8 results about "Unit process" patented technology

The application relates to a sandstone processing system gradation and energy consumption double-target optimization method and system, and relates to the technical field of sandstone processing. The method comprises the following steps: acquiring sandstone processing units, processing unit processes and unit mapping relationships; analyzing the sandstone processing units, the processing unit processes and the unit mapping relationships to determine general process modeling; acquiring project unit parameters and project optimization requirements; inputting the project unit parameters into the general process modeling to determine a double-target optimization model and equipment operation boundaries; analyzing the double-target optimization model and the equipment operation boundaries according to a preset double-target optimization model to determine requirement weight groups; searching in the requirement weight groups according to the project optimization requirements to determine target optimization weights; and analyzing the double-target optimization model according to the target optimization weights and the double-target optimization model to determine an optimal configuration scheme. The application has the effect of improving sandstone processing efficiency.

In a method of predicting an optimal process condition model for a semiconductor fabrication process, process parameter information of a unit process in the semiconductor fabrication process may be collected. First characteristics information of objects to be processed before the unit process and second characteristic information of processed objects after the unit process may be extracted. Process global uniformity (PGU) may be calculated using the first characteristic information and the second characteristic information. A data set of the unit process may be created using the process parameter information and the PGU. A virtual process environment function of the unit process may be created using the data set. The optimal process condition model of the unit process may be created using the virtual process environment function.

The invention belongs to the technical field of magnesia carbon brick production environmental impact evaluation, and relates to an environmental impact evaluation method for magnesia carbon bricks and waste magnesia carbon brick resource utilization products. Firstly, an evaluation object, a function unit and a system boundary are determined; dividing the life cycle of the evaluation object into a plurality of unit processes according to a system boundary, and establishing an input and output data list of each unit process; a corresponding characterization model is selected, a list analysis result is analyzed according to characterization factors of the model, and an evaluation result of the life cycle environmental influence is obtained and represented by environmental influence potential values of different environmental influence types; explaining the environmental influence result of the evaluation object and proposing suggestions according to the contribution degree of each element; then, investment cost, operation cost and environment cost calculation is carried out on several resource utilization paths; and finally, calculating the total income of different waste magnesia carbon brick resource utilization products, and analyzing the total economic benefit.

The invention relates to the technical field of quality management, and discloses a silkworm and mulberry product full life cycle quality traceability system and method based on the Internet of Things, and the system obtains a first material total amount and an initial quality feature vector of a first node raw material, and obtains an active power time sequence curve of a second node processing device; the space mapping unit determines a theoretical characteristic value domain, a theoretical by-product proportion range and a theoretical energy efficiency interval of a produced product according to a physical property conversion operator; the judgment arbitration unit compares the second material total amount change rate, the product characteristic deviation degree, the by-product mass ratio and the unit processing power consumption, and physical property homology is confirmed. The traceability fracture hidden danger caused by physical property conversion is eliminated, the logic relation among the finished product, the by-product and the processing energy consumption is established, and the product quality is improved. Therefore, the management dimension is changed from single output counting to full constraint of the processing process, and the defense elasticity of the supervision network is improved.

The present invention is applicable to the technical field of carbon reduction and energy saving, and provides an iron and steel product carbon footprint evaluation method and system. The method comprises: acquiring production process data of a product to be evaluated and energy flow data, determining production unit processes of said product on the basis of the production process data, and determining energy unit processes of said product on the basis of the energy flow data; on the basis of second input data and second output data of the energy unit processes, calculating, by means of an energy system carbon emission factor model, a self-produced energy carbon emission factor of said product; acquiring first input data and first output data of the production unit processes, and on the basis of the first input data and the first output data, determining a process coefficient of said product in a production process; and on the basis of the process coefficient, the self-produced energy carbon emission factor, the first input data and the first output data, obtaining, by means of a life cycle carbon footprint evaluation model, a carbon footprint evaluation result of said product.

This invention relates to a dynamic optimization method for the entire steel production process. The method first constructs a full-process production scheduling rule engine library. After feature preprocessing, an adaptive unit process structure and a fully connected aggregated process structure are generated through a general modeling framework. Then, a hierarchical optimization framework is built. The monthly plan fusion optimization model adopts a three-stage progressive optimization strategy of capacity balancing, production line division of labor, and order scheduling, combined with a daily scheduling fusion optimization model to achieve dynamic scheduling. Finally, an intelligent solution algorithm engine is used to match and solve the problem and output the results. This application can solve the problems of insufficient model generalization ability, process coordination failure, and difficulty in balancing solution efficiency and global optimization objectives in existing technologies. It improves the model's cross-scenario generalization ability and the degree of coordination of the entire process, significantly reduces solution time, and significantly improves order delivery rate and inventory control level.

In a resin sealing method, a temperature of a sealing mold for appropriately thermally curing a resin during sealing is taken as a normal setting temperature, and a temperature of the sealing mold higher than the normal setting temperature by a predetermined temperature is taken as a switching setting temperature. In a unit process in which a workpiece and the resin are carried into the sealing mold, sealed, and then carried out as a molded product, with respect to at least one of an upper mold and a lower mold, a setting temperature is changed to increase from the normal setting temperature to the switching setting temperature at a predetermined start timing to control the temperature of the sealing mold, and the setting temperature is changed from the switching setting temperature to the normal setting temperature at a predetermined end timing to control the temperature of the sealing mold.

The invention provides a catalyst design optimization method and device based on a high-throughput platform, and the method comprises the steps: preparing a plurality of candidate catalysts based on a plurality of groups of material proportions and preparation parameters; based on a high-throughput platform, measuring the desulfurization rate and the denitrification rate of each candidate catalyst; taking the material ratio and the preparation parameters of each candidate catalyst as input, taking the desulfurization rate and the denitrification rate of each candidate catalyst as labels, and training to obtain a machine learning prediction model; on the basis of the machine learning prediction model, an optimized desulfurization rate, an optimized denitrification rate, an optimized material ratio and optimized preparation parameters are calculated by using an optimization algorithm; and judging whether the optimization result meets the requirement or not, and if the optimization result does not meet the requirement, taking the optimized material ratio and the optimized preparation parameters as a new round of experimental parameters to repeat the preparation unit process. Manpower and material resources can be greatly saved, the research and development period of the catalyst material is remarkably shortened, and the scientific research efficiency is improved.