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Kaohsiung, Taiwan

Chang W.-D.,Shu-Te University
Simulation Modelling Practice and Theory

This paper proposes a novel controller design method based on using artificial bee colony (ABC) algorithms for an unstable nonlinear continuously stirred tank reactor (CSTR) chemical system. Such CSTR process is highly nonlinear and its dynamic is significantly dominated by system parameters. It is a good challenge to access the controller design performance when the controller is applied in the CSTR control system. The commonly used proportional-integral-derivative (PID) controller is taken into account in this study, and tuning three PID control gains is carried out by the artificial bee colony algorithm. With the use of the optimal ABC algorithm, PID controller gains can be derived suitably by means of minimizing the cost function given in advance. Finally, several control operations are provided to confirm the feasibility and effectiveness of the proposed method. We also discuss the influence of algorithm initial conditions on the control performance with many different tests. © 2012 Elsevier B.V. All rights reserved. Source

The university performance assessment has become one of the most important debates for the universities in Taiwan. This study aims at developing an intellectual capital (IC) evaluation model to facilitate the understanding of their contribution to the university performances. A conceptual framework that incorporates IC with the university assessment scheme in Taiwan is proposed to construct the IC components as the central intangible resources of universities that are concentrated on its link to university performance ultimately. Analytic hierarchy process (AHP) is applied to formulate and prioritize the IC measurement indicators for constructing the IC evaluation model as decision guidelines under which the development and productive use of investments in intangible assets can be made. In this paper, a fuzzy approach is integrated with AHP method to make up the vagueness about the degree of importance of decision-makers on judgment. An illustrative example is provided of the proposed model for developing a visualized form of Shu-Te University distinction tree. © 2009 Elsevier Ltd. All rights reserved. Source

In this paper, we consider a deterministic economic order quantity model with generalized type demand, deterioration and unit purchase cost functions under two levels of trade credit policy. Our objective is to find the optimal values of selling prices, replenishment number and replenishment scheme which maximize the total profit over the finite planning horizon. We establish the inventory system and provide structural properties of the optimal solution that facilitate computation. A particle swarm optimization with constriction factor is coded and used to solve the mixed-integer nonlinear programming problem by employing the properties derived from this paper. At the end, some numerical examples are used to illustrate the features of the proposed model. © 2012 Elsevier B.V. All rights reserved. Source

In this paper, a modified particle swarm optimization (PSO) algorithm is developed for solving multimodal function optimization problems. The difference between the proposed method and the general PSO is to split up the original single population into several subpopulations according to the order of particles. The best particle within each subpopulation is recorded and then applied into the velocity updating formula to replace the original global best particle in the whole population. To update all particles in each subpopulation, the modified velocity formula is utilized. Based on the idea of multiple subpopulations, for the multimodal function optimization the several optima including the global and local solutions may probably be found by these best particles separately. To show the efficiency of the proposed method, two kinds of function optimizations are provided, including a single modal function optimization and a complex multimodal function optimization. Simulation results will demonstrate the convergence behavior of particles by the number of iterations, and the global and local system solutions are solved by these best particles of subpopulations. © 2015 Elsevier B.V. All rights reserved. Source

Tsai T.-N.,Shu-Te University
Robotics and Computer-Integrated Manufacturing

This paper presents industrial applications for improving the capability of the fine-pitch stencil printing process (SPP) based on the DMAIC framework and using Taguchi-based methodologies. SPP is widely recognized as the main contributor of soldering defects in a surface mount assembly (SMA). An inadequate volume of solder paste deposition or poor printing quality can cause soldering defects and lead to significant reworking and repairing costs. In practice, both the desired amount of solder paste volume (quantitative index) and printing quality (qualitative index) are preferably used to monitor the SPP for the reduction of soldering defects during the statistical control process (SPC), particularly for a fine-pitch solder paste printing operation. To continuously improve SPP capability, the DMAIC framework is followed and Taguchi-based methodologies are proposed under the considerations of single characteristic performance index (SCPI) and multiple characteristic performance indices (MCPI). The SCPI is optimized using the conventional Taguchi method. Then, a Taguchi fuzzy-based model is developed to optimize the SPP with the MCPI property. Optimizing a multi-response problem by the Taguchi method involves the engineers judgment which tends to increase the degree of uncertainty. The performance of these two approaches is compared through the process capability metric, and the material and factors significantly affecting the fine-pitch SPP performance are reported. © 2011 Elsevier Ltd. Source

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