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A Smart Automated Embedded Based PCB–Bare Board Testing Machine Design and Development using Flexible Flying Probe

Affiliations

  • SNR Sons College, Nava India Bus Stop, Between Fun Mall and Lakshmi Mills, Avinashi Road, Coimbatore - 641 006, Tamil Nadu, India
  • Bharath University,173, Agharam Road, Selaiyur, Chennai - 600 073, Tamil Nadu, India

Abstract


Background/Objectives: To design an automated embedded based flexible flying probe for testing PCB bare board more accurately which is one of the toughest challenge in manual testing. Methods/Statistical Analysis: Embedded based flexible flying probe can precisely position a probe on test points with high accurateness achieved by means of microstepping motors and linear laser encoders. The probe is moved horizontally and vertically based on the command passed by stepper motor which in-turn get the information from the prototype in format of Gerber file. First the flying probe checks the connectivity between two points then if the connectivity is good it will check the next track. Findings: This novel invention of flying probes are developed from new-fangled and novel thought intended to produce fasten testing speed, improved access, and enhanced error coverage. During the testing process if the machine determines some problem in the connectivity, it read the problem and send the error report on the PC display. From the error report, we can identify the fault placed in the PCB. A log file with test results is generated & stored on the PC. Fault details are sent to display unit of PC. The PC displays the matching accuracy and fault detection. The experimental result was conducted on 3 different PCB Bare board and the testing result shows the 92% accuracy and 18% false detection rate. It is compared with the jig board tester which produces less result compared to the proposed technique. The chief confront of this proposal is low down equipment and dispensation cost, absolute testing accurateness and capability to position close to faults and faults that may source irregular breakdowns. Applications/Improvements: This machine can be used for testing any type of PCB board. This proposed work develops a smart flying probe to test PCB which will significantly decrease test times therefore increasing productivity.

Keywords

Embedded, Automatic, Flying Probe, Micro Stepping Motors, Printed Circuit Board (PCB).

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References


  • Hong J, Park K and Kim K. Parallel processing machine vision system for bare PCB inspection. Proc. of the 24th Annual Conference of the IEEE. 1998; p.1346-50.
  • Langley FJ. Imaging systems for PCB inspection. Circuit Mauf. 1985; 25(1):50-54.
  • Beck M, Clark D. SMT inspection strategies: Maximizing cost effectiveness, in Proceedings of Technical Program: NEPCON West 91. 1991; p. 1075- 81.
  • Taylor BR. Automatic inspection in electronics manufacturing. SPIE Autom. Opt. Inspection. 1986; 654:157-59.
  • Heriansyah R, Abu-Bakar Sara. Defects classification on bare PCB using multiple learning vector quantization neural network paradigm. Penang, Malaysia: Proc. of International Conference on Computer Graphics, Imaging, and Visualization. 2004; p. 50-53.
  • Lin SC, Su CH. Department of Power Mechanical Engineering, National Tsing Hua University Hsin-Chu Taiwan. IEEE CIS 2006, A Visual Inspection System for Surface Mounted Devices on Printed Circuit Board. 2006; 300:1-4.
  • NKhalid NK, Ibrahim Z, Abidin MSZ. An algorithm to group defects on printed circuit board for automated visual inspection. 2008 May; 9(2):1-10.
  • MErcal MF, Dagli CH, Tsunekawa S. Automatic PCB inspection algorithms: A survey. Computer Vision and Image Understanding. 1996; 63(2):287-313.
  • Putera ISH, Ibrahim Z. Printed Circuit Board Defect Detection Using Mathematical Morphology and MAT LAB Image Processing Tools. IEEE 2nd International Conference on Education Technology and Computer (ICETC), 2010 June 22-24, pp. V5-359-63.
  • Ibrahim Z, Abdul S, Al-Attas R, Aspar Z. Model-based PCB inspection technique using wavelet transform. Proceedings of the 4th Asian Control Conference. 2002; p. 2026-29.
  • Santoyo J, Pedraza JC, Mejía LF, Santoyo A. PCB Inspection Using Image Processing and Wavelet Transform. MICAI 2007: Advances in Artificial Intelligence Lecture Notes in Computer Science. 2007; 4827:634-39.
  • Pugazhenthi D, Vallarasi AS. Offline Character Recognition of Printed Tamil Text using Template Matching Method of Bamini Tamil Font. Indian Journal of Science and Technology. 2015 Dec; 8(35):1-4.
  • Selvaganesan J, Natarajan K. Robust Face Recognition from Video based on Extensive Feature Set and Fuzzy_Bat Algorithm. Indian Journal of Science and Technology. 2015 Dec; 8(35):1-9.
  • Ali JSA, Ramesh GP. Comparison of PI and PID Controlled Wind Generator Fed Γ- Z Source based PMSM Drives. Indian Journal of Science and Technology. 2016 Jan; 9(1):1-6.

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