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How leading automotive producers improve with simulation


How leading automotive producers improve with simulation

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 in business


Monte Carlo simulation in business

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...

Asset management optimization for repairable spare parts


Asset management optimization for repairable spare parts

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.

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