AI in Manufacturing: Production Execution
Production Execution Management is the fundamental process on a manufacturing shopfloor control. All activities ranging from supply chain and inventory management to production planning and quality control play a supporting role in helping companies deliver quality products with efficiency. Manufacturers are challenged with achieving efficient production runs, quality control, access connectivity, automation, and efficient resource utilization.
At SymphonyAI Industrial, we offer an innovative AI-embedded Product Execution capability from our Manufacturing Execution System (MES) offering for discrete, process and analytical manufacturing industries. In this webinar we will use a discrete manufacturing example and cover the production manager, operator, maintenance technician and quality control personas. Additionally, highlight the ease of integrating our MES with Level 2 and Level 4 systems as well as measure and optimize the Key Performance Indicators using AI-embedded analytics.
Panelists: Srinivas Kuppa - Chief Strategy Officer
Domenic Busa - Pre-Sales Engineer
Accelerating Furnace Performance with AI
In this webinar, we will look at how advanced AI and machine learning models are combined with forecasting models and optimizers to improve melting furnace operations for improved yield and energy management in glass manufacturing.
Panelist: Prashant Srinivasan - Director, AI Products & Applications • Product Engineering
A Scalable AI and IoT Platform for Manufacturing
In this webinar, we will look at how a modern component driven architecture can be leveraged to build a highly scalable cloud-enabled AI platform for near real-time processing with high-volume data ingestion and AI-powered analytics.
Panelists: Raghavan Chockalingam - Engineering Manager • Product Engineering
Venki Tirumala - Director, Software Apps • Product Engineering
Moving from SPC to AI-based Process Automation
This webinar focuses on the approach for enhancing the plant performance through process automation using AI based deep state space models (moving away from if/else rules) in combination with optimization for process control.
Panelist: Bhasker Keely - Senior Principal Data Scientist
Real Time Sensor Fault Detection with AI
In this webinar, we will examine the data science algorithms and AI models to detect sensor instrumentation faults in industrial setup in real-time to differentiate between instrument problems and actual machine or process faults.
Panelist: Sudeep Gowrishankar - Product Manager • Product Engineering
Digital Twins for Remaining days to failure & what if performance analysis
In this webinar, we will examine digital twin models to forecast conditions, simulate “what-if” scenarios and optimize actions to simultaneously extend the remaining time to failure and improve system availability.
Panelist: Venkatesh Raman - Principal Engineer • Product Engineering
Reducing Analysis Costs by 33% - a Case Study
In this PdMTalk, we will look at a $4M reduction in vibration program and workforce costs while also increasing the visibility of asset health.
Panelist: Michael DeMaria - Director, Product Mgmt & Training