operational analysis of a select spinning mill - International ...

Table 5
Coefficients:
Standard T
Parameter Estimate Error Statistic P-Value
CONSTANT -20.9637 0.963011 -21.7689 0.0000
s2rawmaterial consumption 0.657836 0.00502045 131.031 0.0000
s2yield 31.8798 1.45079 21.9741 0.0000
The fitted multiple regression models involving the explanatory variables are given below:
S2YARN-PRODUCTION = -20.9637 + 0.657836*S2RAWMATERIAL CONSUMPTION +
31.8798*S2YIELD.
From the model it is observed that there is a positive relationship between yarn
production and raw material consumption. It shows that yarn production would increase by 0.66
units, if the raw material consumption increases by 1 unit assuming the yield remains the same.
It also shows that there is a positive relationship between yield and yarn production. That is the
yarn production would increase by 31.88 units if the yield increases by 1 unit assuming the raw
material consumption remains the same. The validity of the model has been tested by ANOVA.
The output of the ANOVA is presented as :
Table No.6
Analysis of Variance
Source Sum of Squares Df Mean Square F-Ratio P-Value
Model 142.31 2 71.1552 8996.15 0.0000
Residual 0.0553666 7 0.00790951
Total (Corr.) 142.366 9
Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant
relationship between the variables at the 95.0% or higher confidence level. Hence fitted model
is the most suitable model to describe the relationships of the variables.
Table .7-Related Statistics
R2
Standard
Mean Absolute Error Dubin-Watson Statistics
Error of Estimate
99.9611 percent 0.0889355 0.0593909 3.17366 (P=0.9427)
The R-Squared statistic indicates that the model as fitted explains 99.9611% of the
variability in production. The standard error of the estimate shows the standard deviation of the
residuals to be 0.0889355. The mean absolute error (MAE) of 0.0593909 is the average value of
the residuals. The Durbin-Watson (DW) statistic tests the residuals to determine if there is any
significant correlation based on the order in which they occur. Since the P-value is greater than
0.05, there is no indication of serial autocorrelation in the residuals at the 95.0% confidence level
COBB DOUGLAS PRODUCTION FUNCTION:
Generally for the same level of input factors, everyone should get almost the same level
of output. In spinning mills the production and cost related to the spinning department has been
considered as the important indicator of the operational performance. Therefore production and
cost related to the spinning department has been taken for the analysis. To test production
achievement of the companies, the Cobb-Douglas Production Function is employed. The Cobb-
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