A Process parameter optimization system for injection moulding of a LED lighting module

• Main Authors: LAI,Dong-Can, 賴東燦
• Other Authors: Chen,Wen-Chin
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22100CHPI5230003%22.&searchmode=basic

博士 === 中華大學 === 科技管理博士學位學程 === 100 === The application of the light-emitting diode (LED) lamp-module design normally focuses on LED arrangements of lamp modules which will unveil the illumination effectiveness of lamp lighting modules. However, it almost lacks the study of the process parameters optimization of optical lens module for the multi-quality characteristics. This dissertation is dedicated to obtaining the optimal molding parameter settings of multi-quality characteristics (i.e., view angle and luminous uniformity) integrating computer-aided engineering (CAE) and design of experiment (DOE) with a variety of optimization algorithms; and then verifying their feasibility by way of measuring the practical view angles and the values of luminous uniformity in a plastic injection molding machine. This research herein proposes a molding parameter optimization system based on multi-LED lighting lens design, which illustrates a complete and developed illumination system using DOE for screening the parameters, CAE for mold flow analysis, ANOVA for determining the significant factors, and RSM (response surface methodology) for optimizing the parameter settings in terms of multi-objective quality characteristics. In addition, the proposed system adopts the back-propagation neural network (BPNN) to create a quality predictor of LED-lens molding parameters. Moreover, two kinds of optimization algorithms: the GA (genetic algorithms) combined with PSO (particle swarm optimization) and the GA combined with DFP (Davidon-Flecher-Powell) employed to generate the optimal molding parameter settings and identify the practical (on-line) molding parameter settings. Finally, the realistic multi-LED lighting lens mold of injection molding can be developed, and the mold flow analysis and injection molding process can be implemented through CAE and practical molding parameter setting delved from the underlying optimization algorithms. The results of measuring the view angles and the values of luminous uniformity can be further used in verifying the validity of the study. In this research, the results show the ratio of search iterations between RSM combined with GA-DFP and RSM combined with GA is 1100 to 40 (1100:40); therefore, the search efficiency of RSM combined with GA is 30 times lower than RSM combined with GA-DFP. On the other hand, the promotion of quality characteristics for RSM combined with GA-DFP is 5 percents greater than RSM combined with GA. As mentioned achievements of the study, the proposed research is beneficial to enhance the technologies of design and production, and dramatically reduce the development cycle of multi-LED lighting lens