Neural network modeling with confidence bounds: A case study on the solder paste deposition process

Siu Lau Ho, M. Xie, L. C. Tang, K. Xu, T. N. Goh

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)

Abstract

The formation of reliable solder joints in electronic assemblies is a critical issue in surface mount manufacturing. Stringent control is placed in the solder paste deposition process to minimize soldering defects and achieve high assembly yield. Time series process modeling of the solder paste quality characteristics using neural networks (NN) is a promising approach that complements traditional control charting schemes deployed on-line. In this paper, we present the study of building a multilayer feedforward neural network for monitoring the solder paste deposition process performance. Modeling via neural networks provides not only useful insights in the process dynamics, it also allows forecasts of future process behavior to be made. Data measurements collected on ball grid array (BGA) and quad flat pack (QFP) packages are used to illustrate the NN technique and the forecast accuracies of the models are summarized. Furthermore, in order to quantify the errors associated with the forecasted point estimates, asymptotically valid prediction intervals are computed using nonlinear regression. Simulation results showed that the prediction intervals constructed give asonably satisfactory coverage percentages as compared to the nominal confidence levels. Process control using NN with confidence bounds provides more quality information on the performance of the deposition process for better decision making and continuous improvement.
Original languageEnglish
Pages (from-to)323-332
Number of pages10
JournalIEEE Transactions on Electronics Packaging Manufacturing
Volume24
Issue number4
DOIs
Publication statusPublished - 1 Oct 2001
Externally publishedYes

Keywords

  • Modeling and forecasting
  • Neural networks
  • Nonlinear regression
  • Prediction intervals
  • Process control
  • Solder paste deposition

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

Cite this