Page 201 - Six Sigma for electronics design and manufacturing

Six Sigma for Electronics Design and Manufacturing
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5.4.2 Corrective action for process capability
problems
The previous section described a methodology for calculating process
capability for new parts. If a process capability study was done with
existing parts, and it was found to be unacceptable, the following sug-
gestions might be followed to bring the process capabilities in compli-
ance with six sigma or Cpk targets:
Can specifications be amended (enlarged) and still meet system re-
quirements?
Can increased training, corrective action processes, design of exper-
iments, or other quality improvement tools be used to increase
process capability?
If current processes remains not capable, can new equipment or
outside suppliers be investigated?
5.5 Conclusions
This chapter showed how to handle the common problem of applying
six sigma quality methodology to small as well as large production
volumes. Statistical tools such as moving range and the z, t, f, and 2
distributions can be used to quantify the attributes of the population
distribution for average and standard deviations based on samples
taken. Many examples were given to demonstrate sampling tech-
niques and their relationship to populations. Process capability as
well as gauge capability were also demonstrated with formulas, ex-
amples, and case studies. Finally, the process capability applications
in short- versus long-term production were also shown, with examples
and strategies for handling process capability in the prototype as well
as long-term production.
5.6 References and Bibliography
Burr, I. Engineering Statistics and Quality Control. New York: McGraw Hill,
1953.
Bronshtein, I. and Semendyayev, K. Handbook of Mathematics. Leipzig: Ver-
lag Press, 1985.
Ducan, A. J. Quality Control and Industrial Statistics, 4th ed. Homewood, IL:
Richard D. Irwin. 1995.
Johnson, R., Probability and Statistics for Engineers, 5th ed. Englewood
Cliffs, NJ: Prentice-Hall, 1994.
Walpole R. and Myers, R. Probability and Statistics for Engineers and Scien-
tists. New York: Macmillan, 1993.