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Sensor-enabled PCBs to aid right first time manufacture through defect prediction

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conference contribution
posted on 04.02.2016, 11:10 authored by Richard Sharpe, Guy Banwell, Paul ConwayPaul Conway, Andrew WestAndrew West
© 2014 IEEE. Prevention of defects can reduce waste and aid lean strategies such as right first time manufacture. The prediction of defects leads to prevention; however accurate prediction requires a high understanding of the domain and mechanics of each defect. For a prediction simulation to adapt to a manufacturing line's conditions requires timely information about the products being manufactured. In this paper, research into the addition of a sensory circuit to a PCB in order to monitor defects through its manufacture into a PCBA is outlined. Manual handling and the number of thermal cycles are attributors to many of a product's potential defects. The use of an accelerometer and temperature sensor in a circuit alongside a processor and RFID chip is presented. The use of RFID allows the board to communicate to the manufacturing line, increasing the current state of intelligence for this type of product. The use of an RFID chip also allows data storage for both manufacturing information as well as sensory information. This intelligence capability could be added to the PCB in one of two ways; embedding within the layers of the board or by integrating into a pallet or carrier which the PCB will be associated with throughout its manufacture.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Proceedings of the 16th Electronics Packaging Technology Conference, EPTC 2014

Pages

366 - 371

Citation

SHARPE, R. ...et al., 2014. Sensor-enabled PCBs to aid right first time manufacture through defect prediction. Presented at the 16th Electronics Packaging Technology Conference, (EPTC 2014), Singapore, 3-5th Dec., pp. 366-371.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2014

Notes

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISBN

9781479969944

Language

en

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