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Stable production processes, high efficiency and good product quality are the main objectives of the sintering industry. Taking the whole sintering production process as the research object, cutting-edge intelligent algorithms and classical sintering theories are applied to establish a sintering batch optimization model, a sinter layer permeability prediction model, a sintering end point optimization control model and a sinter quality prediction and evaluation model respectively, supported by a large amount of historical data, so that the model has reasonably accurate results as well as strong practicality. At the same time, a sintering whole process intelligent manufacturing system based on the above four models is constructed using Java and Python programming languages. The system realizes the functions of real-time analysis of key parameters, intelligent early warning, decision optimization and fault tracing, which provides reasonable line optimization suggestions for field operators, and significantly improves the intelligence and production efficiency of sintering process.

Research and application of the sintering whole process intelligent manufacturing system