We use Math Modeling and Data Science to solve real-world problems
Development of Simulation Models and Digital Twins for research + optimization of any processes in Manufacturing, Recycling, Energy, Warehousing & Logistics
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See our worksWhat we do
Our main services
Competencies
We have extensive experience in
Mathematics and Statistics
Math & statistics are two powerful tools that can be used to create and analyze various systems. Mathematical modeling creates a view of the system, while statistics interprets the data and draws conclusions based on them. Combining these two approaches together, we can create complex simulation models for various tasks and industries.
Math & statistics are two powerful tools that can be used to create and…
Smart Factories and Industry 4.0
Smart Factory & Industry 4.0 revolutionize industrial processes through advanced technologies. A smart factory is a data-driven factory that uses digital technologies to improve efficiency, quality, and flexibility. Industry 4.0 integrates IIoT, AI/ML, Big data, Cloud computing, and robotics to create enhancing productivity and flexibility.
Smart Factory & Industry 4.0 revolutionize industrial processes through advanced technologies. A smart factory…
Theory of Constraints (ToC)
ToC is a management philosophy that focuses on identifying and removing constraints (bottlenecks) in a system to improve overall performance. It provides tools such as the Five Focusing Steps and Critical Chain Project Management. ToC improves efficiency, reduces lead times, and increases throughput.
ToC is a management philosophy that focuses on identifying and removing constraints (bottlenecks) in…
Prediction and Forecasting
Predicting & Forecasting are important approachs for businesses to make informed decisions about the future. By analyzing hidata and trends, businesses can make predictions about future demand, sales, financial, and other key metrics; also identify potential risks and make strategic plans.
Predicting & Forecasting are important approachs for businesses to make informed decisions about the…
FinModeling and Risk analysis
Financial modeling is a powerful approach to analyzing financial data and forecasting future performance. By using mathematical models, financial modeling can help to identify and assess potential risks and rewards, which can lead to better decision-making. Risk analysis is an important part of financial modeling, as it helps to ensure that the models are accurate and that the risks are properly managed.
Financial modeling is a powerful approach to analyzing financial data and forecasting future performance….
Troubleshooting and TRIZ
Troubleshooting the process of identifying and resolving problems or issues that occur in various systems, devices, or processes. It involves systematic and logical steps to diagnose and fix problems to restore normal functionality. Troubleshooting is commonly used in technical fields such as information technology, electronics, mechanics, and various industries where equipment.
Troubleshooting the process of identifying and resolving problems or issues that occur in various…
Expertise
We possess extensive knowledge in
Container logistics: process of transporting goods in containers from one location to another.
Mechanized manufacturing: uses machinery to produce goods and services, increasing efficiency, productivity, and quality.
Logistics of supply: the process of planning, transporting, and storing raw materials and components to a manufacturing facility.
Continuous manufacturing: production process in which raw materials are continuously.
Recycling: conversion of waste into new materials, reducing greenhouse gas emissions, energy use, air and water.
Serial production: type of mass production that uses assembly lines to produce distinct items in batches.
Automated production: uses machines and computers to perform production, increasing efficiency, and quality.
Logistics of production: managing materials, semi-finished products, and operations efficiently.
Mechanized warehousing: automates with machines and systems, improving efficiency, accuracy, and reducing costs.
Reverse logistics: movement of goods and materials back from the customer to the manufacturer or retailer.
Mass manufacturing: uses assembly lines to produce large batches of identical products with specialized machines, tools, and division of labor.
Discrete manufacturing: production of distinct items that can be counted, touched, and seen.
Sales logistics: efficient delivery of finished products from the manufacturer to consumers worldwide.
Traditional energy: energy derived from non-renewable resources (fossil fuels – coal, oil, and natural gas).
Recoverable energy: energy that comes from renewable sources (solar, wind, hydroelectric, geothermal, and biomass).
Our workflow
How we work on projects:
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Step 1
Research and Discovery. Gathering requirements, identifying problems, setting goals.
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Step 2
Creating the model. The next step is to create a mathematical or computational model of the system or process.
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Step 3
Validation and verification. Once the model is created, it goes through a verification process to ensure that it accurately represents the real system or process.
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Result
Report with results. The final step is to analyze the results of the simulation and report the findings.
Our benefits
What we can do for you:
Customized Solutions
Our approach involves developing personalized solutions that cater to the unique needs of our clients with the utmost precision.
Knowledge and experience
Our company has a team of skilled and knowledgeable experts with diverse backgrounds, capable of tackling a wide range of tasks.
Cost-Effective
Our clients have been able to save a considerable amount of money in problem-solving through our cutting-edge solutions and consultations.
Software & Tech
We use top tools like: AnyLogic, FlexSim, Simio, Simul8, Matlab
and other programs: Simulink; AnyLogistix; Java; Python (Pandas, NumPy, PyTorch, Keras); MS Power BI, Tableau; Looker, Grafana; KNIME; Apache (Spark, Hadoop, Kafka); Databricks; Pentaho; Alteryx.
Testimonials
What our clients say about us:
Sergiy Kalinchuk
“I’m highly impressed with the quality of service provided by SimexLab. They developed a comprehensive simulation model for my startup, which helped me to identify potential issues and make informed decisions. The team was highly professional and worked closely with me throughout the project to ensure that my requirements were met. Their expertise in simulation modeling and data analytics is unparalleled, and I would highly recommend their services to anyone in need of such services”.
“I’m highly impressed with the quality of service provided by SimexLab. They developed a comprehensive simulation model for my startup, which helped me to identify potential issues and make informed decisions. The team was highly professional and worked closely with me throughout the project to ensure that my requirements were met. Their expertise in simulation modeling and data analytics is unparalleled, and I would highly recommend their services to anyone in need of such services”.
Vitaliy Kryvenko
“I had the pleasure of working with SimexLab on several data science projects, and I must say that their level of expertise and dedication is exceptional. The team at SimexLab has a deep understanding of simulation modeling and data science, and they were able to provide innovative solutions that helped us make informed decisions and improve our business operations. Their professionalism, attention to detail, and commitment to delivering high-quality results exceeded my expectations. I highly recommend SimexLab to anyone looking for reliable and expert partners in the field of simulation modeling and data science.”
“I had the pleasure of working with SimexLab on several data science projects, and I must say that their level of expertise and dedication is exceptional. The team at SimexLab has a deep understanding of simulation modeling and data science, and they were able to provide innovative solutions that helped us make informed decisions and improve our business operations. Their professionalism, attention to detail, and commitment to delivering high-quality results exceeded my expectations. I highly recommend SimexLab to anyone looking for reliable and expert partners in the field of simulation modeling and data science.”
Yaroslav Gordienko
“I have been working with SimexLab for several years now, and I am continuously impressed with their level of expertise and professionalism in the field of simulation modeling and data science. Their team has helped me analyze and optimize various projects, from manufacturing to logistics and transportation, leading to significant cost savings and improved efficiency. SimexLab’s dedication to their clients’ success is unparalleled, and I highly recommend their services to anyone looking to improve their business operations. Their expertise in creating digital twins and modeling complex systems has been instrumental in my investment projects, particularly in the area of colivings and community building”
“I have been working with SimexLab for several years now, and I am continuously impressed with their level of expertise and professionalism in the field of simulation modeling and data science. Their team has helped me analyze and optimize various projects, from manufacturing to logistics and transportation, leading to significant cost savings and improved efficiency. SimexLab’s dedication to their clients’ success is unparalleled, and I highly recommend their services to anyone looking to improve their business operations. Their expertise in creating digital twins and modeling complex systems has been instrumental in my investment projects, particularly in the area of colivings and community building”
News and Articles
A few posts from our blog
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Contact us
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Ihor Ivanisenko (Ph.D., Associate Professor)
Chief Executive Officer (CEO)
Ilia Savchenko
Chief Technology Officer (CTO)
Igor Yeremenko
Business Development Manager (BizDev)
Ihor Ivanisenko (Ph.D., Associate Professor)
Chief Executive Officer (CEO)
Ilia Savchenko
Chief Technology Officer (CTO)
Igor Yeremenko
Business Development Manager (BizDev)
We improve business processes in manufacturing and logistics by using simulation modeling, data engineering, and the Theory of Constraints (TOC). To do this, we use a variety of tools, programs and utilities. One of the biggest challenges facing businesses today is troubleshooting supply chain disruptions. Simulation modeling can be a powerful tool for preventing and mitigating these disruptions. By testing different scenarios and identifying potential problems before they occur, simulation modeling can help businesses to improve their supply chain resilience and protect their bottom line.
We are experts in using simulation modeling to improve supply chains. We have a deep understanding of the challenges that businesses face and the solutions that simulation modeling can provide. We can help you to identify and address the root causes of your supply chain disruptions, and we can help you to develop strategies for preventing them from happening in the future. There are a number of different simulation modeling software packages available, including AnyLogic, FlexSim, Simio, Simul8. These software packages can be used to model a wide variety of supply chain scenarios, including production, transportation, and inventory management. To build simulation models, several basic methods are used with which you can solve problems of any complexity:
- Agent-Based modelings is a type of simulation modeling that allows you to model the behavior of individual agents in a system. This can be used to understand the impact of human behavior on supply chain performance.
- Discrete-Event simulations is a type of simulation modeling that allows you to model the occurrence of events in a system. This can be used to understand the impact of stochastic events, such as demand fluctuations, on supply chain performance.
- System Dynamics is a type of simulation modeling that allows you to model the feedback loops and interactions between different components of a system. This can be used to understand the long-term behavior of a supply chain.
- Monte Carlo simulation is a mathematecal technique that uses randomness to solve deterministic problems. It’s used to estimate the probability of different outcomes & assess risk.
By using a combination of these techniques, we can develop a comprehensive approach to troubleshooting in manufacturing, supply chains, and Industry 4.0. This can help you to improve the resilience and efficiency of your supply chain, and to minimize the impact of disruptions when they do occur.
We improve business processes in manufacturing and logistics by using simulation modeling, data engineering, and the Theory of Constraints (TOC). To do this, we use a variety of tools, programs and utilities. One of the biggest challenges facing businesses today is troubleshooting supply chain disruptions. Simulation modeling can be a powerful tool for preventing and mitigating these disruptions. By testing different scenarios and identifying potential problems before they occur, simulation modeling can help businesses…