Driving AI-Powered Manufacturing Intelligence with FactoryGPT for a Global Packaging Equipment Manufacturer
A global maker of high-speed rotary filling and liquid food packaging systems spent too long finding the cause of downtime and OEE losses. FactoryGPT connected machine, historian and maintenance data and let teams ask questions in plain language.
- Client
- Global manufacturer of rotary filling and liquid food packaging systems
- Industry
- Packaging equipment
- Solution
- ITHENA FactoryGPT
- Scope
- PLEX, FTDM and FiiX integration, conversational analytics, agentic maintenance workflows
- Headline result
- 3x faster drill-down into issues
Three numbers the plant moved.
Results after FactoryGPT went live on the client's production data.
Faster drill-down into production issues
Plain-language questions surfaced downtime causes and OEE losses in seconds.
AI-powered factory intelligence assistant
Operators and managers reached production insight at any hour through the AI assistant.
Increase in maintenance responsiveness
Detected anomalies triggered maintenance actions automatically.
Meet the organization and understand the context behind the transformation.
A global manufacturer of high-speed rotary filling systems and advanced liquid foods packaging solutions. Facing challenges in downtime analysis, fragmented production data, and delayed maintenance response, the client partnered with ITHENA to implement the FactoryGPT solution. The outcome was real-time conversational factory intelligence, AI-driven operational insights, and automated maintenance workflows that improved production visibility, reduced downtime, and accelerated decision-making across plant operations.
FactoryGPT transformed how our teams interact with production data. Instead of relying on multiple dashboards and manual analysis, we can now identify root causes, trigger maintenance actions, and make operational decisions and action in seconds using natural language.
– Director of Manufacturing Operations
Answers buried across too many systems.
Machine, historian and maintenance data sat apart, so root cause analysis was slow.
- Slow root cause analysis for downtime and OEE losses delayed corrective actions and impacted throughput
- Disconnected machine, historian, and maintenance data created fragmented operational insights
- Reliance on dashboards and manual processes slowed decision-making and maintenance response
- Operators lacked instant access to troubleshooting knowledge and historical maintenance information
How ITHENA closed the gaps.
ITHENA’s FactoryGPT solution empowered the client with:
Unified Industrial Data Integration
Connected machine sensors and data from PLEX, FTDM, FiiX, and other manufacturing systems into a centralized LLM-powered intelligence platform
Conversational Factory Intelligence
Enabled operators and plant managers to query production data using natural language and receive instant insights into downtime events, OEE losses, and machine performance issues
AI-Powered Analytics
Continuously monitored machine data, throughput, filling accuracy, cycle times, and downtime trends to detect anomalies and uncover hidden production losses in real time
Agentic AI Workflows
Automated operational actions by triggering maintenance work orders, dispatching service teams, and enabling proactive response workflows based on detected production anomalies
Ask the factory what went wrong.
An illustrative FactoryGPT view: anomalies on the filler are flagged as they happen, and operators ask plain-language questions and get the root cause and next action.