As one of the largest steel manufacturers and suppliers in the world, Tata Steel faced the need to optimize the internal logistics at one of its steel manufacturing units. The company saw potential for increasing the unit’s overall throughput using AnyLogic as production optimization software.
Read on and find out more about the case.
Learn how to create a self-configuring material handling digital twin from this webinar recording with accompanying simulation model. Presented by Dr. Benjamin Schumann in three chapters, the webinar covers how to automatically configure machines and products, conveyors, and automatic guided vehicles (AGV).
Imagine receiving a call from Jeff Bezos — he wants you to simulate a...
AnyLogic experts at business consulting company NFP worked to resolve a crane task distribution problem for a major international metallurgical company. Their innovative solution employed machine learning and improved on an expert selected policy. Read on to learn more about the project.
The simulation model can be found in the cloud and was featured as model of the month December 2019.
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.
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!
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.
How much will profit increase without this bottleneck? Or how about – If we invest in debottlenecking the whole production line, can we meet our targets? Simple questions and a common approach, but the answers may not be what you expect if you were to ask Dr. Alan Barnard, CEO Goldratt Research Labs.
Read on and find out why...
Digital twins are part of Industry 4.0. How are they being used on automobile production lines? Here we investigate how a digital twin is made and used in the automotive industry.
One of the world’s largest capital goods companies, CNHi, wanted to evaluate Industry 4.0 technologies. It chose its IVECO production plant in Suzzara, Italy. Fair Dynamics were contracted and proposed a digital twin. Read on and discover how maintenance costs can be reduced with a digital twin — Production line downtime was shown in a study of over 100 automotive executives to cost an average of $22,000 per minute.
Industry 4.0 was the subject of Yuri Toluyev’s plenary presentation at the IMMOD simulation modeling conference in Saint Petersburg. He described how new approaches to enterprise development, united by the concept of Industry 4.0, are driving technological development.
AnyLogic attended the event and interviewed Toluyev about Industry 4.0, its development, and its implementation. Interesting and informative, read on for Yuri Toluyev’s Industry 4.0 insight...
