Improve efficiency, production management and quality with a proven, modular MES for process, discrete and mixed manufacturing data.
Proficy Manufacturing Execution Systems
Consolidate and transform manufacturing data across plants for cloud storage, analysis, and analyticsView demo
With Proficy Manufacturing Data Cloud (Proficy MDC), part of the GE Digital's Manufacturing Execution Systems suite of solutions, you can easily and quickly increase the derived value by reliably bringing enterprise-wide manufacturing data into the cloud and transforming it into a structured data set.
Proficy MDC enables the consolidation of three data sets required for process optimization and analytical applications: asset data, ERP data, and manufacturing data.
See how to build a ProficyMDC application to identify the best and the worst performers using data from several plants. You will also see how Predix MDC can be used to simply identify defects in batches causing customer complaints.
The new Proficy MDC 1.4 features:
Provides a reliable way to ingest manufacturing data into Proficy Platform Cloud and transform it into a usable format with S95-based contextual and aggregated data model. The transformed data models are accessible through easy-to-use and quick-response APIs.
Separate the storage of historic and static data (cold data) from required data (hot data) to reduce on-site storage and maintenance costs through cloud server technology. Speed on-premises queries to improve operations agility.
Integrates data with multiple systems, creating an enterprise data set for reporting and analysis. Move raw and contextual data to data lakes to pool data into a single location, making it easy and fast to create a context for manufacturing analytics and improve operations.
Proficy MDC ensures that your data is stored and managed in a secure-by-design way. Specifically built for manufacturing, the solution is fully managed with 24/7 monitoring.
Capture all production-related data for cloud storage & enable common enterprise-wide reporting and analytics across several plants
Without having to rely on human intervention, incremental data can be automatically ingested.
Edge monitoring, remote configuration, and deployment.