What is a digital twin? What are its benefits? Is it applicable to my business? If these are the questions you're asking, you've come to the right blog post.
Learn about digital twins in business, how they are combined with simulation, and check out the on-topic case studies from various industries.
Simulation plays an important role in project management as it allows you to predict possible risks and reduce the impact of incorrect decisions on project implementation. In this blogpost, we will look at how different modeling methods could be applied to the problem of software development project management, but then focus on the agent-based approach and its advantages.
As gas and electricity prices surge, people and businesses are now spending a record amount of their income on energy. In this blog post we will show how simulation helps analyze the effects of using renewable energy sources, decentralized energy management, and changing social behavior on energy consumption.
Production scheduling is the process of maximizing the efficiency of production through the detailed planning of manufacturing operations in the short-term. In this blog post, we will illustrate how exactly this has been done using real-world examples from different industries.
Risk management is the process of identifying, assessing, and controlling risks for a business. These risks could stem from a wide variety of sources and if an unforeseen event blindsides your business, it could sustain a financial loss. Simulation is a tool that helps identify potential risks and find ways to make your business resilient.
The world’s leading automotive manufacturers use simulation modeling to optimize production line processes, improve scheduling, create forecasts, and integrate new technologies. Using simulation modeling helps them stay at the forefront of innovation and avoid costly mistakes.
Here are five case studies that highlight the different areas automotive manufacturers apply AnyLogic’s multi-method simulation modeling.
Monte Carlo simulation is a mathematical technique that provides accurate estimates when working with uncertainties. It uses randomness to obtain meaningful information and is effective for calculating business risks and predicting failures such as cost or scheduling overruns.
AnyLogic enables Monte Carlo simulation for highly complex systems. With multimethod modeling simulated systems can be complex, dynamic, and non-linear. The results from these simulation models can come from parallel processing and cloud computing and made available in a variety of ways, including via API and custom UI. Learn more...
ITC Infotech undertook work to optimize inventory keeping in complex asset intensive industries. By combining simulation, machine learning, and optimization, they demonstrated effective asset management and inventory optimization for rotable/repairable spares that balances service levels and inventory costs.
See how Kumar Sumit and his team at ITC Infotech used OptQuest optimization, Python, decision tree machine learning, and AnyLogic for repairables asset management optimization.
Imagine that you need to create a computer program. To do this, you have to hire developers, designers and testers, organize processes, draw up a development plan, constantly evaluate the performance of colleagues, and so on. The task quickly becomes complex. What are your chances of success if you are not a professional?
Here, the downloadable book chapter explores how to use simulation in project management. It gives practical examples from a logistics service provider and a construction company to support its ideas and the demo models from the chapter are open access, so that you can download them, disassemble, and consolidate your knowledge in practice.
