Operation Monitoring Of Supporting Power System For Clean Room Facility

As a wide open facility,clean room in university undertakes scientific research tasks,as well as provides micro-fabrication and testing services for industries.Clean rooms are required to run 7×24 hours to ensure environmental stability including the temperature,humidity,air cleanliness,ventilation,supply of cooling water,DI water and processing gas etc.Thus it is required that the supporting system of the clean room operate efficiently and stably.Nowadays operation monitoring of the supporting system of clean room mainly relies on the daily patrol by engineers,which can't guarantee the real-time monitoring.Moreover,the noise of equipment on site is large,and the slight abnormal noise is hard to be detected.In this case,engineers were aware of a supporting system failure only after some environmental parameters of the clean room was out of line,which always generates fabrication process error and leads to additional loss.Therefore,it is in demand to explore an automatically monitoring strategy.This thesis developed an operation monitoring system for supporting equipments of clean room facility,which can recognize equipment failure in advance,improve the efficiency of equipment maintenance and prevent the potential fabrication process loss.In addition,the system can record the historical fault data.Through the data analysis it can give the preliminary analysis of the fault,judge their causes and improve the efficiency of the engineer's on-site troubleshooting.The hardware of the operation monitoring system mainly included vibration data acquisition module,microcontroller,wireless transmission module,etc.The software included PC software and Android software.The functions of the operation monitoring system had been demonstrated.Firstly,all the vibration data of these equipments were collected when they worked well,which acted as the calibration data for each equipment.Then the vibration data of each equipment was recorded in real time and compared with the calibration data to find potential failures.During the trial operation of the system,three equipment failures were located in time,namely,the motor failure of an exhaust fan,the failure of a delivery pump in the DI water system and the failure of a vacuum pump.Due to the timely warning,the fault can be handled in time and effectively,and their impact on the clean room facility is minimized.