Automatic Control and Computer Sciences

, Volume 52, Issue 5, pp 451–463

# Computer Numerical Control-PCB Drilling Machine with Efficient Path Planning – Case Study 2

• Derar Eleyan
• Saed Tarapiah
• Amna Eleyan
Article

### Abstract

In Printed Circuit Board (PCB) drilling machines, the location of the drill holes are fed into the machine and the PCB will be drilled at the corresponding coordinates. Some machines do not choose the optimal route when completing their tasks. Hence, this paper proposes an approach, which is based on the Algorithm Shortest Path Search Algorithm (SPSA), for finding the optimal route in PCB holes drilling process. In SPSA, when the robotic arm at the initial position, the algorithm calculates the nearest point to the initial position from all points that the wires start or ends with. If the nearest point is a start-of-wire point, it will use SPS algorithm 1. If the nearest point is an end-of-wire point, it will use SPS algorithm 2. This process is repeated until drilling all the lines. Then, the robotic arm will drill all the holes according to the proposed Simulated Annealing Algorithm (AS) in order to determine the optimal machining parameters for milling operations. The results of the different optimization algorithms Genetic Algorithm (GA) and AS are compared and conclusions are presented. The proposed Computer Numerical Control (CNC) machine consists of a driver, drill, three stepper motors, cables and microcontroller PIC16f877A to control the movement of the machine. The SPSA algorithm optimizes the use of the motors and other mechanical paths involved in the process while reducing total time taken to traverse all the drill holes. This paper also explains the detailed problem of interest and the mathematical formulation of the problem is defined. Experimental result indicates that the proposed SPSA-based approach is capable to efficiently find the optimal route for PCB holes drilling process.

## Keywords:

Shortest Path Search Algorithm PCB Drill Holes Path Planning Routing Problem

## Notes

### ACKNOWLEDGMENT

The authors would like to thank Palestine Technical University – Kadoorie (PTUK) and An-Najah National University for supporting this research and allowing us to conduct this work in the university labs. The system is developed for the educational purpose and is currently in use at Microprocessor Control Lab at An-Najah National University.

## REFERENCES

1. 1.
Adam, A., Abidin, A.F.Z., Ibrahim, Z., Husain, A.R., Yusof, Z.M., and Ibrahim, I., A particle swarm optimization approach to Robotic Drill route optimization, 2010 Fourth Asia International Conference on Mathematical/Analytical Modeling and Computer Simulation, IEEE, 2010, pp. 60–64.Google Scholar
2. 2.
Aarts, E., Korst, J., and Michiels, W., Simulated Annealing. Search Methodologies, 2005, pp. 187–210.
3. 3.
MohdMuzafar, I., MohdAzlishah, O., HamzahAsyrani, S., Maizatul Alice, M.S., Mohd Harris, M., RidzaAzri, R., and Khairuddin, O., Route Planning Analysis in Holes Drilling Process Using Magnetic Optimization Algorithm for Electronic Manufacturing Sector, 2013.Google Scholar
4. 4.
Othman, M.H., Abidin, A.F.Z., Adam, A., Yusof, Z.M., Ibrahim, Z., Mustaza, S.M., and Yang, L.Y., A binary particle swarm optimization approach for routing in PCB holes drilling process, First International Conference on Robotic Automation System, 2011, pp. 201–206.Google Scholar
5. 5.
Zhu, G.Y., Drilling path optimization based on swarm intelligent algorithm, 2006 IEEE International Conference on Robotics and Biomimetic, IEEE, 2006, pp. 193–196.Google Scholar
6. 6.
Kirkpatrick, S., Gelatt, C.D., and Vecchi, M.P., Optimization by simulated annealing, Science, 1983, vol. 220, no. 4598, pp. 671–680.
7. 7.
Goldberg, D.E., Genetic Algorithms in Search, Optimization and Machine Learning, New York: Addison-Wesley Publishing Company, Inc., 1989.
8. 8.
Daadoo, M. and Daraghmi, Y., Design and implementation of low cost computer numerical control-printed circuit boards drilling machine, Int. J. Eng. Innovative Technol., 2016, vol. 5, no. 10, pp. 63–67.Google Scholar

## Authors and Affiliations

• 1
Email author
• Derar Eleyan
• 2
• Saed Tarapiah
• 3