Automated Warehouses and Logistics Platforms: How to Avoid Inefficiencies and Improve Performance

The Limits of Traditional Design

As variability, demand peaks, and operational constraints increase, issues often underestimated during the design phase begin to emerge:

• bottlenecks that appear after go-live

• incorrect sizing of resources, equipment, and automated systems

• automation systems performing below expectations

• operating costs (OPEX) based on assumptions rather than real data

These factors highlight a key point in the design of automated warehouses and logistics systems:
it is not enough to define an efficient layout — it is necessary to understand the system’s real behavior.

Process & Logistics Engineering: An Integrated Approach

Process & logistics engineering enables structured analysis and optimization of logistics systems by integrating:

• real process and logistics data

• end-to-end mapping of physical and information flows

• dynamic simulation of automated warehouses, lines, and resources

• application of LEAN methodologies

• industrial, logistics, and economic KPIs

This approach transforms design from a theoretical exercise into a data-driven decision-making process.

Logistics Simulation: A Key Tool

Logistics simulation is one of the most effective tools for evaluating alternative scenarios and supporting strategic decisions. Through dynamic models, it is possible to analyze:

• actual capacity vs theoretical capacity

• alternative layout configurations

• stock levels and work-in-progress (WIP)

• shift organization and workforce planning

• sizing of equipment and handling systems

• impact on CAPEX and OPEX

Simulate first, decide later: this principle reduces design risk and improves decision quality.

Scalability and Flexibility of Logistics Systems

An automated warehouse should not be designed only for current needs, but also for future evolution.

It is essential to assess the system’s ability to adapt to:

• volume increases

• growth in the number of SKUs (product variants)

• changes in product mix

• introduction of new levels of automation

• layout expansions and capacity increases

Without this vision, the risk is building systems that are efficient in the short term but rigid and costly to modify over time.

CASE 1 – Greenfield Project: Food Logistics Platform, Inalca Middle East

An integrated food logistics platform developed in the Kizad area, Abu Dhabi (which we worked on), represents a concrete example of advanced intralogistics and food supply chain design.

The project involved the development of a food logistics and processing platform across a total area of 249,000 sqm, with a main logistics building of 41,000 sqm and a storage capacity of over 32,000 pallets, divided into frozen, fresh, and dry areas.

Design Challenges in Multi-Temperature Logistics

The complexity of the logistics system was linked to the need to integrate within a single operational flow:

• multi-temperature storage (frozen, fresh, dry)

• repacking activities

• high inbound and outbound flows (over 30 truck bays)

• management of high volumes with mixed distribution logic (wholesale and last-mile)

The main risk was the creation of bottlenecks between operational areas and suboptimal resource sizing.

Approach: Logistics Simulation and Flow Integration

To ensure platform efficiency, a model based on dynamic logistics flow simulation was developed with the goal of:

• balancing storage capacity and material handling flows

• optimizing the number and configuration of inbound/outbound bays

• properly managing the mix of frozen, fresh, and dry products

• integrating repacking activities into operational flows

Key Insight

The analysis showed that in large-scale platforms, performance does not depend on individual areas, but on the balance between:

• pallet capacity

• dock management

• product mix

• internal handling equipment

Result

The integrated approach enabled the definition of a scalable logistics model, capable of ensuring operational continuity and supporting high volumes in a highly complex environment.

CASE 2 – Brownfield Project: Agri-Food Logistics Platform, North-East Italy

An agri-food logistics center in North-East Italy, subject to refurbishment and modernization, represents a concrete example of transforming an existing platform with a focus on operational efficiency and energy sustainability.

The facility, with a total surface area of 150,000 sqm and a logistics capacity of approximately 100,000 tons/year, was no longer suitable for new volumes and industry requirements.

Key Challenges: Logistics, Cold Chain, and Energy

The main design challenges included:

• reorganization of logistics processes

• expansion of temperature-controlled areas

• improvement of energy performance

• overcoming structural limitations of the existing layout

The risk was intervening only on infrastructure without solving systemic inefficiencies.

Integrated Approach: Simulation, BIM, and Multidisciplinary Engineering

The project was developed through an integrated approach combining:

• logistics simulation for flow validation

• BIM-based design

• project management and construction supervision

• energy and plant engineering

Key Insight

The analysis highlighted a crucial element: in an agri-food platform of this scale, performance depends not only on available space, but on the balance between:

• logistics flows

• refrigeration capacity

• space organization

• energy performance

Main Interventions

• expansion of cold storage areas

• introduction of an automated warehouse

• construction of a new technical plant center

• implementation of photovoltaic systems (5 MW)

• electrification of internal and external logistics

Result

The project transformed the site into a more efficient, sustainable, and scalable logistics platform, improving competitiveness and responsiveness to demand.

• Efficiency: +23% through better use of space and material flow

• Energy consumption: -20% thanks to plant renewal, centralization, and photovoltaics

Conclusions

In advanced logistics systems — particularly integrated platforms and food logistics platforms — process, storage, and material handling are strongly interconnected. Evaluating them separately leads to inefficiencies and suboptimal decisions.

The real difference lies not only in design, but in the ability to make decisions based on data, simulations, and real scenarios.

The difference is not designing better.

It is deciding better.