• Journal of the Korean Data and Information Science Society
• /
• v.14 no.3
• /
• pp.545-551
• /
• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper we propose how to simultaneously optimize multiple quality characteristics using the principal component analysis of multivariate statistical analysis. An example is illustrated to compare it with already proposed method.

• 한국데이터정보과학회:학술대회논문집
• /
• 2004.04a
• /
• pp.131-139
• /
• 2004

Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

• Journal of Integrative Natural Science
• /
• v.6 no.1
• /
• pp.39-45
• /
• 2013

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. In the Taguchi parameter design, the product-array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined-array approach, was studied. In these studies, only single quality characteristic (or response) was considered. In this paper we propose how to simultaneously optimize for multiple quality characteristics (or multiresponse) using desirability function when we used the combined-array approach to assign control and noise factors.

• Journal of Korean Society for Quality Management
• /
• v.24 no.2
• /
• pp.142-157
• /
• 1996

Robust design in industry is an approach to reducing performance variation of quality characteristic values in products and processes. In the Taguchi type robust design, the product array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. In this paper, for the combined array approach to assign control and noise factors, we propose how to simultaneously optimize multiple quality characteristics. Two examples are illustrated to show the difference between the product-array approach and the combined-array approach.

• International Journal of Precision Engineering and Manufacturing
• /
• v.8 no.4
• /
• pp.10-15
• /
• 2007

Taguchi methods have been used for a long time to improve the product quality and process performance of a manufacturing system, Few researchers have applied this methodology in laser beam cutting (LBC) of sheet metals and found the considerable improvement in cut qualities. In all experimental investigations of LBC so far, the objective was to optimize the single quality characteristic at a time. In this paper the simultaneous optimization of multiple quality characteristics such as Kerf width and material removal rate (MRR) during pulsed Nd:YAG LBC of thin sheet of magnetic material (high Silicon-steel) has been presented using Taguchi's quality loss function. The results show the considerable improvement in multiple S/N ratio as compared to initial cutting condition. Also, the comparison of results from single and multi-objective optimization have been presented and it was found that the loss in quality is always possible shifting from single quality to multiple quality optimization.

• Journal of Korean Institute of Industrial Engineers
• /
• v.24 no.2
• /
• pp.287-296
• /
• 1998

We often have multiple quality characteristics to develop, improve and optimize industrial processes and products. It is not easy to find optimal control factor setting when there are multiple quality characteristics, since there will be conflict among the selected levels of the control factors for each individual quality characteristic. In this paper we propose a desirability function approach and devise a scheme which gives a systematic way of solving multiple quality characteristic problems. A numerical example is provided.

• Journal of Korean Society for Quality Management
• /
• v.27 no.2
• /
• pp.126-142
• /
• 1999

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. Taguchi parameter design has a great deal of advantages but it also has some disadvantages. The various research efforts aimed at developing alternative methods. In the Taguchi parameter design, the product-array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined-array approach, was suggested by Welch et. al. ( 1990) and studied by others. In these studies, only single quality characteristic was considered. In this paper we propose how to simultaneously optimize multiple quality characteristics using desirability function when we used the combined-array approach to assign control and noise factors. An example is illustrated to show the difference between the Taguchi's product-array approach and the combined-array approach.

• 한국데이터정보과학회:학술대회논문집
• /
• 2002.06a
• /
• pp.97-106
• /
• 2002

Taguchi parameter design, the product-array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined-array approach, was suggested by Welch et. al. and studied by others. In these studies, only single quality characteristic was considered. We propose how to simultaneously optimize multiple quality characteristics using desirability function when we used the combined-array approach to assign control and noise factors. An example is illustrated to the combined-array approach.

• Journal of Korean Institute of Industrial Engineers
• /
• v.43 no.2
• /
• pp.127-134
• /
• 2017

For product or process design and development, it is common to optimize multiple responses (characteristics) based on experimental data. To determine optimal conditions, we need to design the experiment, estimate a proper model for each response, and optimize the multiple responses simultaneously. There are several techniques and many research results on optimizing multiple responses simultaneously, when the experimental data are available. However, the experimental design issue for optimizing multiple responses has not been discussed yet. This paper proposes some idea on how to plan screening design when requirements for multiple performance characteristics are to be met in developing new products. A screening design procedure is developed for securing the requirements of multiple responses. Initial design factors are classified into three categories; specific, non-conflicting common, and conflicting common. After screening experiments, follow-up design region search method is suggested with respect to the most unsatisfied or important response, or overall desirability. A case study on a synthesis of melamine formaldehyde resin is presented to illustrate the procedure and to show the validity of the approach.

• Journal of Korea Multimedia Society
• /
• v.10 no.12
• /
• pp.1632-1644
• /
• 2007

Wireless Mesh Networks aim to attain large connectivity with minimum performance degradation, as network size is increase. As such, scalability is one of the main characteristics of Wireless Mesh Networks that differentiates it from other wireless networks. This characteristic creates the need for bandwidth efficiency strategies to ensure that network performance does not degrade as the size of the network increase. Several researches have been done to realize mesh networks. However, the researches conducted were mostly focused on a per TCP/IP layer basis. Also, the studies on bandwidth efficiency and bandwidth improvement are usually dealt with as separate issues. This paper aims to simultaneously study bandwidth efficiency and improvement. Aside from optimizing the bandwidth given a fixed capacity, the capacity is also increased using results of physical layer studies. In this paper, the capacity is improved by using the concept of non-overlapping channels for wireless communication. A channel allocation scheme is conceptualized to choose the transmission channel that would optimize the network performance parameters with consideration of chosen Quality of Service (QoS) parameters. Network utility maximization is used to optimize the bandwidth after channel selection. Furthermore, a routing scheme is proposed using the results of the network utilization method and the channel allocation scheme to find the optimal path that would maximize the network gain.