Assessment of quality activities using Taguchi's loss function

1998 ◽  
Vol 35 (1-2) ◽  
pp. 229-232 ◽  
Author(s):  
Soumaya Yacout ◽  
Jacqueline Boudreau
Keyword(s):  
Loss Function ◽  
Taguchi’S Loss Function

Taguchi's Loss Function in the Weight Quality of Products: Case Study of Cheese Making

2021 ◽  
pp. 453-466
Author(s):  
Nicolás Francisco Mateo-Díaz ◽  
Lidilia Cruz-Rivero ◽  
Luis Adolfo Meraz-Rivera ◽  
Jesús Ortiz-Martínez
Keyword(s):  
Loss Function ◽  
Cheese Making ◽  
Quality Of Products ◽  
Taguchi’S Loss Function

Variable sampling plans for normal distribution indexed by Taguchi's loss function

1997 ◽  
Vol 44 (6) ◽  
pp. 591-603 ◽  
Author(s):  
Ikuo Arizono ◽  
Akihiro Kanagawa ◽  
Hiroshi Ohta ◽  
Kyouko Watakabe ◽  
Kouji Tateishi
Keyword(s):  
Normal Distribution ◽  
Loss Function ◽  
Sampling Plans ◽  
Variable Sampling ◽  
Taguchi’S Loss Function

DETERMINATION OF AN OPTIMAL SETTING AND PRODUCTION RUN USING TAGUCHI'S LOSS FUNCTION

1999 ◽  
Vol 06 (04) ◽  
pp. 335-346 ◽  
Author(s):  
T. P. M. PAKKALA ◽  
M. A. RAHIM
Keyword(s):  
Loss Function ◽  
Continuous Production ◽  
Quadratic Loss ◽  
Process Mean ◽  
Optimal Production ◽  
Production Run ◽  
Optimal Setting ◽  
Random Shocks ◽  
Product Output ◽  
Taguchi’S Loss Function

This paper considers the problem of selecting an optimal setting of the process mean and an optimal production run for a continuous production process. The process is subject to gradual shifts in the process mean due to occurrences of some random shocks. The product output becomes nonconforming only when the process experiences a certain number of accumulated shocks. The changes in the process mean are assumed to follow a nonhomogeneous Poisson process. A quadratic loss function, which is a general form of Taguchi's loss function, is utilized for developing the economic model in determining an initial resetting process mean and an optimal production run. Some new results are derived and some interesting findings are reported.

Modelling and analysis of selective assembly using Taguchi's loss function

2008 ◽  
Vol 46 (15) ◽  
pp. 4309-4330 ◽  
Author(s):  
S. M. Kannan ◽  
A. K. Jeevanantham ◽  
V. Jayabalan
Keyword(s):  
Loss Function ◽  
Selective Assembly ◽  
Taguchi’S Loss Function

Development of a Robust Design Process Using a New Robustness Index

2005 ◽  
Author(s):  
K. H. Hwang ◽  
G. J. Park
Keyword(s):  
Design Process ◽  
Robust Design ◽  
Loss Function ◽  
The Other ◽  
The Third ◽  
Design And Manufacturing ◽  
Probability Of Success ◽  
Robustness Index ◽  
The Mean ◽  
Taguchi’S Loss Function

In product design and manufacturing, robust design leads to a product that has good quality. Robust design is reviewed in two categories: one is the process and the other is the robustness index. The process means efficient manipulation of the mean response and the variance. The robustness index indicates a measure of insensitiveness with respect to the variation. To improve existing methods, a three-step robust design (TRD) is proposed. The first step is “reduce the variance,” the second is “find multiple candidate designs,” and the third is “select the optimum robust design by using the robustness index,” Furthermore, a new robustness index is introduced in order to accommodate the characteristics of the probability of success in axiomatic design and the Taguchi’s loss function. The new robustness indices are compared with the existing ones. The developed robust design process is verified by examples and the results using the robustness index are compared with those of other indices.

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