• Expertise in AI-driven IIoT: FabMetrics specializes in providing AI-driven IIoT digital services to Machine Builders and OEMs, demonstrating their knowledge and experience in the field.
• Revenue Generation Potential: FabMetrics recognizes the significant revenue potential of IIoT digital services for Industrial equipment providers, estimated at $75 billion within five years.
• Low Code Platform and Plug-and-Play Vision: FabMetrics offers a user-friendly low code platform and a plug-and-play approach, enabling machine manufacturers to quickly configure and deploy digital services with low initial investment.
• Comprehensive Product Offerings: FabMetrics provides a range of products including data collection, performance monitoring, data visualization, and AI analysis, offering end-to-end solutions for clients.
• Ready-to-Use AI Models: Unlike competitors, FabMetrics offers pre-built AI models, reducing complexity and time in deploying AI solutions.
• Targeted Focus and Geographical Reach: FabMetrics focuses on specific segments within the machine manufacturing industry and has identified key target areas for growth, including Germany, the Netherlands, Italy, and Turkey.
• Existing Customer Base: FabMetrics has established relationships with reputable customers, demonstrating their credibility and ability to deliver value in the industry.
FabMetrics employs a N-tier architecture. The system is built on native-cloud services which means no server needed and the system is scalable even for extreme IoT data messaging. FabMetrics Insight and FabMetrics MES are browser based applications reaching to a NoSQL database over the application APIs. The APIs can serve external systems as well. Data sources such as PLCs, SCADAs or any other manufacturing / quality management system are connected via FabMetrics Gateway which is an edge-solution. FabMetrics Gateway is a lightweight Linux program comprised of a message workflow system and docker containers. Its objective is to run edge AI algorithms, data harmonization and cost optimization for data acquisition. FabMetrics AI is a tool to setup pipelines for Machine Learning models and statistical analysis on streaming data. The models are trained on the cloud services and it can be deployed to the edge over FabMetrics Gateway or cloud services. Our requirements, and more information about how FabMetrics is installed/deployed you can contact us over the demo form. So our team can make you a demo and explain the details.
FabMetrics uses subscription-based licenses per connection points (PLC, SCADA, Quality Control Points etc.)
FabMetrics provides you a single solution where you can see the digital shadow of your factory and manage it with data analytics. Shop floors have ample of opportunities to optimize:
• Reducing cycle time by identifying bottlenecks
• Increasing equipment efficiency (OEE) by reducing downtime
• Reducing scrap / rework / NOK products by optimizing process variables
• Besides, it is impossible to detect the real top priorities and emerging problems without real time visibility.
For Machine Builders and OEM, the Live monitoring of machines with IoT data will help you:
• to increase service revenues and customer satisfaction with the prediction of machine breakdowns
• to provide digital products to its clients : digital / smart factory portal and MES (Manufacturing Execution System).
• to optimize the design by analyzing variables on the manufacturing field and its impact on the machine design space
• to offer an AI assisted smart setup solution by analyzing historical process data to speed-up setup process of the clients
• to provide predictive maintenance and minimize customer downtime
• Monitor the warranty and machine usage conditions
Provides you a valuable data warehouse with Digital Shadow of your machines on the site!
To get started with FabMetrics there is no need for any historical data, because FabMetrics depends on new data sent to the system to set up its understanding.
Yes. When you request a demo please let us know what kind of data (machine data, quality control etc.) you want to test the solution with. We have ready tools to convert historical data files to simulate real-time data.