Industrial simulation consultancy
Data-driven decisions. Optimized processes. Proven results.
Take your factory to a new level of performance and reliability.
Why simulation?
Discrete event simulation
what it is, benefits and areas of application within the industry.
What is it and benefits
Simulation is the digital imitation of a real-world process or system and is used for optimization or forecasting activities. It enables robust decision-making support without physical investment.
Among the benefits of using simulation, we have:
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Validate solutions without investment.
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Does not affect production.
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Solving non-linear problems.
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Predictive analysis for quotes.
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Data-driven decision making.
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Get greater accuracy in your analysis.
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Complete statistical process control.
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Data visualization.
Areas of Application
Industrial simulation can be applied in a variety of ways, depending on each company's objectives and challenges. The main areas of application include:
1. What-if Scenarios
Evaluation of hypotheses and improvement alternatives without interfering in the real environment.
It allows you to test different layout configurations, production policies, logistics strategies, and setups, identifying which option yields the best results in productivity, cost, and efficiency.
2. Automation Support
Before implementing an automated solution, such as purchasing a robot or automated cell, simulation allows you to verify whether the proposed system will achieve the expected performance and deliver the planned return on investment.
It is an essential tool for reducing risks and ensuring assertive automation decisions.
3. Digital Shadow/Digital Twin
The integration between the simulation model and the real environment creates a digital twin capable of operating with real-time data.
This connection enables continuous process monitoring, performance forecasts, and change impact analysis, bringing the factory floor closer to the digital world.
4. Smart Tools
Within the simulation environment, it is possible to develop customized intelligent tools, using programming and optimization logic.
These tools can automate tasks such as line balancing, setup reduction, production planning, and bottleneck analysis, increasing the efficiency and agility of process engineering.
5. Virtual Reality
Simulation can be combined with virtual reality (VR) headsets, allowing engineers and managers to step inside the virtual model of the factory.
This immersion facilitates the visualization of layouts, workflows, and interactions between equipment, making the validation process more intuitive and collaborative.
6. Optimization and Reinforcement Learning Algorithms
Application of artificial intelligence and optimization algorithms to improve decision-making in complex systems.
Examples include defining the best route for AMRs, optimizing robot decisions to maximize production, and automatically adjusting operating parameters.
These techniques combine simulation and machine learning to create autonomous and adaptive systems capable of continuously seeking the best performance.
Services
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Freelancer in discrete event simulation
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Mapping opportunities for improvement.
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Process mapping and requirements gathering.
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Construction of a simulation model, along with the creation of dashboards and a complete presentation for decision-making.
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Development of optimization algorithms, Smart Tools or Digital Twin.
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Support for debugging and correcting existing models.
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Development and support of custom library for client.
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Trainings
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Introductory course for Simulation Engineer.
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Basic, advanced and programming course in Flexsim.
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Basic, advanced and programming course in Plant Simulation.
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Customized course for target project solution.
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Advanced course focusing on Smart Tools.
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Advanced course focusing on Digital Twin.
For more information, please contact us.
About
I have a degree in Control and Automation Engineering and an MBA in Data Science and Analytics. I've worked with industrial simulation for over six years, developing and optimizing production processes in various sectors, primarily the electronics and automotive industries.
My experience is focused on discrete event simulation, using Siemens Plant Simulation and FlexSim tools to create models that help companies make strategic decisions, reducing costs, improving efficiency and increasing productivity.
Throughout my career, I have had the opportunity to collaborate with major companies such as Flex, Motorola, HP, Denso, Horse, Autoliv, Faurecia, Alstom, among others, leading optimization projects, line balancing, what-if scenario analysis, and the development of optimization and automation algorithms.
I have also completed advanced internal training on the Flexsim and Plant Simulation tools.
I'm a data-driven professional with strong analytical thinking and a focus on results. I'm always seeking to combine engineering, simulation, and data science to transform complex processes into intelligent, measurable solutions.
Contact
Address: Alberto Faria Street 150, Jardim Brasil, Campinas - SP - 13073-014
Email: leandromeirelles@gmail.com
Cell: 55+ (19) 983540033
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