MSc (Operasionele Navorsing), North-West University, Mahikeng CampusGenichi Taguchi alerted statisticians to the importance of considering variation as well as target when designing experiments. The Box-Taguchi method ( a variation of his classical method) has placed little emphasis on C-N interactions. In this study, an attempt is made to understand the C-N interactions. To achieve this, simulated examples are used to demonstrate a modern day technique called Response Model/Combined Array. Also, Taguchi's designs call for a complete cross between a (possibly) fractionated so-called control array and a (possibly) fractionated so-called noise array. It is sought to explore the possibility of cutting down on the total number of exp...
Stabistical methods such as response surface methods and the robust design methods of Taguchi are co...
Success in experiments and/or technology mainly depends on a properly designed process or product. T...
Fractional factorial designs are used in a wide variety of disciplines as a means of studying how ch...
The paper reports a robust parameter design experiment, where we have used Taguchi's product array a...
The modeling of variation through interactions is appealing in crossed array design as it leads to g...
This paper presents a conceptually simple and resource efficient method for robust parameter design....
Standard factorial designs (one array) offer a cost-effective and information-efficient robust desig...
Robust parameter design is a statistical/engineering tool for performance variation reduction in ind...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.This e...
Robust parameter design, originally proposed by Taguchi [System of Experimental Design, vols. 1 and ...
Abstract This research proposes a simple, yet very effective, approach for solving the multi-respons...
Although multiple responses are quite common in practical applications, the robust design problem is...
This paper presents a case study on comparison of Design of Experiments (DOE) via traditional and Ta...
The Robust Design problem is frequently dealt with considering one response only, multiple responses...
<p>To identify the robust settings of the control factors, it is very important to understand how th...
Stabistical methods such as response surface methods and the robust design methods of Taguchi are co...
Success in experiments and/or technology mainly depends on a properly designed process or product. T...
Fractional factorial designs are used in a wide variety of disciplines as a means of studying how ch...
The paper reports a robust parameter design experiment, where we have used Taguchi's product array a...
The modeling of variation through interactions is appealing in crossed array design as it leads to g...
This paper presents a conceptually simple and resource efficient method for robust parameter design....
Standard factorial designs (one array) offer a cost-effective and information-efficient robust desig...
Robust parameter design is a statistical/engineering tool for performance variation reduction in ind...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.This e...
Robust parameter design, originally proposed by Taguchi [System of Experimental Design, vols. 1 and ...
Abstract This research proposes a simple, yet very effective, approach for solving the multi-respons...
Although multiple responses are quite common in practical applications, the robust design problem is...
This paper presents a case study on comparison of Design of Experiments (DOE) via traditional and Ta...
The Robust Design problem is frequently dealt with considering one response only, multiple responses...
<p>To identify the robust settings of the control factors, it is very important to understand how th...
Stabistical methods such as response surface methods and the robust design methods of Taguchi are co...
Success in experiments and/or technology mainly depends on a properly designed process or product. T...
Fractional factorial designs are used in a wide variety of disciplines as a means of studying how ch...