed the product for optimal throughput. I modeled each part so that it required only one milling operation and met the tolerances for assembly.

In oder for the two parts to be assembled, I added a ramp to the acrylic piece. This allowed for the force of friction to be overcome much more easily than the original 90° design. In order for the stock material to be milled, I created the milling processes for each part in GibbsCAM. I minimized the error from the CNC mill by creating processes such as rounded corners and second-pass contours.

Another responsibility of mine was to program the robotic arm for the milling station. This task consisted of programming the robot to place/remove the stock material into the CNC mill. In addition, the parts needed to palletized and placed onto the conveyor belt.


Calculator Holder

The finished product of this assembly line was a calculator holder for students' desks. The purpose of this project was to implement lean manufacturing principles in combination with collaborative robotics to create an efficient, fully automated, product assembly line. Some statistics from the manufacturing procedure can be viewed below.

Throughput

1 part/600 seconds


Steady-state WIP

2.5


Cycle time

1500 seconds

Upon completion of the manufacturing process, I calculated the throughput, steady-state WIP, and cycle time. While designing the process, an emphasis was placed on the robot’s pathways. Each pathway was optimized in order to reduce time spent on robot movement, which led to reduced cycle time. The team designed around six-sigma manufacturing techniques in order to optimize yield.