摘要
Petrochemical industry plays an important role in the development of the national economy. Purified terephthalic acid(PTA) is one of the most important intermediate raw materials in the petrochemical and chemical fiber industries. PTA production has two parts:p-xylene(PX) oxidation process and crude terephthalic acid(CTA) hydropurification process. The CTA hydropurification process is used to reduce impurities, such as 4-carboxybenzaldehyde, which is produced by a side reaction in the PX oxidation process and is harmful to the polyester industry. From the safety and economic viewpoints, monitoring this process is necessary. Four main faults of this process are analyzed in this study. The common process monitoring methods always use T^2 and SPE statistic as control limits. However, the traditional methods do not fully consider the economic viewpoint. In this study, a new economic control chart design method based on the differential evolution(DE) algorithm is developed. The DE algorithm transforms the economic control chart design problem to an optimization problem and is an excellent solution to such problem. Case studies of the main faults of the hydropurification process indicate that the proposed method can achieve minimum profit loss.This method is useful in economic control chart design and can provide guidance for the petrochemical industry.
Petrochemical industry plays an important role in the development of the national economy. Purified terephthalic acid(PTA) is one of the most important intermediate raw materials in the petrochemical and chemical fiber industries. PTA production has two parts:p-xylene(PX) oxidation process and crude terephthalic acid(CTA) hydropurification process. The CTA hydropurification process is used to reduce impurities, such as 4-carboxybenzaldehyde, which is produced by a side reaction in the PX oxidation process and is harmful to the polyester industry. From the safety and economic viewpoints, monitoring this process is necessary. Four main faults of this process are analyzed in this study. The common process monitoring methods always use T^2 and SPE statistic as control limits. However, the traditional methods do not fully consider the economic viewpoint. In this study, a new economic control chart design method based on the differential evolution(DE) algorithm is developed. The DE algorithm transforms the economic control chart design problem to an optimization problem and is an excellent solution to such problem. Case studies of the main faults of the hydropurification process indicate that the proposed method can achieve minimum profit loss.This method is useful in economic control chart design and can provide guidance for the petrochemical industry.
基金
supported by the National Natural Science Foundation of China (61422303, 21376077)
Fundamental Research Funds for Central Universities
