Earticle

Robust design is an approach to reduce the performance variation of mutiple responses in products and processes. In fact, in many experimental designs require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

Taguchi's robust parameter design is an approach to reduce the performance variation of quality characteristics in products and processes. In robust design, the signal-to-noise ratio (SN ratio) was used to find the optimum condition to minimize the variation of quality characteristics as much as possible and bring the average of quality characteristics closer to the target value. In this paper, we propose a simultaneous optimization method based on a linear model of the SN ratio as a method to find the optimal condition of the control factor in case of multi-characteristics. In addition, the proposed method and the existing method were compared and studied by taking actual cases.

The Ponciri fructus immaturus (Poncirus trifoliata Rafinesque) has been used in oriental medicine for uterinecontraction, stomachache, abdominal distension and cardiovascular diseases. Two main compounds, poncirin and naringinwere successfully analyzed by high performance liquid chromatography (HPLC) and carried out method validation accordingto ICH guideline. A successful resolution and retention times were obtained with a C18 reversed phase column, at an 1 ㎖min−1 flow rate, with a gradient elution of a mixture of methanol, water and acetonitrile. Poncirin and naringin showed goodlinearity (R2> 0.999) in relatively wide concentration ranged. The recovery of each compound was 95.81 ~ 101.48% withR.S.D. values less than 1.0%. The application of ultrasound-assisted extraction was shown to be more efficient in extractingponcirin and naringin from Ponciri fructus immaturus. The predicted optimal poncirin and naringin yield were poncirin2.15%, naringin 1.65% under an extraction temperature of 40℃, an extraction time of 10 min in a solvent of 70% methanol.

This paper proposes a method to realize sensor function allocation and effective data aggregation simultaneously in wireless sensor networks. This method realizes dynamic allocation of sensor functions so as to balance the distribution of each sensor function in a target monitoring area. In addition, effective data aggregation is performed by using a tree network topology and time division multiple access (TDMA), which is a collision-free communication scheme. By comparing the results from the proposed method with the results from non-optimized methods, it can be validated that the proposed method is 1.7 times more efficient than non-optimized methods in distributing sensor functions. With this method, the network lifetime is doubled, and the number of data packets received at a base station is considerably increased by avoiding packet collisions.

Optimum condition of simultaneous saccharification and fermentation (SSF) of potato tuber mash for bioethanol production was examined. Central composite rotatable design(CCRD) and response surface methodology(RSM) were employed to find the optimal condition of SSF. Among four SSF factors such as saccharifying-enzyme(Spirizyme Fuel, Novo) dosage, ammonium sulfate content in medium, incubation temperature and yeast inoculum size, saccharifying-enzyme and incubation temperature were found to be important factors by using CCRD. Using RSM, the optimal saccharifying-enzyme dosage and incubation temperature were determined to be 1.45 AGU g-1 dry matter and 31.3℃, respectively. Using the optimal condition of SSF, 14.92% (v/v) ethanol was produced after 60 hr, and all the fermentable sugar was completely used up.

A novel simultaneous microwave-assisted extraction (MAE) and adsorbent treatment process was developed for recovering the anticancer agent paclitaxel from plant cell cultures and removing the plant-derived tar and waxy compounds. Furthermore, the process efficiency was maximized by optimizing the major process variables (extraction time, amount of absorbent, biomass-to-methanol ratio, extraction temperature). The optimum conditions of the simultaneous process for efficiency of the recovery of paclitaxel and the removal of tar and waxy compounds were 6 min for the extraction time, 4.5 (w/v) for the ratio of adsorbent to crude extract, 1:1 (w/v) for the biomass-to-methanol ratio, and 40℃ for the extraction temperature. Performing the simultaneous process under the optimum conditions could recover most (>99%) of the paclitaxel with the purity of ~22% could be recovered from hexane precipitation which was the following process. This result was similar to the efficiency (purity: ~20%, yield: ~95%) of the conventional process in which the paclitaxel recovery process is separated from the adsorbent treatment process. Therefore, it is expected that the conventional process could be simplified by simultaneously performing the recovery of paclitaxel and the removal of plant-derived tar and waxy compounds from plant cell cultures as one process, thus dramatically reducing the cost of the paclitaxel separation/purification process

Saccharification of seaweed, Laminaria japonica (sea tangle) is an essential process for the bioethanol fermentation. The saccharification was carried out by thermal acid hydrolysis and the treatment of isolated marine bacteria, Bacillus sp. JS-1. The 10% seaweed slurry was hydrolyzed with 0.2% (v/v) H2SO4 at 121℃ for 60 min. The hydrolysate was neutralized by 5N NaOH and further degradation was carried out by the 10% (v/v, 1 g dcw/L) Bacillus sp. JS-1. The reducing sugar concentration and viscosity under the optimal saccharification process were 45.6±5.0 g/L and 24.9 cp, respectively. Total yield of the reducing sugar from Laminaria japonica was 69.1%. The isolated marine bacteria was identified as Bacillus sp. by 16s ribosomal RNA sequencing and named Bacillus sp. JS-1. SSF was carried out for the bioethanol production. Thermal acid hydrolysate of 10% Laminaria japonica slurry was fermented at 30℃, 200 rpm for 136 hr by the addition of the 4% (v/v, 0.39 g dcw/L) Bacillus sp. JS-1 and 4% (v/v, 0.45 g dcw/L) yeast. The highest ethanol concentration of 7.7 g/L with 33% of theoretical yield was obtained from 10% Laminaria japonica slurry fermented with Pichia angoporae.

Bio-ethanol is regarded as an alternative fuel to replace fossil fuels. Sugar cane, corn, cassava and seaweed have been studied as biomass for bio-ethanol production. The seaweed is regarded a third generation biomass among them. Seaweed has advantages in fast growth of biomass and high productivity in large area. In this study, seaweed, Saccharina japonica (Sea tangle, Dasima) was used as biomass to produce bioethanol. The pretreatment was evaluated by thermal acid hydrolysis with H2SO4 and HCl. Optimal pretreatment condition was determined with 37.5mM H2SO4and10%(w/v) seaweedslurrybyautocalveat121℃ for 60 min. To Increase the yield of saccharfication, 0.45 g dcw/L of isolated marine bacteria Bacillus sp. were used often the pretreatment and 43 g/L of reducing sugar was obtained. Ethanol fermentation was performed using simultaneous saccharification and fermentation (SSF) and separate hydrolysis and fermentation (SHF) method with Pachysolen tannophilus KCTC 7937. The ethanol concentration of 6.3 g/L by SSF process and 6.0 g/L by SHF process were obtained respectively. Ethanol yields of 19.0 % and 18.1% of theoretical yield from total carbohydrate in Saccharina japonica were obtained by SSF and SHF, respectively.

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.

Microarray gene expression profiling technology is one of the most important research topics in clinical diagnosis of disease. Given thousands of genes, only a small number of them show strong correlation with a certain phenotype. To identify such an optimal subset from thousands of genes is intractable, which plays a crucial role when classify multiple-class genes express models from tumor samples. This paper proposes an efficient classifier design method to simultaneously select the most relevant genes using an intelligent genetic algorithm (IGA) and design an accurate classifier using Support Vector Machine (SVM). IGA with an intelligent crossover operation based on orthogonal experimental design can efficiently solve large-scale parameter optimization problems. Therefore, the parameters of SVM as well as the binary parameters for gene selection are all encoded in a chromosome to achieve simultaneous optimization of gene selection and the associated SVM for accurate tumor classification. The effectiveness of the proposed method IGA/SVM is evaluated using four benchmark datasets. It is shown by computer simulation that IGA/SVM performs better than the existing method in terms of classification accuracy.

The majority of previous studios on tolerance synthesis have viewed the issue as a design methodology to determine optimal component tolerances on behalf of a manufacturer. while meeting given assembly tolerance requirements Although a considerable amount of research has been done on this issue. a couple of important questions still remain unanswered First. how ran a design engineer quantitatively incorporate a customer's perception on a product quality into a tolerance synthesis scheme at the early design stage Second. how ran component tolerances and assembly tolerance be optimized in a simultaneous way? To answer these questions. this article presents the customer-driven concurrent tolerance synthesis which is facilitated by the notion of truncated distribution and the use of mathematical programming techniques. while adopting the major principles of Tagurhl philosophy. The work presented in the article is an effort to gain insight, which can be useful in practice when setting up guidelines for an overall tolerance synthesis.

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.

Robust design is an approach to reducing performance variation of response values in products and processes. In the Taguchl 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 response variable was considered. We propose how to simultaneously optimize multiple responses when there are correlations among responses, and when we use 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.

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 Vining and Myers (1990) and others. In these studies, only single respouse variable was considered. We propose how to simultaneously optimize multiple responses when there are correlations among responses.

The object of multiresponse optimization is to determine conditions on hte independent variables that lead to optimal or nearly optimal values of the response variables. Derringer and Suich (1980) extended Harrington's (1965) procedure by introducing more general transformations of the response into desirability functions. The core of the desirability a, pp.oach condenses a multivariate optimization into a univariate one. But because of the subjective nature of this a, pp.oach, inexperience on the part of the user in assessing a product's desirability value may lead to inaccurate results. To compensate for this defect, a weighted desirability function is introduced which takes into consideration the vriances of the responses.

In many response surface optimization problems for industrial processes, there are more than two responses of interest, and we want to find the optimal levels of the factors that influence the responses. This paper is to propose how to set up the desirability functions to find the optimum for a given set of data, and to propose how to analyse the data and the desirability functions to determine an optimal operating condition for the factors. To implement the proposed method in practice, a FORTRAN computer program was written and explained. Finally, an industrial example is illustrated to explain the proposed technique and the source list of the computer program is attached for the users.

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 response variable was considered. We propose how to simultaneously optimize multiple responses when there are correlations among responses, and when we use the combined-array approach to assign control and noise factors.