Research on the Temperature Detection Model of Netcom Products-Cable Modem as an Example

• Main Authors: Lin, Hung-Kang, 林弘剛
• Other Authors: Ma, Fang-Tz
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/wjy546

碩士 === 龍華科技大學 === 資訊管理系碩士班 === 107 === With the advancement of digital technology, the demand for cable modems (CM) is increasing day by day, so this study is aimed at the topics of the cable modem. The users placed the cable modem arbitrarily. If they placed in a poorly air-conditioned environment or an airless space, the products will overheat and it will shorten the service life of the products. In addition, the ambient temperature during transport also affects the cable modems. Therefore, the temperature detection of the cable modems is worth discussing the issue. This study investigated whether the environmental temperature changes affect the quality of cable modems. The test conditions were the operating temperatures of 0°C and 40°C; ambient humidity of 90%; storage temperature of -10°C. The test period were 2 hours and 4 hours, and the temperature data was read every one second. Firstly, the temperature line on the temperature recorder is attached to the cable modem, and then the cable modem was placed in the constant temperature and humidity machine which were set the temperature and humidity of the simulated environment. Then we performed the temperature test until the temperature reached a constant temperature, and finally the machine would calculate the test time. After the test was completed and the temperature data was collected after data analysis, the data was filled in the customer demand specification sheet. We evaluated whether the customers temperature standards were met. If they were not met, we recommended the R&D member to change the line design or replace the higher-priced components to meet the customers required specifications. This study conducted a real machine test of five sets of samples and collected temperature data for 2 hours and 4 hours of temperature measurement points. Then the statistical verification analysis of the study showed that there was no significant difference in the temperature data between the two. Therefore, this study suggests that case companies can shorten the product temperature detection time to 2 hours, which can save working time.