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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.

Restricted Areas: How to control access for transporters (Part 6)


Restricted Areas: How to control access for transporters (Part 6)

A key part of the AnyLogic 8.6 update related to the Material Handling Library. Now the movement of transporters such as AGV can be restricted by area and access can be permitted conditionally: by transporter number, by schedule, by throughput, and more.

This technical blog guides you through how to use these restricted areas and demonstrates them with the help of a practical example model: Areas with Limited Access for Transporters.

Webinar: Fundamentals of the AnyLogic Material Handling Library


Webinar: Fundamentals of the AnyLogic Material Handling Library

Learn how to model multi-level environments and how to simulate automated guided vehicles and cranes in this webinar video recording with supporting materials.

Using four example models, our in-house simulation expert and head of training in North America, Dr. Arash Mahdavi, introduces the fundamentals of the AnyLogic Material Handling Library. Understand the possibilities the library presents and see how to get started.

Material Handling Library Tutorial: AGV, Cranes, and Conveyors


Material Handling Library Tutorial: AGV, Cranes, and Conveyors

AnyLogic Help has a new tutorial: Lead Acid Battery Production (Material Handling). By following the tutorial, you can learn how to model material handling processes using AnyLogic’s specialized Material Handling Library. The tutorial explains step-by-step how to create a model of a lead-acid battery production line. The model includes path-guided and free-space automatic guided vehicles (AGV), conveyors, and cranes. Check it out!

An industrial problem resolved by AI and simulation


An industrial problem resolved by AI and simulation

A short blog presenting an industrial problem and its reinforcement learning solution, made using AnyLogic and developed by EII. The flexibility and customizability of AnyLogic allowed the use of RL4J to create a hybrid platform.

Read on, find out about the problem and see how to train learning agents by letting them interact with an AnyLogic environment. You will also learn the techniques used to formulate the industrial problem in a way fit for machine learning.