The fuzzy regression has been found effective in modeling the relationship between the dependent variable and independent variables when a high degree of fuzziness is involved and only a few data sets are available for model building. This research, therefore, proposes an approach for optimizing multiple responses in the Taguchi method using fuzzy regression and desirability function. The stati...

Optimization for enhanced phytase production by Aspergillus oryzae SBS50 in submerged fermentation was investigated using Taguchi design. In first step design, starch, beef extract, magnesium sulphate, ferrous sulphate and Tween 80 were identified as significant factors affecting phytase production. These significant factors were further optimized at four different levels using a second Taguchi...

Wire Electrical Discharge Machining (WEDM) is a non-traditional thermo-electric process capable of machining hard materials of highly complex three dimensional shapes. In this paper, the dry WEDM experimentation is conducted using oxygen as a dielectric medium. The deionized water is replaced by the oxygen as a dielectric medium to ameliorate the environmental impact in the machining surroundin...

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and t...

     The quadratic loss function has been used by decision-theoretic statisticians and economists for many years.  In this paper  the estimation of scale parameter under a bounded loss function, which is adequate for assessing quality and quality improvement, is considered with restriction to the principles of invariance and risk unbiasedness. An implicit form of minimum risk scale equivariant ...

achieving optimal production cycle time for improving manufacturing processes is one of the common problems in production planning. during recent years, different approaches have been developed for solving this problem, but most of them assume that mean quality characteristic is constant over production run length and sets it on customer’s target value. however, the process mean may drift from ...

the problems of sequential change-point have several important applications in quality control, signal processing, and failure detection in industry and finance. we discuss a bayesian approach in the context of statistical process control: at an unknown time $tau$, the process behavior changes and the distribution of the data changes from p0 to p1. two cases are considered: (i) p0 and p1 are fu...

Some examples of absurd uniformly minimum variance unbiased estimators are discussed. Two reasons, argued in the literature, for having such estimators are lack of enough information in the available data and property of unbiasedness. In this paper, accepting both of these views, we show that an appropriate choice of loss function using a general concept of unbiasedness leads to risk unb...