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The conditions for the preparation of activated carbon(AC) from corn cob(CC) treated with NaHCO3 using microwave radiation were optimized through response surface methodology (RSM) and central composite design (CCD).The effects of the radiation power, radiation time, and impregnation ratio were studied from the adsorption capacity on methylene blue dye(MB), and yield results.From the analysis of variance...
The prescription of pomelo beverage was optimized to maximize the sensory score in this study. A Box-Behnken design of response surface methodology involving the addition amount of pomelo juice, addition amount of citric acid, addition amount of sugar, was used, and second-order model for the sensory score was employed to generate the response surface. The optimum condition for the process was determined...
Different numerical optimization strategies are used to find an optimized parameter setting for the sheet metal forming process. Metamodels based on responses from numerical experiments may form efficient approximations to functions in engineering analysis. They can improve the efficiency of engineering optimization substantially by uncoupling computationally expensive analysis models and (iterative)...
Response surface method (RSM) is a set of mathematical and statistical methods for experimental design and evaluating the effects of variables and searching optimum conditions of variables to predict targeted responses. Oestrone (E1) is one of the most important steroid estrogens in sewage and waterbody. An internal standard method of HPLC-MS-MS for E1 is established with its operational parameters...
The paper reports three examples of best industrial practice showing the substantial benefits gained in terms of time-to-market reduction when virtual prototyping is enhanced by statistical and stochastic methodologies. These examples from a microelectronics setting of high volume component and module manufacturing deal with different fields: i) ball grid array (BGA) design optimization based on sophisticated...
Model selection strategy is investigated for sequential optimization method (SOM) to deal with the optimization design problems of electromagnetic devices. Four kinds of approximate models, response surface model, radial basis function model, Kriging model and artificial neural network model are considered respectively. From the analysis of two mathematic test functions and an IEEE TEAM benchmark...
This paper describes an experiment exploring the potential of kriging metamodeling for multi-objective simulation optimization. The experiment studies an (s, S) inventory system with the objective of finding the optimal values of reorder point s and maximum inventory level S so as to minimize the total cost of the system while maximizing customer satisfaction. This experiment compares classical response...
Metamodels based on responses from designed (numerical) experiments may form efficient approximations to functions in engineering analysis. They can improve the efficiency of engineering optimization substantially by uncoupling computationally expensive analysis models and (iterative) optimization procedures. This paper investigated the kriging metamodel approach. In order to prove accuracy and efficiency...
An approach which combines PERT and CPM in one model to solve project scheduling problems, is introduced. Due to the stochastic nature of activity time and cost for PERT and CPM networks, robust design for project scheduling via statistical method is introduced in the presented approach. The statistical method, such as response surface methodology (RSM), is used to develop a rationale of the time-cost...
Screening latent defects in a wafer test process is very important task in both reducing memory manufacturing cost and enhancing the reliability of emerging package products such as SIP, MCP, and WSP. In terms of the package assembly cost, these package products are required to adopt the KGD (known good die) quality level. However, the KGD requires a long burn-in time, added testing time, and high...
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