Abstract: Providing visualizations of relationships among multi-dimensional data models for manufacturing intelligence systems. Storing configuration data in an intelligence data store under a configuration schema enables a multi-dimensional model visualization. The multi-dimensional data model visualization depicts all of the many-to-many, dynamic relationships between objects in a single display.

Abstract: Providing visualizations of relationships among multi-dimensional data models for manufacturing intelligence systems. Storing configuration data in an intelligence data store under a configuration schema enables a multi-dimensional model visualization. The multi-dimensional data model visualization depicts all of the many-to-many, dynamic relationships between objects in a single display.

Abstract: Providing visualizations of relationships among multi-dimensional data models for manufacturing intelligence systems. Storing configuration data in an intelligence data store under a configuration schema enables a multi-dimensional model visualization. The multi-dimensional data model visualization depicts all of the many-to-many, dynamic relationships between objects in a single display.

Abstract: A software agent is described that receives an information request to retrieve information based on a name defined by a configured manufacturing data model. The agent serves the request by relating data coming from one or multiple backend systems and adding contextual data (Metadata). A result set is prepared to correspond to the format and filtering criteria defined in the information request, and the agent produces a response in a normalized format. The response contains the requested data and metadata used for navigation and contextualization purposes. The response in the normalized format is transmitted by the agent synchronously or asynchronously based on criteria specified in the request.

Abstract: A software agent is described that receives an information request to retrieve information based on a name defined by a configured manufacturing data model. The agent serves the request by relating data coming from one or multiple backend systems and adding contextual data (Metadata). A result set is prepared to correspond to the format and filtering criteria defined in the information request, and the agent produces a response in a normalized format. The response contains the requested data and metadata used for navigation and contextualization purposes. The response in the normalized format is transmitted by the agent synchronously or asynchronously based on criteria specified in the request.