52 results about "Inventory cost" patented technology

The invention relates to a CNC machining material unified management system based on intelligent early warning and multi-dimensional fusion, and belongs to the technical field of intelligent manufacturing and industrial informatization. The invention aims to solve the technical challenges in the existing CNC processing material management. The system adopts a three-layer architecture, comprises a data layer, a business logic layer and an application layer, and realizes the functions of unified modeling, classified management, batch tracking, inventory early warning and the like of material data. Through the intelligent tool breakage prediction module, the two-stage position management module, the intelligent inventory prediction module and the like, the system can automatically identify tool breakage abnormity, optimize the storage position, predict the inventory depletion date and generate intelligent replenishment suggestions. The system improves the management efficiency, reduces the inventory cost and the stockout risk, is suitable for the fields of intelligent manufacturing and industrial informatization, and meets the requirements of digital transformation of enterprises.

The invention relates to the technical field of purchase demand prediction, and discloses a part purchase demand prediction method and system based on machine learning, and the method comprises the steps: obtaining modular product basic data, and generating a BOM graph structure; calculating prior probability distribution through a Bayesian inference algorithm; executing an adaptive probability pruning algorithm to solve the problem of combinatorial explosion; quantizing uncertainty by using a Bayesian deep learning network; calculating a differentiated safety inventory coefficient based on the value-at-risk model; executing an importance sampling algorithm to carry out Monte Carlo simulation on high-risk low-frequency configuration, and verifying a demand coverage rate in an extreme scene; an incremental learning mechanism is utilized to update probability distribution and a pruning threshold according to the new order data, and a self-adaptive optimization demand prediction result is output; according to the method, the inventory cost is remarkably reduced, the stockout risk is reduced, and the balance between the calculation efficiency and the prediction accuracy is realized.

The invention relates to the technical field of computer application technology and Internet of Things, in particular to an intelligent food sales inventory management system based on Internet of Things. The system comprises an Internet of Things sensor network, a data acquisition module, a data processing module and a decision control module. The Internet of Things sensor network is provided with a temperature sensor, a humidity sensor, a weight sensor and an RFID tag, and is used for collecting food stock environment parameters and stock data in real time. The data acquisition module is connected with a sensor network and an external data source, and integrates and preprocesses sales data, weather forecast data and holiday event data. And the data processing module adopts a long-short-term memory network model to carry out sales prediction, and adopts a support vector machine model to evaluate the food deterioration risk. Real-time monitoring, accurate prediction and dynamic optimization of food inventory are realized through multi-source data fusion and machine learning, food waste and inventory cost are effectively reduced, and operation efficiency is improved.

The invention provides a real-time monitoring and risk assessment method and system for a product registration rate in a satellite general assembly process, and the method comprises the steps: building a satellite general assembly process flow in advance, and determining the demand type, number and time node of each process for a product; actual arrival data, production progress data and supply chain state data of products in the satellite final assembly process are collected in real time; according to actual arrival data and demands, calculating a product neat rate at the current moment, and dynamically updating a neat rate evaluation result; analyzing the potential risk based on a risk prediction algorithm to obtain a risk level; and generating early warning information according to the risk level, and formulating an optimal scheduling strategy to adjust a production plan and supply chain resource allocation. According to the method, efficient production organization and supply chain collaboration can be achieved, the production efficiency can be remarkably improved, the inventory cost is reduced, and the risk of production delay caused by irregular products is reduced.

The application relates to the technical field of data processing, and discloses a steel structure plant profile blanking optimization method and system based on Tekla. The method comprises the following steps: extracting component parameters based on Tekla, comparing with a standard database to distinguish rolled pieces and welded pieces; disassembling the welded pieces and correcting a list according to plate thickness; counting inventory to generate an available resource list; adopting a multi-level matching strategy to determine the demand for the rolled pieces; adopting plate cutting optimization to generate thin plate and thick plate cutting plans for the welded pieces, and processing variable cross-section webs through pair-by-pair complementary splicing, so as to determine the demand for coiled materials and steel plates; and constructing a dynamic optimization model integrating inventory and fund constraints, so as to output an optimal scheme under the fund limit constraint. The application improves the comprehensive utilization rate of materials, preferentially guarantees the supply of main components, reduces procurement and inventory costs, and provides scientific decision support for steel structure plant blanking.

The application discloses a kind of concrete sales intelligent computing method and system, it is related to building and logistics management technical field.The application is accurate to predict customer demand and optimize production quantity and raw material proportioning by dynamically adjusting production plan, the problem that production surplus or deficiency caused by large demand fluctuation in traditional production is solved, inventory cost is reduced and production efficiency is improved, in transportation link, real-time monitoring traffic condition and dynamically optimizing transportation route, transportation efficiency and delivery punctuality are significantly improved, transportation cost is reduced and concrete quality is ensured;In production process, raw material proportioning and concrete state are monitored in real time using sensor and machine learning algorithm, production parameters are dynamically adjusted, the quality fluctuation problem caused by inaccurate proportioning or not timely monitoring in traditional production is solved, and the stability of product quality is ensured.

The utility model provides an adjustable condenser support belongs to condenser support technical field, include: support mechanism, the outside of support mechanism is equipped with adjusting mechanism, the surface fixedly connected with two connecting mechanisms outside adjusting mechanism, the surface of connecting mechanism is equipped with the mounting seat, support mechanism includes two first support plate, the surface of first support plate is equipped with second support plate, the surface of first support plate is equipped with two second clamping groove, the surface of second support plate is equipped with two second clamping groove, the second clamping groove is adapted, this scheme passes through support mechanism and hinged adjusting mechanism, realizes the stepless regulation of height and span, thereby has increased the practicality of this support, has reduced the inventory cost, passes through the clamping structure of the sliding support seat and mounting seat of connecting mechanism, realizes the independent disassembly of condenser, promotes the maintenance efficiency, and avoids the support structure fatigue caused by the frequent operation.

This invention relates to the field of inventory cost analysis, addressing the problems of lagging information updates and lack of predictive warnings in cost accounting, which prevent the automatic triggering of targeted inventory optimization strategies. Specifically, it is a rolling analysis method for spot inventory costs with full-process tracking, including a pre-warehouse process cost statistics module, an in-warehouse cost statistics module, a rolling analysis module, an inventory cost prediction statistics module, and an inventory optimization decision-making module. Based on complete inventory cost accounting, this invention endows cost management with real-time and forward-looking capabilities through rolling analysis and dynamic prediction. Ultimately, through intelligent linkage between cost and profit and a multi-level decision-making mechanism, it achieves an intelligent closed loop from data to action, transforming inventory cost management from traditional recording into a core decision-making tool for profit protection and risk prevention, effectively improving the enterprise's inventory operation efficiency and overall profitability.

This invention discloses a real-time assessment method for in-transit inventory costs based on process-oriented tracking and statistics, belonging to the field of logistics cost accounting technology. It aims to solve problems such as lagging in-transit inventory cost accounting, reliance on manual labor, inability to dynamically calculate, and difficulties in full-chain traceability. This invention constitutes a complete solution through layered creation of tracking pools, automatic aggregation based on logistics identifiers, real-time rolling calculation triggered by events, and full-chain aggregation presentation centered on contract numbers. On the one hand, it achieves real-time, automatic, and accurate accounting of in-transit inventory costs through automatic aggregation and rolling calculation of costs throughout the entire process from order to warehousing. On the other hand, through dynamic updates and deep traceability, as well as strengthening the correlation query between contract numbers and accounts payable and business documents, it provides enterprises with unprecedented cost transparency and control capabilities, fundamentally overcoming the core defects of existing technologies.

This disclosure provides a method, apparatus, storage medium, and electronic device for supply chain replenishment quantity forecasting. The method includes: constructing a first feature vector based on the inventory status on the replenishment decision date; inputting the first feature vector into a prediction model, and determining that the output value of the prediction model is the first replenishment quantity corresponding to the current replenishment decision date, wherein the prediction model is used to characterize the correlation between the feature vector and the replenishment quantity. This disclosure obtains a prediction model for characterizing the relationship between the feature vector and the replenishment quantity by training a preset model, uses the prediction model to perform end-to-end replenishment quantity forecasting based on the inventory status on the current replenishment decision date, and uses the predicted replenishment quantity to assist supply chain inventory management decisions, achieving the lowest inventory cost while ensuring service levels.

This invention, entitled "A Distributed Hybrid Interleaved Batch Scheduling Method and System for Parallel Production Lines," belongs to the field of production line scheduling. It addresses the problem of minimizing inventory and stockout costs. The method includes: complete delivery based on vehicle model bill of materials; each production line comprises multiple sequentially connected stages, with the same set of dies only allowed on one production line at any given time; during the stamping stage, only one production line can utilize the stamping die to process the corresponding sub-batch; a consistent sub-batch partitioning strategy is adopted for the same batch, ensuring that the quantity and corresponding dimensions of each sub-batch remain unchanged in subsequent processing stages after partitioning; the dimensions between different sub-batches can be determined by the selected sub-batch partitioning rules; alternating processing of sub-batches from different batches is allowed on the same production line; each sub-batch can only be processed by one production line in each stage; the scheduling objective is to minimize the total sum of inventory and stockout costs while achieving complete delivery.

The invention discloses an IGS valve runner adaptive flow changing method based on a sandwich structure, which comprises the steps of material selection, stock comparison, switching block selection and the like, and aims to solve the problems of stock troubles and installation adaptation caused by unsuitability and incompatibility of an existing gas runner piece and a valve runner. Compared with the prior art, the flow channel effectively overcomes the existing defects, can efficiently adapt to stock differences, achieves the effect of reducing the stock cost, has the technical characteristics of compact and compatible structure, reliable flow channel design and simple processing technology, effectively improves the design and production flexibility, and is suitable for wide popularization.

The utility model relates to a semi-steel tire dual-purpose calendered large roller shutter fabric inventory screen display device, and belongs to the field of tire storage devices. Dual-purpose calendering large roller shutter cloth goods shelves are vertically arranged in parallel, the calendering large roller shutter cloth goods shelves are of a cylindrical structure, U-shaped LED screen supports are inserted into the top ends of the adjacent dual-purpose calendering large roller shutter cloth goods shelves, LED screen protection boxes are hung on the LED screen supports, LED screens are installed in the LED screen protection boxes, and the LED screens are connected with an EMS production management system through data lines. Arc-shaped shaft supporting plates are fixed to the positions, with the same height, between every two adjacent dual-purpose calendering large roller shutter cloth goods shelves. According to the utility model, on the basis of an EMS production management system, informatization management of the large roller shutter cloth inventory in the semi-steel tire dual-purpose calendaring process is realized, real-time monitoring and visualization of inventory data are realized, dynamic optimization of the inventory is realized, the inventory cost is reduced, accurate management of the inventory data is ensured, and manual operation errors are reduced.

The system is an inventory replenishment solution based on artificial intelligence (AI), and aims to optimize the inventory management process of an enterprise through automatic and intelligent technical means. The system integrates a plurality of data sources, utilizes an advanced AI model to carry out prediction and decision making, provides an accurate inventory replenishment strategy for enterprises, ensures efficient inventory management, and reduces risks of stockout and excessive inventory. The system is a key component in modern supply chain management, and aims to automatically adjust the inventory level by means of intelligent analysis of historical sales data, market demand prediction, supply chain efficiency optimization and the like so as to reduce inventory overstock, avoid stockout conditions and improve the overall operation efficiency. According to the system, through intelligent inventory management and replenishment decision, the inventory management efficiency is greatly improved, the inventory cost is reduced, and the customer satisfaction is improved. The method is suitable for enterprises of various scales, and is especially suitable for industries with complex supply chains and large demand fluctuation, such as retail, manufacturing and electronic commerce.

This invention discloses a method and system for optimizing medical consignment inventory based on kit integrity constraints. The method includes: constructing a material dependency graph for surgical kits, representing each surgical kit as a graph structure containing nodes and edges; constructing a shortage risk propagation model based on historical borrowing and returning data, calculating the risk transmission coefficient of material shortages on kit availability, and forming a kit integrity probability assessment system; establishing an optimization model aimed at minimizing the probability of kit shortages under total safety stock budget constraints, dynamically allocating the safety stock level of each material within the kit; integrating surgical scheduling data with the inventory calculation model, and implementing differentiated inventory reservation and sharing strategies based on surgical certainty levels to achieve synergistic optimization of kit integrity and inventory costs. This effectively solves the problem that traditional single-material inventory calculation methods cannot guarantee kit integrity, significantly improving material availability and reducing redundant inventory costs.

A method and system for generating procurement plans for chain pharmacies based on big data, relating to the field of procurement management, is disclosed. The method includes: first, collecting historical sales data, real-time inventory data, and external environmental data to construct a multidimensional database; then, standardizing the data and constructing a drug classification matrix using a data mining model; next, using causal analysis to identify key factors influencing drug demand and establishing a weight matrix of demand influencing factors; calculating procurement parameters such as safety stock levels, economic order quantities, procurement trigger points, and procurement cycles based on this weight matrix; and finally, combining a supplier evaluation system to generate a procurement plan including a list of drugs to be procured, procurement quantities, procurement time, and supplier selection. This method, through multidimensional data analysis and causal relationship mining, achieves scientific and precise procurement decisions, improves procurement efficiency, and reduces inventory costs.

This utility model relates to a splicing car sill, comprising a first material and a second material. A first contact edge is integrally formed on one vertical surface of the first material, and a second contact edge is integrally formed on one vertical surface of the second material. This utility model, through the splicing design of the first and second materials, achieves rapid adaptation of sills of different specifications, significantly reducing material types and inventory costs. The insertion and matching of the guide post and countersunk hole ensures precise splicing alignment, eliminating manual adjustment errors and improving assembly efficiency. The combined design of the first and second sliding grooves is compatible with center-split, center-split double-fold, and side-opening double-fold sill supports, offering strong versatility. The T-shaped limiting part of the auxiliary connecting component works in conjunction with the connecting plate to significantly improve the shear resistance of the splicing node. The connecting plate is fixed by the sliding T-shaped limiting part and can be disassembled without special tools, facilitating later maintenance or component replacement.

The invention relates to the technical field of data processing, and discloses a Tekla-based steel structure plant profile blanking optimization method and system. The method comprises the following steps: extracting component parameters based on Tekla, and comparing the component parameters with a standard database to distinguish a rolled piece and a welded piece; the welding part is disassembled, and the list is corrected according to the plate thickness; counting the inventory to generate an available resource list; determining the demand quantity by adopting a multi-stage matching strategy aiming at the rolled piece; a thin plate and thick plate cutting plan is generated through plate cutting optimization according to the welding parts, variable cross-section webs are processed through pairwise complementary splicing, and the demand quantity of coiled materials and steel plates is determined; and constructing a dynamic optimization model fusing inventory and fund constraints, and outputting an optimal scheme by using the fund limit constraints. The comprehensive utilization rate of materials is increased, supply of main body components is guaranteed preferentially, the purchase and inventory cost is reduced, and scientific decision support is provided for discharging of the steel structure factory building.

The invention discloses a hierarchical clustering Q learning-based ship equipment spare part demand prediction method. The method comprises the following steps of 1) obtaining historical demand data of ship equipment spare parts; 2) preprocessing the collected data set, and identifying and processing missing values and abnormal values in the data; 3) dividing the data sets into a training data set and a test data set, and respectively performing clustering operation on the two data sets; 4) constructing a spare part prediction model; 5) training a spare part prediction model of Q learning by using the training data set; and 6) based on to-be-predicted ship spare part demand data, using the trained model to carry out subsequent ship spare part demand data prediction. According to the hierarchical clustering Q learning-based spare part demand prediction method provided by the invention, the optimal prediction model can be automatically selected according to different spare part feature distribution, the prediction error of the spare part demand is reduced, and the purpose of reducing the spare part inventory cost is achieved.

The invention relates to a WEEE recycling supply chain inventory optimization method based on evolutionary reinforcement learning, and belongs to the technical field of supply chain management and artificial intelligence. According to the method, a multi-level inventory cooperative control model is constructed, an inventory optimization problem is modeled as a Markov decision process, and an evolution reinforcement learning algorithm is utilized to train an intelligent agent to learn an optimal strategy. Core innovations include design state space capture inventory dynamics, action space processing continuation to discrete decision mapping, and cost-based minimization of reward functions. According to the algorithm, a population evolution mechanism and experience playback optimization are fused, and the learning efficiency and stability are improved through parallel exploration and sample screening. According to the method, the uncertainty of the recovery amount and demand can be effectively dealt with, the inventory cost is reduced, the supply chain robustness and sustainability are enhanced, and a self-adaptive intelligent solution is provided for WEEE management.

The invention discloses a material management method, a computing device and a computer readable storage medium, and the method comprises the steps: determining a first material demand according to a target production plan, and carrying out the neat analysis of the first material demand on a production level according to an existing inventory; determining a second material demand according to an analysis result of the neat set analysis, the second material demand being a material demand corresponding to the first material demand which cannot be satisfied by the existing inventory; acquiring at least one purchase order in a purchase state, and matching the second material demand based on material information in the purchase order; and managing the first material demand according to an analysis result of the registration analysis and a matching result of the purchase order. Therefore, the material requirement of the current production plan is met in time on the basis of the existing inventory and the purchase order through the method of neat set analysis and purchase order matching, the risk of production interruption is reduced, the inventory is optimized, and the inventory cost is reduced.

The invention provides a material inventory management method and device, equipment and a storage medium, and the method comprises the steps: determining the total cost of a storage supply chain based on the storage supply chain data of at least one material and to-be-optimized parameters through employing a mayfly naiad algorithm integrated with at least one strategy, such as a position optimization strategy, a speed optimization strategy and a search range optimization strategy; according to the method, the storage supply chain total cost is optimized, the to-be-optimized parameters are iteratively optimized with the minimum storage supply chain total cost as the optimization target, inventory management operation is driven based on the optimized parameter values after iteration is finished, automatic optimization of multi-node and multi-category material inventory parameters is achieved, the inventory collaboration requirement of a complex supply chain can be met, and the inventory cost in the supply chain is reduced.

This invention relates to the field of artificial intelligence technology and discloses a bank intelligent printing device and its consumable management platform. The platform includes: an intelligent monitoring module for real-time monitoring of the status of each bank's intelligent printing device, tracking consumable reserves, and adjusting for environmental adaptation; an AI prediction module for using a multimodal spatiotemporal fusion model to predict consumable usage data from a preset time period prior to the current time period, outputting a consumable demand list and failure risk for the future preset time period; and a dynamic inventory management module for automatically placing consumable orders when inventory reaches a critical value and performing barcode verification upon consumable receipt to intercept mismatched consumables. Through these methods, this invention achieves fully automated intelligent management and control of bank intelligent printing devices, effectively reducing failure rates and inventory costs.

This invention provides an order processing method, apparatus, electronic device, and readable storage medium. By acquiring orders to be processed, when finished goods inventory is insufficient, the method executes the order using all finished goods and calculates a first demand quantity. Then, it determines whether to produce based on whether semi-finished goods inventory meets the first demand quantity, and calculates a second demand quantity when semi-finished goods inventory is insufficient. Finally, it uses raw materials to produce the second demand quantity of materials to complete the order. By sequentially utilizing finished goods inventory, semi-finished goods inventory, and raw materials, order demands are responded to level by level. Even when finished goods or semi-finished goods inventory is insufficient to meet all demands, order execution can still be effectively promoted, significantly improving the utilization rate of inventory resources and order processing efficiency, shortening the production cycle, reducing inventory costs, and enhancing the system's adaptability to complex order demands.

The invention discloses a product customization method, platform, system and device, a storage medium and a program product, the product customization method is applied to an online customization sales platform, and the product customization method comprises the following steps: the online customization sales platform obtains and loads a product processing image and product processing information; constructing a product model according to the product processing image and the product processing information; and carrying out analogue simulation on the constructed product model to obtain an optimized product model. Product customization and sales are achieved through the online customization sales platform, and the problems that due to the fact that product customization cannot be achieved, the inventory cost is high, the cost is difficult to control, the market response is slow, the production efficiency is low, and the production period is long are solved.

The utility model belongs to the technical field of hydraulic engineering, and discloses a hydraulic engineering pipeline connecting device which comprises a bottom plate, a rectangular groove is formed in the surface of the bottom plate, a first threaded rod is movably installed in the rectangular groove, a sleeving block is movably installed on the surface of the first threaded rod, and a connecting plate is fixedly installed on the top of the sleeving block. And a lower limiting plate I and a rectangular block I are fixedly mounted at the top of the connecting plate in sequence. By means of the device, the pipeline connecting process is quicker, simpler and more convenient, the device can quickly adapt to pipelines of different specifications, tedious adjustment is not needed, and therefore the connecting efficiency is greatly improved, the connecting efficiency and convenience are improved, the pipelines of different specifications and thicknesses can be limited, and the practicability is high. And the flexibility of the water conservancy pipeline system is remarkably improved, so that different engineering requirements can be met, the dependence on pipelines of specific specifications is reduced, and the inventory cost and the management difficulty are reduced.

The utility model provides a transmission box with adjustable handle center distance and a door and window, the transmission box comprises a transmission shell and a transmission box body, the transmission box body is embedded in the transmission shell, an adjusting assembly is arranged in the transmission shell, a gear sleeve used for being connected with a handle driving shaft is arranged in the transmission box body, and the handle driving shaft is connected with the adjusting assembly. The transmission box body can move up and down in the transmission shell through an adjusting assembly. The transmission box body is formed by splicing a first box body and a second box body. According to the transmission box, the transmission box body moves up and down in the transmission shell by adjusting the adjusting assembly, so that the vertical distance between the lap joint face of the transmission box and the surface of a C-shaped groove of a window sash profile and the axis of a shaft hole of the transmission box can be changed, and the center distance of a handle of the transmission box is adjusted; therefore, the specifications and types of the transmission box can be reduced, the mold opening, manufacturing and inventory costs are reduced, and the problems of multiple specifications and high mold opening, manufacturing and inventory costs caused by the non-adjustable center distance of the handle of the transmission box are solved.

The application discloses an enterprise inventory optimization method and system based on an inventory optimization index tree, designs an enterprise inventory cost reduction capability model covering the whole supply chain based on an integrated supply chain methodology, then the enterprise selects appropriate enterprise inventory optimization indexes according to the inventory cost reduction capability model to construct the inventory optimization index tree, acquires inventory abnormal indexes by monitoring target values and actual values of the enterprise inventory optimization indexes in the index tree, and then completes performance improvement by optimizing the abnormal indexes.

The embodiment of the invention provides a service processing method, device and equipment, a medium and a product, and the method comprises the steps: obtaining first construction data of a service architecture, the first construction data comprises first prediction data of a first product in the service architecture in a first time period, constructing a bill of material required by the first product and supply cycle information of each material in the bill of material; obtaining second construction data of the service architecture, wherein the second construction data comprises second prediction data and second execution data of a first product in the service architecture in a second time period; based on the first construction data and the second construction data, predicting and executing deviation analysis processing to obtain safe water level data of the business architecture; and performing inventory management on various materials required by construction of the first product in the business architecture in the first time period according to the safe water level data. According to the embodiment of the invention, sufficient material supply can be ensured, the inventory liquidity is kept, and the inventory cost is effectively controlled.

The utility model discloses a steering system eccentric wheel, and particularly relates to the technical field of steering system eccentric wheels, the steering system eccentric wheel comprises a supporting disc, an eccentric supporting assembly is arranged on the supporting disc, and the eccentric supporting assembly comprises a mounting disc arranged at the top of the supporting disc. According to the utility model, parts such as the mounting disc and the limiting sleeve can be driven to rotate around the axis of the supporting disc by detaching the positioning pin or the bolt in the limiting hole, so that large-range coarse adjustment is realized; and the bolts matched with the adjusting grooves and the positioning holes are loosened, so that the bolts move along the arc-shaped adjusting grooves, and small-range fine adjustment can be realized. According to the adjusting mode, the problem that the angle of an existing eccentric wheel cannot be adjusted is effectively solved, the differential requirements of steering systems of different vehicle types for the eccentric angle can be met, the purchase and inventory cost of parts is reduced, after the steering system is abraded, the transmission error can be compensated by adjusting the eccentric angle, and the transmission efficiency is improved. And the steering precision can be recovered without replacing parts.