| injection_molding {stepjglm} | R Documentation |
Data from Injection molding experiment
Description
The experiment was performed to study the influence of seven controllable factors and three noise factors on the mean value and the variation in the percentage of shrinkage of products made by injection molding.
Usage
data(injection_molding)
Format
A data frame containing 32 rows and 11 variables.
The responses were percentages of shrinkage of products made by injection molding (Y).
Controllable factors:
A: cycle time
B: mould temperature
C: cavity thickness
D: holding pressure
E: injection speed
F: holding time
G: gate size
At each setting of the controllable factors, four
observations were obtained from a 2^{(3-1)}
fractional factorial with three noise factors:
M: percentage regrind
N: moisture content
O: ambient temperature
Details
The data set considered is well known in the literature of industrial experiments and has been analyzed by several authors such as Engel (1992), Engel and Huele (1996) and Lee and Nelder (1998). The experiment was performed to study the influence of seven controllable factors and three noise factors on the mean value and the variation in the percentage of shrinkage of products made by injection molding.Noise factors are fixed during the experiment but are expected to vary randomly outside the experimental context.
The aim of the experiment was to determine the process parameter settings so that the shrinkage percentage was close to the target value and robust against environmental variations.
References
Engel, J. (1992). Modeling variation in industrial experiments. Applied Statistics, 41, 579-593.
Engel, J. and Huele, A. F. (1996). A generalized linear modeling approach to robust Design. Technometrics, 38, 365-373.
Lee, Y. and Nelder, J.A. (1998). Generalized linear models for analysis of quality improvement experiments. The Canadian Journal of Statistics, 26, 95-105.
Examples
data(injection_molding)
head(injection_molding)