+10% shipping capacity and +50% estimated ROI: Logistics capacity planning for a major beverage company

A major company in the beverage industry sought to understand how to expand the capacity of its logistics processes to support production growth while ensuring greater efficiency, predictability, and better utilization of existing resources. The analyzed system was highly complex, integrating nine production lines with a distribution center responsible for receiving, storage, picking, internal movements, and shipping flows.

The growth in handled volumes was increasing pressure on storage and shipping, while different activities, such as inbound, transfers, and distribution, simultaneously competed for the same resources. Variability in the product mix, inventory dispersion, and rules governing the use of storage structures added further complexity to the system.

Although the facility demonstrated the capacity to reach high volumes on certain days, these results could not be sustained consistently. Historical data indicated a typical capacity of approximately 22 to 31 trucks per day, while higher peaks had already been observed.

The challenge, therefore, was not simply to determine the maximum possible volume, but to understand what capacity could be sustained under normal conditions, which factors were effectively limiting performance, and which changes could prepare the logistics system for future growth.

The Challenge

Logistics capacity was the result of the simultaneous interaction between different processes, resources, and constraints. Production, receiving, storage, and shipping shared equipment and areas, meaning that changes in one process had a direct impact on the others. The main challenges identified included:

• Production growth without an equivalent expansion in logistics capacity;
• High daily performance variability;
• Increasing queues, waiting times, and internal movements;
• Competition for resources between inbound, transfers, and distribution;
• Dispersion of SKUs and batches across inventory;
• Honeycombing effect and loss of effective storage capacity;
• Complexity generated by the SKU mix within loads;
• Resource utilization and sizing;
• Difficulty sustaining high transfer volumes consistently.

Given this scenario, it was necessary to evaluate the system as a whole, avoiding decisions based on the isolated analysis of equipment, areas, or processes.

Solution

EYF developed a Digital Model of the logistics system using FlexSim to provide an integrated representation of the main logistics processes and evaluate different alternatives before any intervention in the real environment. The model incorporated historical production, inbound, and outbound data, as well as storage rules, initial inventory, vehicle characteristics, operator and equipment availability, work shifts, and planned and unplanned downtime.

The representation covered the flow from the output of the nine production lines through storage and shipping, including receiving, internal movements, picking, pallet relocation, transfer loading, and route loading.

With the Digital Model, different hypotheses could be evaluated in a controlled virtual environment, making it possible to understand not only the individual impact of each change but also its effects on the entire system. The analyses were structured around four main dimensions:

• Layout and storage strategy: Evaluation of different physical configurations and rules for the use of storage locations;
• Process variability: Analysis of the impact of the number of SKUs per vehicle on shipping capacity;
• Resource availability: Evaluation of different operator and forklift staffing levels;
• Capacity expansion: Exploration of alternatives to support higher production and transfer volumes.

To further analyze storage, EYF also used OptLayout, a layout optimization solution that considers the actual dimensions of the facility, the location of production lines and docks, and storage constraints associated with different products.

The combination of FlexSim and OptLayout made it possible to develop and evaluate alternative layout configurations, occupancy rules, resource availability, and process strategies before implementation.

Impact

The project demonstrated that the capacity of the logistics system was not constrained by a single physical bottleneck.

Performance resulted from the interaction between resources, storage, load composition, and shared logistics flows, making an integrated system-level assessment essential.

The analyses made it possible to distinguish initiatives with limited impact from alternatives capable of generating more significant capacity gains.

The opportunities identified included revising load-building strategies to reduce SKU mix complexity, rebalancing resources between receiving and shipping, appropriately sizing headcount by shift, and utilizing storage structures according to process criticality.

For storage, the combination of layout optimization and revised occupancy rules demonstrated the potential to improve the utilization of existing locations and reduce inefficiencies caused by inventory dispersion and the honeycombing effect.

For longer-term growth, the study also enabled the evaluation of structural alternatives, including dedicated picking flows, distribution center expansion, and greater integration of inventory information.

Rather than simply establishing a theoretical maximum capacity, the project provided a clear understanding of the conditions required to sustain different levels of production and shipping.

With the Digital Model developed by EYF, supported by FlexSim and OptLayout, different decisions could be evaluated virtually before implementation, reducing uncertainty and creating a quantitative foundation for prioritizing improvements and investments.