Whole-process optimizing method of multi-stage batch production process

Abstract

The invention discloses a whole-process optimizing method of a multi-stage batch production process. The whole-process optimizing method of the multi-stage batch production process comprises the steps of collecting and preprocessing a plurality of batches of production data of a multi-stage batch production process, wherein the production data comprises procedure parameters and product quality attribute data; establishing a partial least square (PLS) model between the procedure parameters and the product quality attribute data by means of the PLS method; and determining an optimizing objective, combining with the PLS model and calculating Bayesian posterior prediction probability, coinciding with the optimizing objective, of product quality attribute, and selecting largest procedure parameter combination of the Bayesian posterior prediction probability as the optimizing result. According to the whole-process optimizing method of the multi-stage batch production process, optimizing technological operation coinciding with established quality objectives can be provided for every stage of the multi-stage batch production process, and finally stability and improvement of product quality are achieved.

Description

Technical field [0001] The invention belongs to the field of production process control and optimization, and particularly relates to a full-process optimization method for a multi-stage intermittent production process. Background technique [0002] Intermittent processes occupy an important position in modern manufacturing and are widely used in the processing and manufacturing of high value-added products such as pharmaceuticals, chemical products, biological products, and agricultural products. In actual production, a batch process composed of multiple process units or procedures in a certain sequence is called a multi-stage batch process. The main purpose of the multi-stage batch process is to improve the performance of the product, ensure the stability of the product quality, and enhance the market competitiveness of the product. Unlike batch process units, the control and optimization of multi-stage batch production processes are more challenging due to their complex natur...

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Problems solved by technology

(4) Fluctuations in the quality of raw materials or disturbances in a certain process unit will be transmitted to the quality of the final product as the production process proceeds, resulting in differences between batches of final products

However, the combination of PLS ​​pathway modeling and SIC method is cumbersome, and the theory of SIC itself is not complete, which makes the optimization somewhat empirical; and because its optimization goal is to maximize a certain quality index, the continuity of product quality is ignored

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