[[abstract]]Dual-response surface methodology is a powerful tool for simultaneously optimizing the mean and the variance of responses in quality engineering. In this article, we suggest a weighted mean squared error (MSE) approach to improve the optimization procedure. In addition, we propose a data-driven approach to determine the weights when the prior information is vague. This is based on the idea of an “efficient curve.” Examples are given to illustrate the superiority of the proposed method, as compared with other existing procedures.[[notice]]補正完畢[[journaltype]]國外[[booktype]]電子版[[countrycodes]]US
Abstract. Many quality engineering practitioners continue to have a considerable interest in impleme...
In Multi-Response Surface Optimization (MRSO), responses are often in conflict. To obtain a satisfac...
In today’s world, quality has been the key issue to the success of many multinational organizations....
In dual response surface optimization, minimizing weighted mean squared error (WMSE) is a simple yet...
Purpose: The purpose of this paper is to develop a systematic weighting procedure based on process c...
Dual response surface optimization considers the mean and the variation simultaneously. The minimiza...
WOS: 000234321500003Designing high-quality products and processes at low cost is an economic and tec...
Despite all the existing optimization schemes for solving dual response surface problem, the trade...
In dual-response-surface optimization, the mean and standard deviation responses are often in confli...
In recent years, response surface methodology (RSM) has brought many attentions of many quality engi...
Dual response surface optimization (DRSO), inspired by Taguchi’s philosophy, attempts to optim...
Quality engineering practitioners have great interest for using response surface method in a real si...
The dual response surface methodology is a widely used technique in industrial engineering for simul...
A dual-response surface optimization approach assumes that response surface models of the mean and s...
Nearly all real life systems have multiple quality characteristics where individual modeling and opt...
Abstract. Many quality engineering practitioners continue to have a considerable interest in impleme...
In Multi-Response Surface Optimization (MRSO), responses are often in conflict. To obtain a satisfac...
In today’s world, quality has been the key issue to the success of many multinational organizations....
In dual response surface optimization, minimizing weighted mean squared error (WMSE) is a simple yet...
Purpose: The purpose of this paper is to develop a systematic weighting procedure based on process c...
Dual response surface optimization considers the mean and the variation simultaneously. The minimiza...
WOS: 000234321500003Designing high-quality products and processes at low cost is an economic and tec...
Despite all the existing optimization schemes for solving dual response surface problem, the trade...
In dual-response-surface optimization, the mean and standard deviation responses are often in confli...
In recent years, response surface methodology (RSM) has brought many attentions of many quality engi...
Dual response surface optimization (DRSO), inspired by Taguchi’s philosophy, attempts to optim...
Quality engineering practitioners have great interest for using response surface method in a real si...
The dual response surface methodology is a widely used technique in industrial engineering for simul...
A dual-response surface optimization approach assumes that response surface models of the mean and s...
Nearly all real life systems have multiple quality characteristics where individual modeling and opt...
Abstract. Many quality engineering practitioners continue to have a considerable interest in impleme...
In Multi-Response Surface Optimization (MRSO), responses are often in conflict. To obtain a satisfac...
In today’s world, quality has been the key issue to the success of many multinational organizations....