scholarly journals Effects of granulation process variables on the physical properties of dosage forms by combination of experimental design and principal component analysis

2019 ◽  
Vol 14 (3) ◽  
pp. 287-304 ◽  
Author(s):  
Prakash Thapa ◽  
Du Hyung Choi ◽  
Min Soo Kim ◽  
Seong Hoon Jeong
2014 ◽  
Vol 14 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Thella Babu Rao ◽  
A. Gopala Krishna

AbstractThe present investigation proposes the optimization of the wire electrical discharge machining process for machining ZC63/SiCP metal matrix composite. SiC particulate size and its percentage with the matrix are considered as the process variables along with the most significant WEDM variables such as pulse-on time, pulse-off time and wire tension. In view of quality cut, surface roughness, metal removal rate and kerf are considered as the process responses. Since, these responses are correlated with each other and they need to be optimized simultaneously. Therefore, the problem is treated as multi-response optimization problem. Principal component analysis (PCA) has been implemented to convert the multi-objective optimization problem in to single objective optimization problem by converting the multiple correlated responses in to the total quality index. Taguchi's robust optimization technique has been adopted to derive the set optimal process parameters which maximize the total quality index. The derived optimal process responses are confirmed with the experimental validation tests. ANOVA is conducted find the importance of the chosen process variables on the overall quality of the machined component. The practical possibility of the obtained optimal process performance is observed using SEM studies.


2019 ◽  
Vol 15 (6) ◽  
pp. 155014771985758 ◽  
Author(s):  
Chen Xu ◽  
Fei Liu

Multivariate statistics process monitoring can achieve dimensionality reduction and latent feature extraction on process variables. However, process variables without beneficial information may affect the monitoring performance. This article proposes a distributed principal component analysis method based on the angle-relevant variable selection for plant-wide process monitoring. The directions of principal components are utilized to construct the sub-blocks, where the variables in each sub-block are determined by angle. After establishing the principal component analysis model in each sub-block, the monitoring results are fused by Bayesian inference. The simulation results show that the proposed method can select the responsible variables effectively and enhance the monitoring performance.


Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1167
Author(s):  
Han Tang ◽  
Changsu Xu ◽  
Yeming Jiang ◽  
Jinwu Wang ◽  
Zhenhua Wang ◽  
...  

The physical properties of maize seeds are closely related to food processing and production. To study and evaluate the characteristics of maize seeds, typical maize seeds in a cold region of North China were used as test varieties. A variety of agricultural material test benches were built to measure the maize seeds’ physical parameters, such as thousand-grain weight, moisture content, triaxial arithmetic mean particle size, coefficient of static friction, coefficient of rolling friction, angle of natural repose, coefficient of restitution, and stiffness coefficient. Principal component and cluster comprehensive analyses were used to simplify the characteristic parameter index used to judge the comprehensive score of maize seeds. The results showed that there were significant differences in the main physical characteristics parameters of the typical maize varieties in this cold area, and there were different degrees of correlation among the physical characteristics. Principal component analysis was used to extract the first three principal component factors, whose cumulative contribution rate was over 80%, representing most of the information of the original eight physical characteristic parameters, and had good representativeness and objectivity. According to the test results, the classification standard of the evaluation of the physical characteristics of 15 kinds of maize seeds were determined, and appropriate evaluations were conducted. The 15 kinds of maize seeds were clustered into four groups by cluster analysis, and the physical characteristics of each groups were different. This study provides a new idea for the evaluation and analysis of the physical properties of agricultural materials, and provides a new method for the screening and classification of food processing raw materials.


2015 ◽  
Vol 27 (6) ◽  
pp. 922-939 ◽  
Author(s):  
Mouna Gazzah ◽  
Boubaker Jaouachi ◽  
Laurence Schacher ◽  
Dominique Charles Adolphe ◽  
Faouzi Sakli

Purpose – The purpose of this paper is to predict the appearance of denim fabric after repetitive uses judging the denim cloth behavior and performance in viewpoint of bagging ability. Hence, it attempts to carry out the significant inputs and outputs that have an influence on the bagging behaviors using the Principal Component Analysis (PCA) technique. In this study, the Kawabata Evaluation System parameters such as the frictional characteristics, the bending, compression, tensile and shear parameters are investigated to propose a model highlighting and explaining their impacts on the different bagging properties. To improve the obtained results, the selected significant inputs are also analyzed within their bagging properties using Taguchi experimental design. The linear regressive models prove the effectiveness of the PCA method and the obtained findings. Design/methodology/approach – To investigate the mechanical properties and their contributions on the bagging characteristics, some denim fabrics were collected and measured thanks to the Kawabata evaluation systems (KES-FB1, KES-FB2, KES-FB3 and KES-FB4). These bagging properties were further analyzed applying the method of PCA to acquire factor patterns that indicate the most important fabric properties for characterizing the bagging behaviors of different studied denim fabric samples. An experimental design type Taguchi was, hence, applied to improve the results. Regarding the obtained results, it may be concluded that the PCA method remained a powerful and flawless technique to select the main influential inputs and significant outputs, able to define objectively the bagging phenomenon and which should be considered from the next researches. Findings – According to the results, there are good relationships between the Kawabata input parameters and the analyzed bagging properties of studied denim fabrics. Indeed, thanks to the PCA, it is probably easy to reduce the number of the influent parameters for three reasons. First, applying this technique of selection can help to select objectively the most influential inputs which affect enormously the bagged fabrics. Second, knowing these significant parameters, the prediction of denim fabric bagging seems fruitful and can undoubtedly help researchers explain widely this complex phenomenon. Third, regarding the findings mentioned, it seems that the prevention of this aesthetic phenomenon appearing in some specific zones of denim fabrics will be more and more accurate. Practical implications – This study is interesting for denim consumers and industrial applications during long and repetitive uses. Undoubtedly, the denim garments remained the largely used and consumed, hence, this particularity proves the necessity to study it in order to evaluate the bagging phenomenon which occurs as function of number of uses. Although it is fashionable to have bagging, the denim fabric remains, in contrast with the worsted ones, the most popular fabric to produce garments. Moreover, regarding this characteristic, the large uses and the acceptable value of denim fabrics, their aesthetic appearance behavior due to bagging phenomenon can be analyzed accurately because compared to worsted fabrics, they have a high value and the repetitive tests to investigate widely bagged zones may fall the industrial. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. This can help understanding why residual bagging behavior remained after garment uses due to the internal stress and excessive extensions. Regarding the selected influential inputs and outputs relative to bagging behaviors, there are some practical implications that have an impact on the industrial and researchers to study objectively the occurrence of this aesthetic phenomenon. Indeed, this study discusses the significance of the overall inputs; their contributions on the denim fabric bagged zones aims to prevent their ability to appear after uses. Moreover, the results obtained regarding the fabric mechanical properties can be useful to fabric and garment producers, designers and consumers in specifying and categorizing denim fabric products, insuring more denim cloth use and controlling fabric value. For applications where the subjective view of the consumer is of primary importance, the KES-FB system yields data that can be used for evaluating fabric properties objectively and prejudge the consumer satisfaction in viewpoint of the bagging ability. Therefore, this study shows that by measuring shear, tensile and frictional parameters of KES-FB, it may be possible to evaluate bagging properties. However, it highlights the importance and the significance of some inputs considered influential or the contrast (non-significant) in other researches. Originality/value – This work presents the first study analyzing the bagged denim fabric applying the PCA technique to remove the all input parameters which are not significant. Besides, it deals with the relationship developed between the mechanical fabric properties (tensile, shear and frictional stresses) and the bagging properties behavior. To improve these obtained relationships, for the first time, the regression technique and experimental design type Taguchi analysis were both applied. Moreover, it is notable to mention that the originality of this study is to let researchers and industrials investigate the most influential inputs only which have a bearing on the bagging phenomenon.


1999 ◽  
Vol 210 (1) ◽  
pp. 73-76 ◽  
Author(s):  
Miguel Frau ◽  
Susana Simal ◽  
Antoni Femenia ◽  
Esther Sanjuán ◽  
C. Rosselló

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