Parameter Optimization in Mixed-Line Production Processes for On Cell Touch Panel Products---Case Study of a Color Filter Plant

• Main Authors: Yi-Chuan Liu, 劉義川
• Other Authors: Hui-Fen Chen
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/ng9gv4

碩士 === 中原大學 === 工業工程研究所 === 102 === This technical report explores the use of color filters (abbreviated as CF) process line operating mode to mixed line production On Cell touch sensor problem, an optimization method for parameter setting of machine equipment, and in the case G Company for case study. On Cell touch sensor the control program to import products made with CF mixed line production, its past experience in CF line processes can’t be applied to optimize the model requires the development of a new line of production and mixing parameters. G Company previously made trial and error method parameter optimization, can’t effectively achieve shorter production lead times and product defect rate control purposes, it is neces-sary to propose a set of scientific methods and can improve the yield. To solve this problem, research methods into three steps: (a) the reaction of customer complaint statistics touch products and selected factors adverse conditions are expected to improve (more commonly used only for a certain product specifications), (b) identify the cause Touch optimize product adverse conditions reasons related process and focus on machine equipment (only for a more common product specifications) and experimental de-sign (c) the use of focused machine equipment of important process parameters parameter value (only for certain over the Common product specifications). Where the second step is more complex, but also contains the method used: (i) fish-bone diagram: The purpose is to list the factors of production lines (human, machine, material, method) that might affect; (ii) the quality of cross-functional flowchart: The pur-pose of viewing the production process has to be repeated or whether the process can cause poor production procedures; (iii) Quality function deployment: the purpose is expected to improve the poor conditions, descending one by one narrow and converge to the production line may be adverse conditions machine equipment, parameters, and other factors; (iv) the causal matrix: The aim is by Plato proportional relationship after convergence, a list of key factors affecting processes; (v) Failure Mode Analysis (FMEA): The purpose of affecting the process of the key factors to do RPN values obtained detailed analysis of convergence observed a relatively high fraction of the project, we can focus on machine equipment, parameters. According to the above mentioned methods, found that the parameters of etching ma-chine is focused on improving the parameters, including etching machine of the spray pressure, the conveyor speed and the etchant temperature, found spray pressure which fac-tors are significant factors, while conveying speed and the temperature of the two factors was not significant, moreover considering etchant can be stored for longer without in-creasing the cost of heating elements, in addition to shortening the cycle time of the con-veyance under the consideration of the highest speed setting machine, increase the utiliza-tion rate of production can be improved, finally This combination of parameter values proposed three factors. For combinations of parameter values presented in this technical report, G companies small production test models produced from G's On Cell GP5A3054 product testing results to improve effectiveness analysis consists of two parts (1) Product defect rate analysis and (2) and R control chart analysis. analysis the Product defect ratio, that not improved yield before was 27.27% , sample size was 55 confidence interval (0.1550, 0.3903), the Product defect ratio improved to 2% for the 48 samples, 95% confidence interval for the Product defect ratio = (0.0196, 0.0596) lower average the Product defect ratio 25.27%. From the analysis and R control charts can be seen, there are more points before the improvement beyond the control limits, but many said the process beyond the center position offset spec-ifications far, the improved and R control charts in almost all control limits indicates the process is stable and close to the center of the process specification values. Then again re-duce manufacturing costs partly because lowering rates reduce the cost of making defective products and the amount of cost reduction will change as the utilization rate is different from, utilization rate of 100%, 80%, 60%, respectively, the relative availability Daily cost savings were 11,200,000 NT, 8,960,000 NT, 6,720,000 NT