142 results about "Enterprise resource planning" patented technology

A computer-implemented method for operating an artificial intelligence voice agent system includes receiving voice input through communication channels; analyzing converted text through natural language processing (NLP) pipelines implementing intent recognition and sentiment analysis detecting emotional cues using a multimodal large language model (LLM); generating response content using machine learning models trained on domain-specific corpora; converting generated responses to synthetic speech through text-to-speech (TTS) engines; integrating with a customer relationship management (CRM) platforms or an enterprise resource planning (ERP) database; and implementing continuous learning by updating language understanding models using conversation logs, voice recognition parameters based on user feedback, and response generation patterns. One implementation is a computer-implemented system and method that operates a suite of intelligent interactive devices and platforms including an artificial intelligence voice agent, enhanced communication platforms, an intimacy companion system, and augmented / virtual reality eyeglasses. Further, one implementation includes AR / VR eyeglasses that project visual content onto interchangeable lenses or directly onto the user's retina via laser-based retinal projection, provide prescription adjustments, incorporate ear-mounted sensors for monitoring physiological parameters like heart rate, oxygen saturation, and blood pressure, and utilize wireless data transmission, onboard environmental sensing, and remote calibration, all designed to offer dynamically adaptive, secure, and context-aware interactions across communication, personal assistance, health monitoring, and immersive augmented or virtual reality environments.

The invention discloses an ERP (Enterprise Resource Planning) data intelligent supervision method based on the Internet of Things, which relates to the technical field of enterprise informatization, and comprises the following steps: constructing a time sequence integrity observation layer in an Internet of Things data acquisition link, embedding a mirror image time anchor in each sensor sampling point, recording electromagnetic interference, time service offset and queuing delay, generating a phase fingerprint time baseline, and obtaining a phase fingerprint time baseline; constructing a unified time reference framework; operating a causal coherent analysis mechanism based on a unified time reference frame, comparing instantaneous offsets of a mirror time anchor and a real-time timestamp, identifying a phase inversion region, extracting information of a corresponding sampling node, a production line position and an energy consumption unit, generating a high-risk time slice list, and determining a time correction boundary. According to the method, a time sequence observation layer and a time reference frame are constructed, phase abnormity is identified, a data trend is reconstructed, a regulation and control instruction draft is generated, sampling time sequence recovery and scheduling convergence are realized through time inversion control, data consistency and decision accuracy are improved, and a closed-loop control system is constructed.

The invention relates to the technical field of carbon emission, in particular to an on-chain enterprise carbon emission accounting method and system. The method comprises the following steps: acquiring energy consumption, process flow and supply chain collaborative data of an enterprise in links of raw material acquisition, production processing, logistics transportation, equipment operation and recovery processing through Internet of Things equipment, and generating a carbon emission data set; based on a life cycle evaluation theory, boundaries of direct emission, indirect energy emission and supply chain associated emission are divided, and enterprise-level, product-level and supply chain-level carbon emission accounting models are constructed. A machine learning algorithm is utilized to analyze production fluctuation data in real time, carbon emission factor weights and accounting boundary parameters are dynamically adjusted, and an accounting result is optimized. And outputting a result to a green purchase decision-making system, a carbon asset management system and a supply chain collaboration platform. The system integrates industrial Internet of Things equipment, block chain nodes and enterprise resource planning system interfaces, collects and verifies full-link data in real time, solves the problem of data collection, and improves the accounting reliability.

The invention relates to the technical field of intelligent warehouse logistics, and particularly discloses a warehouse logistics AI path planning system and method based on multi-modal dynamic optimization. The system comprises a multi-source data layer which aligns inventory data, traffic flow data and meteorological data of a warehouse management system (WMS) in real time through a sliding window synchronization mechanism, and ensures time-space consistency of multi-modal input; the dynamic fusion engine responds to a traffic interruption event within 3 seconds based on a space-time alternative path algorithm and generates an anti-interference optimized path scheme; according to the path decision core, a two-stage reinforcement learning architecture formed by a graph convolutional network (GCN) and a deep Q network (DQN) is adopted, static topology analysis and dynamic real-time characteristics are fused, and a final transportation path is output; the decision auditing module is used for recording Q value distribution of decision nodes, constructing a traceable path decision tree and automatically detecting regional distribution deviation through a quantization formula; and the zero-code compatible layer is used for presetting a standardized API template library and a rule compiler so as to realize plug-and-play integration with an enterprise resource plan (ERP) or a warehouse management system (WMS). Through multi-source data collaborative optimization, dynamic anti-interference decision and whole-process audit tracing, the real-time performance, robustness and transparency of warehouse logistics path planning are remarkably improved.

An artificial intelligence-based business management system for real-time decision optimization, consisting of: a data acquisition unit configured to ingest structured, semi-structured and unstructured data streams from enterprise resource planning (ERP) systems, customer relationship management (CRM) platforms, Internet of Things (IoT) devices, external market feeds and financial transaction systems, encrypting, timestamping and verifying the data prior to further processing; a graph processing unit that is communicatively connected to the said acquisition layer, wherein the unit is configured to encode heterogeneous data into dynamic graph structures comprising nodes representing business entities and edges representing transaction or relationship dependencies, wherein the unit is further configured to perform deduplication, metadata tagging and real-time data synchronization; a decision optimization unit operationally linked to the graph processing unit, wherein the decision optimization unit includes modules for reinforcement learning, modules for Bayesian optimization and multi-objective solvers configured to simulate multiple alternative decision paths and select an optimal path based on performance indicators such as cost efficiency, resource utilization, customer satisfaction and risk minimization; a real-time inference control unit with specialized hardware cores, including at least one graphics processing unit (GPU), a field-programmable gate array (FPGA) and an application-specific integrated circuit (ASIC), wherein the accelerator performs inference tasks of the decision optimization unit with a latency in the millisecond range; a diagnostic processing unit configured to generate causal diagrams, feature mapping maps, and interpretable result summaries according to the optimization outputs; and a control interface unit configured to transmit optimized decisions to process controls within the enterprise, robot actuators, planning systems or interactive dashboards, with the interface supporting bidirectional communication for higher-level interventions, error feedback and triggers for re-optimization.

A computer-implemented method for improving test data troubleshooting in an enterprise resource planning (ERP) system is disclosed. The method can receive an error message generated by an application programming interface of the ERP system when processing a set of test data, embed the error message into a message vector, search a vector database comprising a plurality of object vectors to identify a target object vector matching the message vector, retrieve a target object document associated with the target object vector, and generate an answer including instructions to modify the set of test data based on the error message and the target object document. Related systems and software for implementing the method are also disclosed.

A system may include a data classification module configured to classify data into classified data based on predefined sensitivity levels and regulatory compliance requirements. A system may include an access control module configured to manage permissions for different user roles within an enterprise, granting access to the classified data in accordance with the sensitivity levels and regulatory compliance requirements. A system may include a data formatting module configured to format classified data into formatted data with customized presentations for various enterprise departments. A system may include an integration module configured to interface with at least one of an Enterprise Resource Planning (ERP) system or a Customer Relationship Management (CRM) system to retrieve and classify the data. A system may include a user interface module configured to present the formatted data within the host application, providing a seamless user experience for accessing the embedded marketplace.

The invention belongs to the technical field of block chain ERP (Enterprise Resource Planning), and discloses an enterprise ERP management system based on a block chain, which realizes credible sharing through an alliance chain architecture of a block chain base layer, ensures sensitive information privacy through a zero-knowledge proof technology, and can establish cooperative trust without endorsement of a third-party mechanism; the intelligent contract of the supply chain cooperation unit automatically executes cooperation rules such as purchase and acceptance, and trust disputes caused by manual intervention are avoided; the intelligent contract engine drives the unit processes of supply chain, production, finance and the like to be automated, so that end-to-end linkage of purchase-production-finance is realized, and manual operation links are reduced; the dynamic contract updating function enables the enterprise to quickly adapt to the business rule change, and the online period of a new business scene is shortened; the digital twinborn technology of the production management unit is fused with the AI model of the data analysis center, so that the decision accuracy of production scheduling and inventory management is improved, the resource configuration is optimized, and the problems of solidified process and slow response of the traditional ERP (Enterprise Resource Planning) are solved.

A pay sheet planning system includes a first information management unit that stores and manages, as a database, resolution information, on the basis of a resolution information input signal input through an input device of the manager computer; and a second information management unit that stores and manages, as a database, slip information, on the basis of resolution information, corresponding to a slip registration target selection signal input through the input device of the manager computer, in the resolution information that is generated, stored and managed through the first information management unit.

The application provides an enterprise resource planning system data flow conversion monitoring method, relates to the technical field of abnormal cause analysis in an enterprise resource planning system, and aims to solve problems such as difficult extraction of abnormal propagation causality, unexplainable traceability path, and low efficiency of quasi-real-time cause analysis in a multi-node complex business process. The core technical scheme includes the following steps: collecting and standardizing time series data of business key state indicators, establishing a local causal correlation cache by using a sliding window and a causal reasoning algorithm, recursively tracing back to an abnormal node as a terminal to form a preliminary causal path, screening high-confidence causal links through multi-dimensional time consistency evaluation, generating a simplified dynamic path by using a node semantic aggregation mechanism, and finally embedding the path in an operation and maintenance interface in the form of a visual trajectory to realize interactive cause analysis verification. The scheme improves the accuracy and explainability of abnormal cause analysis, realizes full-process automation and man-machine fusion optimization from data to root cause links, and significantly enhances the intelligent level of system abnormality handling.

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 application relates to a data query method and device, electronic equipment and a computer storage medium, and is applied to a system comprising multiple organizations, such as an ERP (Enterprise Resource Planning) system and the like; the method comprises the following steps: acquiring a query request sent by a client, the query request being used for querying data that can be used by a first organization; in response to the query request, determining an index value of the data that can be used by the first organization in a master table according to a first data model; the first data model comprises a first record, the first record recording index information of the data that can be used by the first organization in the master table, the master table recording a plurality of pieces of data and an index value corresponding to any one piece of data in the pieces of data, and the first record being a record corresponding to the first organization in the first data model; and obtaining a query result according to the index value of the data that can be used by the first organization in the master table. The technical scheme reduces the data quantity of a single table and the number of relationship tables that need to be maintained, and improves the query efficiency.

The invention discloses a cigarette order delivery warehouse intelligent matching method, system and device and a medium, belongs to the technical field of intelligent manufacturing and intelligent logistics, and aims to solve the technical problem of how to realize intelligent distribution and logistics cost optimization of multi-warehouse and multi-specification cigarette orders. According to the technical scheme, the method comprises the following steps: collecting relevant information of cigarette orders: obtaining order information, delivery warehouse information, customer address information, specification demand quantity and transportation cost information through an enterprise resource planning system, a warehouse management system or a geographic information system; data preprocessing: cleaning, normalizing and formatting the collected cigarette order related information, and constructing a data set; building an intelligent matching model of the cigarette order delivery warehouse: building the intelligent matching model of the cigarette order delivery warehouse through the processes of defining decision variables, minimizing the total logistics cost and setting constraint conditions according to the specification items of the order and the delivery warehouse information; and optimizing the cigarette order delivery warehouse intelligent matching model based on an improved adaptive algorithm.

A method and a system for verifying and synchronizing distributed data under an applet belong to the technical field of industrial internet and production, the method is executed by a manufacturing execution system, and the method comprises the following steps: receiving production execution data verified in real time by a mobile terminal; generating a production execution report and synchronizing the production execution report to an enterprise resource planning system to generate a process report; when report data is corrected, collaborative operation is triggered according to the generation state of a process report to maintain data consistency, and the system correspondingly comprises a data acquisition and verification terminal, a manufacturing execution system platform and an enterprise resource planning system platform to realize the collaborative operation. And an intelligent cross-system collaborative correction mechanism is constructed, so that the problems that data verification is lagged, cross-system synchronization is difficult and consistency is difficult to guarantee in traditional production are effectively solved.

The invention discloses an option rendering method and system based on million-level data, and the method comprises the steps: determining a visual region of a pull-down selector, and calculating the rendering range of the visual region and the rendering number of options according to the height and text length of the options; creating standard nodes based on the rendering quantity, and filling the display content of each initial option into each standard node; in response to a user operation of a user in the visual area, adjusting the display content of each standard node; and rendering each standard node, and displaying the rendered standard nodes in the visual area. According to the method and the corresponding system, the problems of inquiry lagging and state data loss under million-level data are solved, the method and the system are suitable for a high-frequency operation scene of an ERP (Enterprise Resource Planning) of a power supplier, the data rendering efficiency of the pull-down selector is improved, and the rendering time consumption is reduced.

The invention relates to the technical field of data processing, in particular to a data integration processing method and system for packaging an ERP (Enterprise Resource Planning) system, and the method comprises the steps: converting to-be-integrated data in the ERP system into feature vectors; clustering the to-be-integrated data according to the membership degree of the clustering center to which the to-be-integrated data belongs to obtain a plurality of target class clusters, determining fluctuation indexes of the target class clusters, and selecting an integration conflict cluster from the target class clusters based on the fluctuation indexes; determining a correction membership degree of the integrated conflict cluster; and clustering the to-be-integrated data in the integrated conflict cluster based on the corrected membership degree and the Euclidean distance to obtain updated ERP classified integrated data corresponding to the integrated conflict cluster. Therefore, the data integration accuracy of the ERP system is improved.

A system and method for centralized, automated procurement across multiple supplier platforms is disclosed. The centralized, mobile-optimized procurement system and process synchronizes in real-time with multiple supplier platforms, consolidates purchasing workflows, and supports intelligent decision-making through rule-based and AI-enhanced features. The disclosed system and method address inefficiencies in traditional procurement processes by introducing a centralized platform that aggregates supplier data, synchronizes inventory and pricing in real time, and enables automated order placement through intelligent agents. These agents, acting on behalf of the user, log into supplier websites using dedicated credentials and execute transactions without requiring supplier-side integration. The system maintains segmented data silos to ensure confidentiality across clients and suppliers, and supports dynamic cart management, including error handling, substitution recommendations, and business rule enforcement. Additionally, the platform is optimized for mobile use, overcoming limitations of conventional punch-out systems, and integrates with enterprise resource planning systems to provide real-time budget visibility.

The invention discloses a warehouse three-dimensional modeling and simulation system based on digital twinning, and relates to the technical field of digital twinning, and the system comprises a data interface layer which is used for connecting at least one of a warehouse management system, a warehouse control system, a sensor network and an enterprise resource planning system, therefore, the original data including the equipment state, the inventory information and the operation instruction can be obtained. According to the warehouse three-dimensional modeling and simulation system based on digital twinning, a digital main line layer and a consistency arbitration mechanism are introduced, and a closed-loop verification process based on historical behavior comparison is implemented on a simulation result, so that the data credibility of a digital twinning model and the accuracy of simulation prediction are effectively improved; therefore, the state information and optimization suggestions output by the system have higher reliability, solid data and decision support are provided for real-time scheduling, bottleneck diagnosis and long-term planning of the warehouse, and the overall efficiency and stability of warehouse operation are improved.

Disclosed herein are a system, method, and computer program product embodiments for recommending knowledge resources to resolve errors at a source and / or target system. For example, a request to post data to a target system is received from a source system. A determination is made that an error occurred with respect to the request. An error context for the error is determined. The error context comprises information describing the error and information describing the system. A representation of the error context is provided as an input to an ML model. The ML model is configured to predict a knowledge resource for resolving the error based on the error context. A prediction indicating the knowledge resource for resolving the error is received from the ML model. A recommendation to apply the knowledge resource on the source and / or target system is provided via a user interface based on the prediction.

According to some embodiments, a digital core for a cloud computing environment is associated with an enterprise (e.g., the digital core may comprise enterprise resource planning software optimized for an in-memory database). Moreover, an integration inspector framework may establish a checkpoint between an application system (e.g., a source application system to provide information via the digital core and / or a target application system to receive information via the digital core) and the digital core. The integration inspector framework then automatically validates a communication arrangement associated with the application system and performs a data replication test, in connection with the application system and the digital core, using test data. A result of the data replication test is then evaluated and indicated (e.g., to a user via a user interface).

This invention provides a logging method, logger, and storage medium, applicable to Enterprise Resource Planning (ERP) systems, such as manufacturing management systems, supply chain systems, human resources systems, financial systems, tax systems, and auditing systems. The method includes: extracting hierarchical relationships from objects to be processed; mapping each level in the hierarchical relationship to a node; organizing the nodes into a hierarchical structure for storage according to the hierarchical relationship; and using tags to record log information for each node in the hierarchical structure.

The technology described herein is directed towards product classification across multiple contexts within an enterprise environment, e.g., based on stock keeping unit (SKU-) related data. Relevant SKU attributes and patterns for each context are used to train machine learning-based classification models, which are then used to classify descriptive data of a product, such as one or more modules of a SKU. In one implementation, natural language processing and vectorization of input data are described to provide appropriate input to the trained classifier. Context-specific rules derived from domain knowledge and regulatory guidelines can be integrated to refine the classifications made by the model. The system incorporates integration with enterprise resource planning (ERP) systems, enabling efficient data management and classification within an existing infrastructure.

The invention provides an automatic implementation platform and an automatic implementation method based on an ERP system, and relates to the technical field of system integration, and the platform comprises an information collection module which is configured to respond to a service implementation request of a service request object, and receive at least one target service of the service implementation request and service parameter information of each target service; and a service configuration module configured to receive service coding data generated after the data coding system codes the service parameter information of each target service, and perform service configuration on each target service based on the service coding data of each target service and a configuration rule corresponding to each target service through an ERP system, generating service configuration information of each target service; and the service deployment module is configured to deploy each target service to a specified production system based on the service configuration information of each target service. According to the invention, the automation implementation efficiency based on the ERP system is effectively improved.

The invention relates to a method and a system for generating different product production process flows. The method comprises the following steps: creating a process flow group in an enterprise resource planning system; performing group class setting on the created process flow group to obtain a process flow group subjected to group class setting; determining a process flow chart on an editing flow chart page corresponding to the process flow group subjected to group class setting; adding preset production process specification data into the process flow chart to generate a process flow chart of the to-be-produced commodity; and storing the process flow chart of the to-be-produced commodity into a database of an enterprise resource planning system, inputting the commodity, and calling out the corresponding process flow chart to guide commodity production. According to the method, common process flows can be classified and templated by creating the process flow groups and setting the group classes, so that the consistency of production process execution is ensured, and standardized management of the production flows is realized.

The invention relates to a material project package fund distribution management method and system based on a generative model, and the method specifically comprises the following steps: obtaining multi-modal data of a target power grid engineering material project package from at least one business database, the business database comprises an enterprise resource planning system, a material management platform and a document management system; the multi-modal data comprises structured data and unstructured data; performing normalization processing on the structured data by adopting a Z-score standardization method, and converting the unstructured data into a text feature vector with a fixed length by utilizing a BERT-BiLSTM hybrid neural network model of an improved attention weight mechanism; and adopting a multi-head attention mechanism to carry out adaptive weighted fusion on the preprocessed structured data and the text feature vector to form a unified mixed feature matrix.

The invention discloses an assembly control system, method and equipment for a vehicle. The vehicle assembly control system comprises an enterprise resource planning unit which generates a whole vehicle production work order according to a sales order and maintains controller material data; the warehouse management unit is used for receiving the material data of the controller, recording the production batch information of the warehouse-in controller and the position and the number of the warehouse-in controller, and picking the controller for warehouse-out according to a first-in first-out rule according to a demand instruction of the controller during warehouse-out of the controller; the production line is used for binding the vehicle identification code with the serial number of the controller which is delivered out of the warehouse by the warehouse management unit; and the manufacturing execution unit receives the production work order and sends a controller demand instruction to the warehouse management unit. By adopting the embodiment of the invention, the controller matched with the assembled vehicle can be effectively called from the inventory, and potential safety hazards caused by long-term storage of the controller in the inventory can be avoided, so that the safety and reliability of the vehicle production and assembly process are ensured, and the vehicle production and manufacturing efficiency is improved.

The application discloses a composite machine production method, relates to the technical field of computers, and obtains various production instructions by analyzing production requirements of the composite machine through an order assembly system; generates a sales order through an enterprise resource planning system; splits the sales order through a customer relationship management system to obtain a first material list, and determines a second material list based on a material damage ratio; locks target material inventory based on a supply chain planning and optimization system through the enterprise resource planning system, splits the production instructions based on the locked target material inventory to obtain various machine production work orders; and performs corresponding machine production on the various machine production work orders through a production execution system and a production line to obtain the composite machine, improves the efficiency and accuracy of composite machine production, and realizes efficient management, control and tracing of the composite machine order.

A computer-implemented method for improved backorder processing (BOP) in an enterprise resource planning system is disclosed. The method can receive one or more user prompts from a user interface and create a BOP segment using a large language model. The BOP segment selects a subset of a plurality of order requirements using one or more filters determined based on the one or more user prompts. A filter is defined by an attribute, an operator, and one or more attribute values. The method can create a BOP variant using the large language model. The BOP variant defines a confirmation scheme for the BOP segment based on the one or more user prompts. The method can further execute the BOP variant using the large language model, including batch processing the subset of the plurality of order requirements using the confirmation scheme.

The present application relates to the technical field of informationization of oil exploration and development and digital processing of whole life cycle management of industrial assets, in particular to a whole life cycle operation and maintenance management system for an oil downhole transmitter, comprising: an asset data management module for building a whole life cycle data lake serving asset value analysis; a benchmark valuation modeling module for generating a theoretical asset value curve of the transmitter under the assumption of no environmental stress; a risk quantification correction module for outputting a risk-adjusted theoretical residual value; a management performance analysis module for calculating a management performance residual after stripping the influence of environmental risks; a decision and execution module for automatically generating differentiated management instructions for asset disposal, inventory strategy adjustment or supplier evaluation, and driving downstream enterprise resource planning systems or inventory control systems to perform closed-loop operations; the present application effectively solves the phenomenon of shirking operation and maintenance responsibilities due to poor well conditions.