scholarly journals Optimization of multiple performance characteristics in turning using Taguchi’s quality loss function: An experimental investigation

2013 ◽  
Vol 4 (3) ◽  
pp. 325-336
Author(s):  
Ashok Kumar Sahoo ◽  
Tanmaya Mohanty
Keyword(s):  
Experimental Investigation ◽  
Loss Function ◽  
Performance Characteristics ◽  
Quality Loss ◽  
Quality Loss Function

Applying the Quality Loss Function in Healthcare

2008 ◽  
pp. 102-107
Author(s):  
Elizabeth Cudney ◽  
Bonnie Paris
Keyword(s):  
Health Care ◽  
Loss Function ◽  
Health Care Services ◽  
Quadratic Loss ◽  
Healthcare Industry ◽  
Quality Loss ◽  
Quality Loss Function ◽  
Quadratic Loss Function ◽  
Care Services ◽  
Fundamental Value

Using the quadratic loss function is one way to quantify a fundamental value in the provision of health care services: we must provide the best care and best service to every patient, every time. Sole reliance on specification limits leads to a focus on “acceptable” performance rather than “ideal” performance. This paper presents the application of the quadratic loss function to quantify improvement opportunities in the healthcare industry.

Research of Asymmetric Quality Loss Function with Triangular Distribution

2013 ◽  
Vol 655-657 ◽  
pp. 2331-2334 ◽  
Author(s):  
Qiu Jin ◽  
Shao Gang Liu
Keyword(s):  
Mathematical Models ◽  
Loss Function ◽  
Loss Functions ◽  
Optimum Process ◽  
Triangular Distribution ◽  
Quality Loss ◽  
Quality Loss Function ◽  
Process Mean ◽  
Asymmetric Quality Loss

The asymmetric quality loss functions with the triangular distribution for determining the optimum process mean are studied. The condition of using the linear and quadratic asymmetric quality loss function in the model is considered. The eight mathematical models under an asymmetric quality loss function with the triangular distribution based on the analysis of the linear and quadratic asymmetric quality loss function are presented. Finally, the validity of models is verified by the examples.

A robust tolerance optimization method based on fuzzy quality loss

2009 ◽  
Vol 223 (11) ◽  
pp. 2647-2653 ◽  
Author(s):  
Y Cao ◽  
J Mao ◽  
H Ching ◽  
J Yang
Keyword(s):  
Loss Function ◽  
Optimization Method ◽  
Quality Level ◽  
Tolerance Design ◽  
Quality Loss ◽  
Quality Loss Function ◽  
Proposed Model ◽  
Quality Grade ◽  
Practical Engineering ◽  
Manufacturing Time

Using the quality loss function developed by Taguchi, the manufacturing time and cost of a product can be reduced to improve the factory's competitiveness. However, the fuzziness in quality loss has not been considered in the Taguchi method. This article presents a fuzzy quality loss function model. First, fuzzy logic is used to describe the semantic of the quality, and the quality level is divided into several grades. Then the fuzzy quality loss function is developed utilizing the loss in monetary terms, which indicates the quality loss of each quality level and the normalized expected probability to each quality grade. Moreover, a new optimization model for tolerance design under fuzzy quality loss function is established. An example is used to illustrate the validity of the proposed model. The result shows that the proposed method is more flexible and can achieve the balance of quality and cost in tolerance design. It can be easily used in accordance with practical engineering applications.

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