Brazil's Leading Ethanol Producer Finds Simulation Offers Fast, Picture-Perfect Analysis of Agricultural Operations

Avoided Unnecessary Purchases

"The model proved to be very adherent to the real dynamics of the operations of CTC's can sugar internal movement in the plant. It also allows you to view points of queuing and resources with high and low occupancy"

  • Mara Veronez
    Information Technology Professional
    Cosan Combustiveis e Lubrificantes S.A.

Simio correctly predicted a method to avoid unnecessary sugar cane transport purchases that saved Cosan over $500,000!

The Company


With over 44.2 million tons of sugarcane processed, 1.7 billion liters of ethanol and 3.3 million tons of sugar produced, Brazilian clean energy manufacturer Cosan has earned its place as world leader in its agricultural manufacturing niche.

Cosan's complex sugar chain supply chain of 18 production plants, two refineries, and two port terminals stretches northwest along the Tiete River in the State of Sao Paulo. This network combines to make Cosan the world's largest exporter of sugar and alcohol and as well as a global leader in the production of sugarcane alcohol. And keeping with the company's belief that "energy is in everything", Cosan is the world's largest generator of sugarcane bagasse – the residual waste from sugar cane production.

The Challenge

Cosan senior management holds the agricultural logistics team responsible for managing the activities of logistics processes in order to meet corporate supply needs of sugar cane for the agricultural area.

Specifically, there is a need to analyze operations for capacity improvement while reducing CAPEX budget requirements, where possible. Three key points following the harvest of sugarcane in a specific location are identified as needing change to meet corporate objectives:

  • Determine optimum number of vehicles required in fleet used to transport sugarcane to processing mills to preserve capital.
  • Propose how to increase the actual capacity of sugarcane received at the sugar mills.
  • Identify the production bottleneck problems to solve in order to improve the flow of sugar cane.

This case highlights the analytical approach taken to preserve CAPEX requirements for fleet vehicles.

The Approach

Cosan chose discrete event simulation to analyze the dynamics of their operations, identify bottlenecks and points for improvement, and assess value scenarios. In order to visualize operations while quickly getting answers to their implementations, they selected Simio®, a new, state of the art, 3D rapid modeling simulation software capability. Over the course of three months, newly hired engineers collected data in the field and received hands-on training and modeling assistance from Paragon Consulting of San Palo.

To model agricultural operations to analyze the sugarcane's post-harvest journey to production mills the model objectives include:

  • Dimension the fleet of road transport sugar cane crop to Unity Costa Pinto;
  • Evaluate the actual capacity of reception of cane sugar mills;
  • Identify bottlenecks and points for improvement in the flow of CCT (Cut-Load-Haul) of cane sugar.
  • Other model parameters uses are:
    • Input Variables: 32
    • Output Variables: 39
    • Auxiliary variables: 92
    • Variables Entities: 8
    • Input tables: 19
  • Simulated days:
    • 240 (1st season)
  • Number of Entities:
    • 12 (10 Harvesters compositional types for transport of sugar cane)

The Results

Bottom Line: The planned 2011 CAPEX requirements are reduced by eleven (11) full cane transport sets.

The value gained by using simulation is that senior management gets a predictive risk analysis. The risk analysis covers a 240-day season factoring in labor variations, unplanned downtime, non-optimal equipment speeds and other uncertainty. The model proved to be very similar to the real dynamics of Cosan's operation for a cane sugar harvest and internal movement in the plant.

"The model proved to be very adherent to the real dynamics of the operations of CTC's cane sugar and internal movement in the plant," said Mara Veronez, Information Technology Professional at Cosan Combustíveis e Lubrificantes S.A. "It also allows you to view points of queuing and resources with high and low occupancy."

The model allows management to view points of queuing and resources with high and low occupancy. In the end then, management receives a fast, picture-perfect future look into proposed courses of action to improve.

Next steps in the overall effort to improve agricultural operations in Cosan's agricultural logistics operations include detailing the frontend process of mechanized harvesting and expansion of the model to other plants of the group. The Cosan team also plans to use the Simio modeling tool for other agricultural operations such as scaling of the truck fleet train.