7 results about "Production chain" patented technology

The invention relates to the technical field of production and manufacturing management, and discloses a multi-source demand fusion and dynamic scheduling production plan collaborative management method and system, and the method comprises the steps: automatically obtaining production demands from a plurality of heterogeneous business source systems through a unified interface; performing data mapping and conversion on the heterogeneous demands to generate standardized main production plan demands, and distributing a unique tracing identifier penetrating through a production full link for each demand; calculating and generating a main production plan through a dual-mode scheduling engine supporting forward and reverse scheduling algorithms on the basis of a standardized demand, a product production cycle parameter and a working calendar; and issuing the main production plan to a manufacturing execution system, automatically capturing demand changes, performing versioning processing on affected plan items, and re-triggering scheduling calculation. According to the invention, end-to-end monitoring is realized through the unique tracing identifier, and rapid and closed-loop response is carried out on demand change, so that the accuracy and agility of production plan making are improved.

This invention discloses a data management and control system for the entire production process of silicone rubber products based on digital twins, belonging to the field of silicone rubber production management and control technology. It includes a data acquisition module, a twin construction module, a simulation driving module, and a quality field module. The data acquisition module collects real-time physical data of the entire production chain of silicone rubber products from raw materials to finished products. The twin construction module establishes a virtual digital twin of the physical production line. The simulation driving module injects real-time production data into the twin and drives synchronous simulation to generate a sequence of state parameters. The quality field module performs dynamic field analysis on the state parameter sequence, constructs an adaptive mesh topology that dynamically deforms with the parameters, and generates dynamic quality streamlines representing the quality transfer path between the topology nodes. This system realizes synchronous simulation of the entire silicone rubber production process and digital representation of the quality transfer process.

The invention relates to the technical field of non-woven fabric production quality management and control, in particular to an EVA-based laminated non-woven fabric product quality tracing method and system, and the method comprises the steps: synchronously collecting whole production chain time sequence process parameters through a sensor network, generating an original parameter flow bound with a production coil, obtaining a baseline, a rhythm and a disturbance component through multi-scale decomposition, and obtaining a reference parameter flow; and mapping to a product raw material layer, an interface bonding layer and a surface layer to generate a layering quality parameter set. And constructing a defect mode sample library, identifying a potential defect evolution path through unsupervised clustering, calculating a dynamic matching degree between a current parameter set and the defect evolution path in an early stage in real time, and triggering parameter backtracking and root positioning of a corresponding process link if the dynamic matching degree exceeds a threshold value. According to the method, layered association of the process parameters and the product structure is realized, defect evolution characteristics can be identified in advance, and the accuracy and the preposition of quality tracing of the EVA laminated non-woven fabric are improved.

The present application relates to the technical field of non-woven fabric production quality control, in particular to a quality tracing method and system for EVA laminated non-woven fabric products, comprising: synchronously collecting time sequence process parameters of the whole production chain through a sensor network to generate original parameter flow bound with production volume, obtaining baseline, rhythm and disturbance components through multi-scale decomposition, and mapping them to product raw material layer, interface bonding layer and surface layer to generate layered quality parameter set. A defect mode sample library is constructed, potential defect evolution paths are identified through unsupervised clustering, dynamic matching degree between current parameter set and early stage of defect evolution path is calculated in real time, and if the dynamic matching degree exceeds the threshold, parameter tracing and root cause positioning of the corresponding process link are triggered. The present application realizes the hierarchical correlation between process parameters and product structure, can identify defect evolution characteristics in advance, and improves the accuracy and proactivity of EVA laminated non-woven fabric quality tracing.

This invention provides a bottle cap production chain, comprising: a bottle cap injection molding device, a first conveying mechanism, a second conveying mechanism, and a case packer connected in sequence; a blowing mechanism is provided between the first conveying mechanism and the second conveying mechanism; the second conveying mechanism is provided with a conveying channel, a first diversion channel, a second diversion channel, a guide component, and a flipping mechanism; the case packer is connected to the first diversion channel and the second diversion channel respectively, and is used to sequentially place the correctly oriented bottle caps and the incorrectly oriented bottle caps into a case, so that the correctly oriented bottle caps and the incorrectly oriented bottle caps in the case are arranged alternately from top to bottom. Compared with the prior art, the bottle cap production chain of this invention can divide the bottle caps produced by the bottle cap injection molding device into two batches, and then flip the correctly oriented bottle caps of one batch to the incorrect orientation, and the correctly oriented bottle caps and the incorrectly oriented bottle caps are sequentially loaded into the case by the case packer, improving the stability of the bottle caps placed in the case.

The invention discloses an AI-based product quality risk assessment method and system, and the method comprises the steps: obtaining the multi-source data of an automobile bearing production chain, carrying out the deep extraction, obtaining the multi-source features of the production chain, constructing a physical consistency penalty term, constructing a physically guided cross-modal attention matrix, carrying out the modal fusion, obtaining the state features of the production chain, and carrying out the prediction of the product quality risk. Constructing a manufacturing process dynamic directed graph and a risk propagation adjacency matrix, performing risk propagation to determine a risk value of each manufacturing process, and performing Bayesian optimization on a risk threshold value of each manufacturing process according to a bearing structure parameter and a bearing type to obtain a risk dynamic threshold value; and carrying out quality risk assessment on the automobile bearing according to the risk value and the risk dynamic threshold value of each manufacturing process. The method not only can improve the efficiency and accuracy of automobile bearing quality risk assessment, but also has good interpretability, and can be directly applied to an automobile bearing quality risk assessment system.