Rotor machining is a traditional discrete manufacturing process, among which large amount of non-essential energy is being wasted. The machining process belongs to pipeline production, so a flow-shop scheduling model is built to optimize it. But when there are over three machines, this will be an NP-hard problem. We introduce an improved ant-colony algorithm to find the best solution and then use the real machining data to test it. The total energy consumption is reduced by over 10% and this shows the model and intelligent algorithm work well.
Measuring the content of hydrogen chloride (HCl) in exhaust gas used to take time and energy. In this paper, we introduce a new online monitoring system which can output real-time data to the monitoring center. The system samples and cools exhaust gas, and after a series of processing, it will be analyzed by a specific instrument. The core part of this system is remote terminal unit (RTU) which is designed on Cortex-A8 embedded architecture. RTU runs a scaled-down version of Linux which is a good choice of OS for embedded applications. It controls the whole processes, does data acquisition and data analysis, and communicates with monitoring center through Ethernet. In addition, through a software developed for windows, the monitoring process can be remotely controlled. The new system is quite beneficial for steel industry to do environment monitoring.
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