A digital twin for a "tailor-made" storage system

In dynamic simulation, a virtual model is created to test all the variables of a logistics system, preventing critical issues and identifying the best solution for the customer

A digital twin for a truly “tailor-made” automatic storage system. Technological development currently offers many opportunities to companies that want to automate their logistics system. Among these, dynamic simulation makes it possible to design the best possible storage system based on the characteristics and needs of the customer. By creating a “virtual storage system”, the Ferretto tests the performance of the system taking into account all the factors involved, resolving any and all critical issues ahead of time and evaluating the most suitable solutions: from the incoming/outgoing flows to the hourly flows, from the picking stations to the handling speed. This is also how high-performance automatic storage systems are created, with a design process that makes the creation of prototypes unnecessary and translates into significant time and cost savings.

What is Dynamic Simulation?

Dynamic simulation is a technique based on the use of sophisticated state-of-the-art software, such as FlexSim. These tools create a simplified representation of a logistics system with the aim of improving the ability to understand, predict and control its behavior. In practice, with this software, the experts of Ferretto create a model – a digital twin – that replicates the organization, characteristics and operating methods of the automatic storage system to be built, not generically, but based exactly on the expected operating conditions. Simulation is thus especially useful in the planning of new systems and even entire plants.

A DIGITAL TWIN FOR MAXIMUM EFFICIENCY

Simulation becomes a tool that enables designers to meet the specific needs of any individual company. Starting from the project-specific variables – type of storage system, handling systems, peripherals, picking stations – we create a 3D model of the system with all its components and, with the help of flow diagrams, we start simulations to analyze hourly flows, system behavior, picking/placing time, material handling operations. Every single phase is tested, which makes it possible to use the collected data to evaluate whether the operating logic responds to the customer’s needs, whether (and where) there are critical issues, and whether the system can be further optimized.

Some of the parameters that can be tested are:

number of incoming/outgoing flows from the storage facility or to the shipment platforms;
number and type of resources to be used for material handling operations;
time needed for picking/placing operations;
kinematic performance of, for example, shuttles and stacker cranes under all expected conditions of use.

Some examples of application include:

analysis of system efficiency as the position of the resources used changes;
reduction of stand-by times or queue size;
minimization of the negative effects resulting from failures;
batch optimization and part sequencing;
analysis of the effect of tooling times and tool changes;
definition of priorities and shipping logics for goods and services.

DIGITAL SIMULATION, MANY PRACTICAL ADVANTAGES

The main advantage of the use of simulation for automatic material handling systems is the ability to verify the design expectations and optimize the main parameters, thereby supporting companies from the design phase with an additional tool to increase analysis effectiveness and make better strategic decisions.

These are the main benefits of simulation:

possibility to test and validate designs and analyze the performance of entire storage facilities that operate according to different variables and complex operating logics;
emulation of the entire operating cycle in a virtual environment: storage systems, buffer areas, conveyor belts, AGVs and even operators can be quickly added, removed, or adapted to the model, enabling the quick identification of the optimal operating conditions and the maximization of the overall efficiency;
definition of the conditions that maximize the overall efficiency of the systems and of the entire plant. Through the balancing of flows, the optimization of sorting policies, and the proper definition of transfer and storage elements, it is possible to optimize conveyor systems, AGV operations and even manual handling activities;
experimentation with alternative layout policies and different storage criteria to improve system performance;
possibility to carry out dynamic simulations and display the results in a risk-free virtual environment, testing possible scenarios of interest in order to highlight system criticalities and variables;
evaluation of factors such as time, variability and complex relationships in order to make better decisions in system optimization before any implementation in real life, which results in time and cost savings.

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