A system and method are disclosed for executing and monitoring changes in a warehouse plan. The method includes receiving an initial warehouse plan, receiving a changed warehouse plan, receiving user input defining a scope, capturing, via sensors, real-time data to determine execution changes, identifying warehouse execution changes based on the captured real-time data, outputting an execution changes report, using the received initial warehouse plan, the received changed warehouse plan, the identified warehouse execution changes and the defined scope of warehouse analysis to identify changes in the initial warehouse plan and generate required tasks, generating a task and changes report for tasks based on the identified changes, receiving warehouse information, determining a task priority and task schedule, outputting a dynamic task sequence and task schedule, beginning real-time electronic monitoring of user performance, and in response to the monitoring of user performance, changing the dynamic task sequence and task schedule.

A method and system for providing technical service to an agricultural working machine. A digital service module of a server, configured to coordinate the technical service, may receive a request for service. The request for service may include at least one part and at least one service needed to fix the problem of the agricultural working machine. The digital service module is divided into a plurality of subsystems and follow a multi-target optimization strategy during planning and implementing the service events.

A system and method for managing a stocking of a warehouse on a farm. The system comprises a server, a database, and a computational device. A module for managing the stocking of the warehouse with spare parts and information and/or criteria regarding the stocking of the warehouse are stored in the database. The module is executable by the computational device, with the server hosting the module for the computational device. Upon execution of the module by the computational device, the module is configured to automatically plan, coordinate, and supervise the stocking of the warehouse with spare parts based on the information and/or criteria stored in the database.

A spare parts planning system and method for planning and coordinating spare parts for agricultural machines. The spare parts planning system may be configured to perform planning and coordination of spare parts for a service order, with the service order being derived from the definition of a customer problem. The spare parts planning system may additionally be configured to assemble the spare parts stock stored in the respective warehouse in such a way that the spare parts stock is adapted to the expected parts failure probability, with this adaptation comprising the storage of the spare parts and/or the procurement of the spare parts from central warehouses.

A technician planning method and system for planning agricultural machine technicians to plan and coordinate repairs and/or maintenance of agricultural machine. The technician planning method and system includes a server, a database, and the communication device. The server receives a customer problem from a customer communication device regarding the repair and/or maintenance of the agricultural machine. The customer problem initiates a delivery of a spare part and a technical service, with information being stored in the database concerning the location and/or the delivery possibilities of the spare part. The technician planning system is configured to determine at least one deployment planning of the agricultural machine technicians for the service order with respect to the technical service. The service order is derived from a definition of the customer problem and one or more planning criteria stored in the database with respect to the agricultural machine technicians.

A method and system for performing an agricultural process in line with an insurance policy. An agricultural working machine is operated by a customer. A digital service module, which may be hosted on a server, comprises an insurance policy management system to ensure to stay in line with the insurance policy at least partly while performing the agricultural process. The digital service module plans and implements the service events based on an optimization strategy, which may comprise a multi-target optimization strategy based on a number of weighted optimization criteria, which may be at least partly derived from insurance policy information.

A system and method for planning technical service to at least one agricultural machine on at least one farm in a region. The system comprises a server, a database and a computational device. A module, executable by the computational device, for planning technical service to the at least one agricultural machine and a crop cultivation map for the region are stored in the database. Upon execution of the module by the computational device, the module is configured to generate a service network plan for the region to provide technical service to the at least one agricultural machine based on the crop cultivation map.

A system and method for managing a warehouse on a farm. The system comprises a server, a database, and at least one user end device. A module for managing the warehouse and information and/or criteria for managing the warehouse is stored in the database. The module is executable by the at least one user end device and the server is hosting the module for the at least one user end device. Upon execution of the module by the at least one user end device, the module is configured to manage a stock of spare parts in the warehouse based on the information and/or criteria stored in the database.

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.

An artificial intelligence as a service (AIaaS) system of copper procurement decision support is provided. The AIaaS system includes a storage device, a processing device, a developer interface, and a user interface. The storage device includes a copper material database and a source code repository, and the processing device executes a plurality of control instructions to access the copper material database and the source code repository, so as to execute a copper material price forecast module, a copper material demand forecast module and a scrap copper price forecast module. The developer interface is used by the developer to establish a copper material price forecast artificial intelligence model, a copper material demand forecast artificial intelligence model, a scrap copper price forecast artificial intelligence model, and the user interface is used by an operator to select and deploy artificial intelligence models to generate a copper material forecast price, a copper material forecast demand and a scrap copper forecast price, and the user interface is used by the decision maker to access forecast results to generate a copper procurement decision support suggestion.