8results about How to "Clear management" patented technology

The invention discloses a flexible manufacturing-based DPA component matching method, which comprises the following steps of: establishing a DPA component requirement catalog, establishing a management database, and creating catalog entries for each component needing DPA detection; the method comprises the following steps: establishing DPA components, and creating a corresponding DPA component for each basic component needing to execute DPA detection in enterprise product bill of material structure management; the method comprises the following steps: establishing a corresponding relation between a DPA component requirement directory and a component, establishing a mapping relation between a DPA requirement directory and a DPA component, triggering to generate or call a corresponding DPA component demand according to the mapping relation, and realizing automatic conversion from a detection requirement to a specific execution material; and establishing a matched operation system, and integrating the system into a manufacturing execution system or a material demand planning module of an enterprise resource plan. According to the method, automatic identification of DPA detection requirements, intelligent matching of detection materials and accurate accounting of related cost can be realized.

The utility model discloses a kind of auxiliary recording devices for salad dressing food processor, it is related to food processor technical field, including food processor body and cooking jar, cooking jar is installed on food processor body, sleeve is provided at cooking jar front side, sleeve is fixedly installed on food processor body, rotating shaft is rotatably connected in sleeve interior, rotating shaft outside is evenly provided with several columns of label group, several columns of label group are annular array arrangement on rotating shaft outside, and label group is composed of several upper and lower label blocks, and several upper and lower label blocks are evenly arranged on rotating shaft outside.The utility model is through the design of label group, rotating shaft, recording shield and formula display, can automatically record feeding process, in the process of every closure plate opening / closing, the raw material of corresponding label block is put, and in the process, the automatic shielding of corresponding label block is completed by recording shield of automatic downward movement, avoid feeding forget or error, improve the accuracy, efficiency and operation convenience of feeding, reduce raw material waste.

The invention relates to the field of precise milling and turning, in particular to a dynamic quality planning intelligent management method based on a mechanism model, which comprises the following steps: collecting multi-source heterogeneous data, and respectively constructing an implicit disturbance risk index for representing a system disturbance risk and a wear state parameter for representing a system wear state based on the data; calculating to obtain a system critical index in combination with the implicit disturbance risk index and the wear state parameter; presetting a critical state grade threshold value, and comparing the system critical index with the critical state grade threshold value to obtain a critical state evaluation result; generating a process correction factor based on the critical state evaluation result and the system critical index; according to the process correction factor, outputting a grading correction strategy for the processing process parameters; dynamic balance of production efficiency and quality safety is realized, and quality collapse is effectively inhibited.

The invention relates to an image classification method based on incremental learning. The method comprises the following steps: collecting a multi-modal data set and dividing the multi-modal data set into a basic data set and an incremental data set; the multi-modal data set at least comprises image data and text data; constructing an image classification model; inputting the basic data set into an image classification model for training, storing a training weight, and then inputting the incremental data set into the trained image classification model for incremental learning to obtain a trained image classification model; image data to be classified are obtained and preprocessed, and then the image data are input into the model to obtain a corresponding classification result. According to the method, efficient balance of new and old knowledge and inhibition of disastrous forgetting are realized by optimizing learnable prompts and multi-modal fusion, and the model performance and practicability are improved on the premise of avoiding dependence on data caching and not remarkably increasing the parameter quantity.

The application provides a kind of multi-model API docking management method and system based on deep learning, it is related to artificial intelligence and cloud computing technology field, including the following steps: collect and standardize all the AI prompt word templates and skill assets generated in workflow storage, to generate AI prompt word template library and skill asset library;Request data is optimized;The state of the multi-business model is evaluated in combination with the optimized request data to determine the target business model, and the optimized request data is distributed to the target business model to perform inference operations;Real-time acquisition of inference results and performance indicators generated during the execution of the target business model, and the inference results and performance indicators are returned to the cloud storage space;The AI prompt word template library and skill asset library are updated to realize the docking optimization of multi-business model.The application realizes the efficient, low-cost and adaptive optimization of multi-business model call, with good scalability and practical value.

This invention discloses a closed-loop soil improvement method for vineyards using organic fertilizer synergy, comprising the following steps: seasonal directional grass cultivation, preparation of Bacillus subtilis agent, preparation and application of self-made organic fertilizer in the early stage of vineyard establishment, and closed-loop synergistic improvement method; the closed-loop synergistic improvement method is divided into early stage improvement and late stage improvement, relying on grass return to the field and Bacillus subtilis to maintain soil fertility and nutrient cycle.