181 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 relates to the technical field of cloud computing, and discloses an enterprise resource planning data efficient processing method based on cloud computing, and the method comprises the steps: collecting system data of finance, supply chain, production management and the like through a multi-source interface module, and carrying out the preprocessing through a hierarchical fusion framework, thereby obtaining a standardized data set; the method comprises the following steps of: selecting a multi-target scheduling model, inputting the multi-target scheduling model into a task decomposition model, generating task decomposition parameters based on a block processing mechanism and a service association rule, constructing the multi-target scheduling model aiming at the shortest processing duration and the minimum resource occupation, and outputting an optimal scheduling scheme by adopting a dynamic allocation algorithm. A hierarchical execution control model comprising a strategy layer, a coordination layer and an execution layer is established, the strategy layer performs global task planning, the coordination layer performs local resource adjustment, and the execution layer tracks tasks based on a load balancing algorithm and outputs a processing control instruction to realize efficient processing. The method improves the data processing efficiency and the resource utilization rate, and provides support for enterprise decision making.

The invention relates to the technical field of data management, and discloses an automatic collaborative decision-making method, system and equipment for enterprise resource planning, a medium and a product, so as to solve the problem of low automatic decision-making efficiency of an existing enterprise resource planning system. The method comprises the following steps: constructing a multi-agent reinforcement learning model, designing a global reward function and a local reward function, constructing a potential function of the local reward function, and training based on training data to obtain a collaborative decision model; collecting work information of each collaborative workflow to obtain business data; calling a collaborative decision model to perform collaborative decision on the business data according to the global reward function and the local reward function, and performing reward shaping on the local reward function based on the potential function to generate a business strategy; generating a decision instruction based on the business strategy according to the labor division content of each actuator in the enterprise resource system; and each actuator executes the corresponding decision instruction, monitors the execution process in real time, records the execution result, generates feedback information, and updates the work information.

A computer-implemented method can run an application associated with an intelligent scenario deployed on an enterprise resource planning (ERP) system. The application receives input values for one or more parameters from a tenant user through a user interface of the ERP system. The method can select a prompt template defined in the intelligent scenario, generate a prompt using the prompt template by replacing the one or more parameters included in the prompt template with respective input values, prompt a large language model (LLM) specified by the intelligent scenario using the prompt, receive a response generated by the LLM, and present the response on the user interface of the ERP system.

The invention discloses an intelligent optimization system for enterprise resource planning, and relates to the technical field of enterprise resource management, and the system comprises a data collection and preprocessing layer, a knowledge construction and reasoning layer, a risk early warning and decision support layer, and a resource scheduling and execution layer. According to the invention, a knowledge graph covering various resources of an enterprise and association relationships thereof is constructed by using preprocessed data through a knowledge construction and reasoning layer, a causal relationship network among the data is established, and meanwhile, an intervention effect evaluation unit combines an anti-factual reasoning result of a causal reasoning unit to evaluate the intervention effect of the enterprise. Quantitative evaluation is carried out on different resource pre-allocation intervention schemes, and a detailed evaluation report is output, so that an enterprise can perceive and take corresponding measures in advance before a risk occurs, and can select an optimal scheme according to a scientific evaluation result when a resource planning decision is made, thereby effectively ensuring stable operation of enterprise resources, and improving the resource planning efficiency. And the operation risk caused by the resource problem is reduced.

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.

A computer-implemented method receives a request to explain a configuration key which represents a set of rules for controlling a process flow of an entity of an enterprise resource planning (ERP) system, the set of rules defining a data operation scheme based on a plurality of tables stored in a database of the ERP system. The method generates a data object from the plurality of tables, the data object including a group of key-value pairs which collectively define the set of rules, preserving the hierarchy of the involved tables. The method generates a prompt based on the data object generated from the plurality of tables, prompts a large language model using the prompt, receives a response from the large language model, and based on the response, outputs an explanation of the configuration key summarizing the set of rules in natural language. Related computing system and software are also disclosed.

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.

The invention provides a configurable ERP (Enterprise Resource Planning) system, method, equipment and medium for automatically saving certificates, and belongs to the technical field of ERP system management, and the ERP system comprises the following steps: a certificate editing module receives certificate information input and editing operation of a user; the non-strict checking module monitors whether the voucher information contains a core accounting element or not in real time; the strict detection module performs financial rule verification on the voucher information containing the core accounting elements; the automatic storage module automatically stores the voucher information passing the financial rule verification when a preset automatic storage triggering condition is met; the incomplete voucher management module allocates temporary numbers to the incomplete vouchers and performs financial rule verification again after the user supplements the incomplete vouchers; and if the user storage priority module receives a manual storage request of the user, the current automatic storage process is interrupted, and manual storage is executed preferentially. The method prevents data loss, improves the working efficiency, adapts to multiple scenes, optimizes the user experience, and guarantees the safety of financial data.

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.

The invention relates to the technical field of enterprise resource management, in particular to an enterprise management optimization method and system based on big data, and the method comprises the following steps: capturing data of employee skills, a project execution process and customer interaction according to enterprise resource planning in an enterprise, analyzing the captured data, and carrying out the multi-dimensional information classification processing; and constructing an enterprise resource comprehensive data set. According to the method, the flow and utilization efficiency of the resources is improved by establishing the graphic database to integrate the enterprise resources and converting the data elements into the network nodes and the connecting edges, and the resource flow and utilization efficiency is improved by identifying and analyzing the association strength of the nodes and the weights of the edges in the resource network. Through detailed flow path analysis, an enterprise can formulate a scientific resource allocation strategy according to market requirements and current resource situations, resource allocation and use are optimized after dynamic resource allocation is implemented, the strategy is adjusted in time by comparing and analyzing resource efficiency and cost effectiveness before and after optimization, and the market response speed and competitiveness of the enterprise are remarkably improved.

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 invention relates to the technical field of enterprise resource planning, and discloses a sales method, system and device and computer equipment, the sales method is applied to a management platform, and the method comprises the steps: obtaining customer order request information of each store in a preset time period, and generating an order and an order number of a corresponding store based on the customer order request information; based on the order number and a preset auditing condition, auditing the order of the corresponding store; after the verification is passed, a store delivery order is generated based on the order, the market inventory condition and the delivery strategy; and picking up the goods from the market warehouse to the corresponding store warehouse based on the store delivery order and the order deposit number, so that the store warehouse picks up the goods to the customer according to the goods picking application, the exclusive auditing rule is made for different market stores, the belonging market is accurately determined, and the purpose of accurate goods picking of the customer is achieved.

The invention discloses a commodity purchase price floating calculation device and method based on ERP, and relates to the field of material purchase. The device comprises a data acquisition module used for acquiring daily prices of bulk raw materials and recording protocol reference prices, price difference thresholds and price floating thresholds of the bulk raw materials; the price calculation module is used for calculating the price of the bulk raw material according to the size relation between the difference value between the daily price of the bulk raw material and the protocol reference price of the corresponding bulk raw material and the price difference threshold value and / or the size relation between the price floating between the daily price and the protocol reference price and the price floating threshold value. Determining the types of bulk raw materials for commodity price calculation, and calculating the latest price of the commodity according to the determined types of the bulk raw materials; and the price tracing module is used for providing a query interface and feeding back the historical price of the commodity and the price calculation process according to the input information. The technical problems that in the prior art, a calculation formula for agreed execution prices is large in calculation amount, low in efficiency and incapable of tracing to the source are solved.

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.

A system for automated, middleware-based intelligent data mapping between heterogeneous enterprise resource planning (ERP) systems and cloud platforms, the system comprising the following: an ERP data acquisition unit with a variety of physical communication ports, selected from Ethernet and serial ports, a network interface controller physically connected to the communication ports, and a DMA (Direct Memory Access) controller configured to transfer raw ERP data packets into a volatile buffer memory without processor intervention; a Semantic Mapping Unit consisting of a Field Programmable Gate Array (FPGA) configured as a lexical analyzer to analyze ERP schema definitions and extract entity descriptors, and a Tensor Processing Unit (TPU) configured to evaluate the semantic similarity between heterogeneous schema elements based on ontological models stored in a non-volatile memory repository; a transformation logic unit comprising a parallelized vector processor configured to perform matrix-based transformations, field normalizations and structural reorganization of ERP data into a harmonized format, and a rule application circuit configured to perform compliance-based anonymization, unit conversions and value scaling prior to cloud distribution; a cloud interface unit comprising a protocol adapter bank with encoders, translators, and message queue writers, wherein the cloud interface unit is coupled with a cryptographic controller configured with a hardware public key infrastructure (PKI) circuit to generate digital signatures and verify integrity codes for all outgoing payloads; and a Feedback Learning Control Unit implemented in the firmware, wherein the engine is electrically coupled to the Semantic Mapping Unit and the Transformation Logic Unit and is configured to monitor error logs, success rates and acknowledgment codes received from the cloud platforms and to update the semantic and transformation rules stored in the non-volatile memory repository accordingly.

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.

The invention belongs to the technical field of aero-engine assembly, and particularly relates to a piston type aero-engine intelligent assembly system which comprises a remote server. The system comprises an enterprise resource planning system server, a manual receipt input end, a large display screen, a large display screen server, station equipment, a manufacturing execution system server, a warehouse management computer, an industrial Ethernet, a module, a laser marking machine, a leakage tester, a printer, a wireless network, a code scanning gun, an AGV, an AGV scheduling system and an Ethernet. Functional modules of the manufacturing execution system are divided into plan management, quality data, real-time data, statistical analysis, equipment management, system setting, system management and the like.

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.