Molins: Vertical Raw Mill Energy Optimization
Real-time optimization
The results show growing savings ranging from 5% to 10% in the power consumption per ton of product produced (kWh/t) from first recommendations, plus increased quality and throughput, with an additional productivity of 14.6 t/h.
From 2017
Ongoing Service
Vertical raw mill energy optimization to respect product quality at all times
Client
Cementos Molins, Barcelona (Spain).
Industry
Electric power
3600 kW
Production
340 t/h
Control
F. L. Smidth
Controlled
6 Variables
Why AI, Why Now?
Shaping the future of the Cement industry
Maximizing productivity while minimizing energy needs in a raw mill is a complex challenge due to the constant need to balance quality constraints like fineness and humidity. Additionally, operators must keep vibrations under strict thresholds and ensure overall process stability. Manual set-point adjustment often fails to capture the optimal efficiency window, creating a clear opportunity for OptibatĀ® to provide real-time, data-driven autonomous control.
The Problem
In its factory near Barcelona, the customer manufactures and markets cements, both melted and Portland. The vertical raw mill is responsible for grinding and drying the raw material before being introduced in the clinker kiln. The grinding process is done through vertical pressure of rollers against a circular movement table.
The material falls from the mill and exits under the action of centrifugal force by an air exhauster fan. The major energy consumptions are caused by motor of the rotating table, the separator and the air exhauster fan. Productivity has to be maintained above target values, quality of the product needs to respect constraints of fineness and humidity at all times, while vibrations have to be kept under thresholds and the process is maintained stable without interruptions in production. In this context, minimizing energy needs is a difficult challenge.
The Solution
OptibatĀ® has been setup, providing significant energy savings, while maintaining and even improving the productivity and the product quality.
OptibatĀ® is connected to the existing control system, learning from data, reporting potential savings and recommending in real time the optimum set-points values for the following variables:
- Power of air exhauster fan.
- Inside differential pressure,.
- Inlet pressure.
- Outlet temperature.
- Pressure of grinding rollers.
- Spray water flow.
Constraints are strictly respected, including vibrations of the mill, thickness of grinding layer, output quality like thickness and humidity of grinded material, operating limits of the mill components, production rates, and stability of the process.
Quality
The system improved product fineness by 5.59% while strictly respecting all technical constraints. OptibatĀ® ensures that output qualityāspecifically thickness and humidity of the ground materialāis maintained or enhanced during autonomous optimization, preventing off-spec production.
Specific consumption
Savings
Productivity
Fineness improvement
success study
Solutions applied to Molins
Consistent product quality
Optimize production with OptibatĀ®. Leverage real-time data to predict quality outcomes, reduce variability, and ensure product consistency while boosting efficiency and profitability.
Lower COā emissions and measurable sustainability impact
Advanced emissions management by OptibatĀ®. Use AI models to monitor energy and process conditions in real-time, automatically applying optimal strategies to reduce emissions without sacrificing quality or safety.
Maximized throughput with lower energy use
Maximize yield with OptibatĀ®. Continuously analyze process data to anticipate disturbances and push assets to their maximum sustainable limits while maintaining stable, continuous operations.
Improve energy efficiency
Reduce energy consumption with OptibatĀ®. Implement Real-Time Optimization to identify invisible inefficiencies and maximize energy efficiency in your industrial operations without compromising quality.
success study
How it was carried out
PHASE 1
System Integration
OptibatĀ® was seamlessly connected to the plant's existing control system (DCS), allowing for real-time data acquisition and set-point communication.
PHASE 2
Dynamic Set-point Optimization
In collaboration with plant engineers, three critical operating variables were selected for real-time adjustment:
- Exhauster fan power.
- Mill differential pressure.
- Grinding roller pressure.
PHASE 3
Transition to "Automatic Pilot"
After an initial period of providing recommendations to operators (Open Loop), the system was transitioned to Closed Loop control. In this mode, OptibatĀ® autonomously adjusted the set-points every few minutes to maintain the lowest specific energy consumption (kWh/t) while staying within strict quality and stability constraints.
PHASE 4
Continuous Monitoring
The system provided transparent reporting on savings and performance, ensuring that productivity stayed at its peak without human intervention.
Reviews del cliente
Mason Mitchell expressed his gratitude, stating that the team's innovative approach not only brought his vision to life but also enhanced the functionality of each space, making everyday living a delightful experience. Their commitment to excellence and customer satisfaction truly sets them apart in the realm of interior design.
Detailed Review
Design Execution
Project Planning
Budget Management
Implementation
Professionalism
We found it incredibly satisfying to discover how we could optimize our manufacturing processes by applying Optibat's analysis-based proposals. After reviewing the predictions, we drew up a plan and executed it in just a few months.
Mason Mitchell
TITAN US-MIAMI COO
