Andy Alubaidy (PhD, PEng.), Faculty of Applied Science & Technology, Sheridan College
In this work, a Vision Guided Robotic Smart System (VGRSS) that is capable of assembling electronic boards and inspect them for defects and faults before going further to soldering step has been designed and built. Currently the electronic board assembly is done manually in many companies using human labour to select the components and place them in position on the PCB by reading the assembly drawing and manually assembling the entire board. As per the current setup there are high rework rates as result of human error and missing components on the board which is detected at a mush later stages when the board goes for non-destructive testing and fails the quality test. There is a need to upgrade the manufacturing process to reduce the production cost and modify it to optimise the production capacity, reliability, and accuracy. The main purpose of the VGRSS is to eliminate human labour cost and to reduce the required training for the operator. The VGRSS reduces the chances of missing the components on the board and eliminates the rework cost. Thus, enhances the product’s quality, adds an intermediate smart inspection check, and improves the cycle time.
Figure 1 shows block representation of the VGRSS processing operation. PCB’s are coming on a conveyor while all the electronic components are stored within reach of the robot. The conveyor stops once a PCB is detected and the vision system send the robot the location and orientation of the PCB. The robot with its flexible gripper pick the electronic parts one by one and place them in the proper location on the PCB. The major constraint for this work was the variety of electronic components, its size and the different complexity of the components which are to be inserted on the printed circuit board (PCB). Another challenge was the communication protocol as not all devices and controllers used the same system. One other constraint was the softness or delicate nature of the various electronic components which required to be handled carefully. By finding the common communication link between the various devices all the processors and controllers were connected to transfer data at a required speed. To solve the electronic component variability issue, all the different components were grouped based on the physical appearance and weight, and custom gripper were designed to hold the different components securely so that there is no slippage during manipulation. The system was programed using ABB Rapid code. All the electronic components were able to be detected, identified by the vision system and then picked and placed in their respective places on the PCB. The system was extensively test to ensure the repeatability of the operation. The system was executed in a production mode to ensure the quality of the final product. Results showed that the system was successfully designed, built, programed, and executed to perform the electronic board assembly with much better cycle times.
About the Author
Dr. ANDY ALUBAIDY received his PhD in mechanical engineering from Ryerson University in 2012. He has extensive industrial and academic experience in the areas of advanced manufacturing, robotics and automation. He joined Sheridan College in 2013, and is currently a professor in the School of Mechanical and Electrical Engineering and Technology. Dr. Alubaidy has been involved in various successful research and development projects with small, medium, and large manufacturing and consulting companies.
Dr. Alubaidy is a member of the Professional Engineers Ontario, Canadian Council of Professional Engineers, the American Society of Mechanical Engineers, CMC Microsystems, and Webmed Central Biomedical Engineering Editorial Board. He is a Siemens Mechatronics certified instructor and Fanuc Robotics certified instructor.
Dr. Alubaidy research interests are in the areas of robotics, vision systems, deep learning, smart factories, Industrial Internet of Things, advanced manufacturing and automation. Over the past years, his research has been published in many international journals and conferences, as well as in several book chapters. He received the NSERC/CRSNG (Nano Innovation Platform) award in 2010 and was nominated for the Ryerson Golden Medal award in 2012 for his excellence in academia and research. He was nominated for the People award in 2020 and he recently received The Minter Award of Excellence from the Ontario Ministry of Colleges and Universities. Dr. Alubaidy work of rethinking academic delivery during global pandemic was featured in MacLean’s in 2020.