Transforming Process Visibility for a Major Distillery
- Chakravarthi Gera
- Sep 21
- 2 min read
Client Overview
A leading distillery in India, known for its high-volume ethanol production, faced significant operational challenges due to its reliance on handwritten logs for capturing critical process parameters. These manual systems created bottlenecks in data visibility, hindered analysis, and slowed down decision-making.
Business Challenge
The distillery’s continuous production environment demanded:
Uninterrupted monitoring of process parameters
Customizable data capture flows sensitive to feedstock variations and tank transfers
Accurate mapping of data from Distributed Control Systems (DCS) to specific recording times
A centralized system for audit trails, collaboration, and real-time insights
Handwritten logs were no longer sufficient to meet these needs, resulting in missed recordings, delayed approvals, and limited ability to optimize yield.
Solution Delivered By Hopnet
We developed a custom E-Logbook solution using the Frappe framework, tailored to the distillery’s continuous process requirements. The platform was designed to:
Digitize the entire distillation process management
Integrate seamlessly with DCS systems for real-time data capture
Enable mobile and on-premise access for operators and managers
Provide timely alerts for data entry and anomaly detection
Support future integration with machine learning for predictive insights
Key Outcomes
1. Rapid Deployment
Delivered in just 40 days, transitioning smoothly from proof-of-concept to production
2. Improved Yield
Achieved a improvement in final ethanol yield through better process control and data-driven optimization
3. Zero Missed Recordings
Automated alerts and mobile access ensured complete data capture across shifts
4. Real-Time Process Visibility
Operators and analysts gained instant access to quality-critical parameters
Enabled root cause analysis for low yield and process deviations
5. Seamless ERP Integration
Automatically fetched raw material data to flag low-quality batches
Ensured consistent product quality and maximized profitability of byproducts like CO₂, livestock feed, and fertilizer
6. Scalable and Cost-Efficient
Built on Frappe, an open-source framework, allowing for license-free deployment
Modular design supports future enhancements including machine learning and automated anomaly detection
