- Details
- Hits: 891
- Header Image : /images/banners/metaphacts-use-cases-banner.jpg
The Bosch Materials Science Knowledge Graph powers a smart business application for material research and development built with metaphactory. As a one-stop knowledge hub for materials and chemical component information, the application supplies high-quality answers about existing materials in a timely manner and supports engineers in developing and introducing new materials for production.
Here you can learn more about the Bosch Materials Sicence Knowledge Graph »
- Details
- Hits: 1657
- Header Image : /images/banners/metaphacts-use-cases-banner.jpg
metaphactory was used by this German industrial manufacturing company to build a bill of material application that consolidates customer and purchase information, as well as order history information. The application can be used to track customer-specific product configurations, plan the fulfillment for new orders, and determine the spare parts required for maintenance and service requests.
- Details
- Hits: 991
- Header Image : /images/banners/metaphacts-use-cases-banner.jpg
metaphactory was used by this German industrial manufacturing company to build an industrial configuration management application which provides an overview into the product and parts features, requirements and dependencies. Product managers, support engineers, technical planners and technical maintenace specialists can use the application to maintain configurations, determine how components fit together and how they can be combined to create solutions that solve very specific customer needs or maintenance requests while staying within a predefined budget, and forecast materials and parts required for production.
- Details
- Hits: 899
- Header Image : /images/banners/metaphacts-use-cases-banner.jpg
Siemens AG is one of the leading providers of factory automation solutions and components as well as Manufacturing Execution Systems and Product Lifecycle Management Software. To support human manufacturing planners and line operators in their daily tasks and increase the autonomy of production machinery, the research group for "Semantics and Reasoning" of Siemens Corporate Technology initiated a Manufacturing Knowledge Graph leveraging metaphactory. The goal was to test the feasibility of Smart Manufacturing Planning and Smart Manufacturing Execution concepts utilizing semantic technology. For this, the team created a Manufacturing Knowledge Graph to capture heterogeneous data sources and expert knowledge and built an AI-based knowledge graph application to automate the allocation of suitable production equipment.
The results
The feasibility studies conducted proved that:
- The number of possible plans and configurations that human planners need to evaluate can in some situations be reduced from approx. 1,400 to as few as 40.
- The realization of low-volume orders is feasible and can become affordable by enabling machines to act autonomously.
Learn more
To learn more about this solution, download the full case study here »
- Details
- Hits: 884
- Header Image : /images/banners/metaphacts-use-cases-banner.jpg
As a consortium member in the Geiser project, metaphacts focused on designing and implementing scalable backend services for the storage, retrieval, and processing of semantic geo data, by combining state-of-the-art semantic data management with Big Data technologies for scale-out and GPU acceleration. The technology was implemented in an operational planning use case where machine sensor data was integrated and correlated with technician operational schedules and spare parts management systems to improve maintenance operations, reduce wait times, and minimize downtimes.