Advertisement

Journal of Materials Science

, Volume 29, Issue 7, pp 1731–1738 | Cite as

The effect of production variables on the strength of brass/Sn-Pb-Sb solder joints: A statistical analysis

  • M. Evans
Papers
  • 42 Downloads

Abstract

Tomlinson and Cooper's data on solder joint strength have been used to illustrate the additional benefits, in terms of useful results, that can be obtained from the application of stepwise regression techniques to production process data. This technique provides extra quantitative information in three main areas. First, those production variables of importance can be identified and the exact effect of such variables on joint strength determined. Secondly, linear versus non-linear association between such production variables and joint strength can be tested. Finally, the degree and significance of interaction effects can be estimated. Using this stepwise regression technique it was found, contrary to Tomlinson and Cooper's paper, that the relationship between strength and antimony content was, in all cases, non-linear, whilst all other relationships were linear. The significant main effect variables were furnace cooling, cooling time and antimony content with the latter being the most important explanatory variable. However, the effects of these and other interaction explanatory variables were not minor as Tomlinson and Cooper suggest. Important interaction effects were also identified particularly so between gap size and antimony content.

Keywords

Interaction Effect Explanatory Variable Antimony Solder Joint Effect Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    W. J. Tomlinson and G. A. Cooper, J. Mater. Sci. 21 (1986) 1730–1734.CrossRefGoogle Scholar
  2. 2.
    D. F. Hendry in “Economic Modelling”, edited by P. Omerod (London, 1979) Ch. 9.Google Scholar
  3. 3.
    W. Mendenhall and T. Sincich, “Statistics for the Engineering and Computer Sciences,” 2nd Edn (Maxwell-Macmillan, London, 1989) Ch. 12.Google Scholar
  4. 4.
    T. S. Breusch, Austral. Econom. Papers 17 (1978) 334–355.CrossRefGoogle Scholar
  5. 5.
    H. White, Econometrica 48 (1980) 817–838.CrossRefGoogle Scholar
  6. 6.
    M. C. Jarque and K. A. Bera, Econom. Lett. 6 (1980) 255–259.CrossRefGoogle Scholar
  7. 7.
    Minitab Reference Manual (Minitab Inc., State College, PA, 1989.Google Scholar

Copyright information

© Chapman & Hall 1994

Authors and Affiliations

  • M. Evans
    • 1
  1. 1.Department of Materials EngineeringUniversity College SwanseaSwanseaUK

Personalised recommendations