![]() ![]() For example, simulation runs for all 40 fleet sizes can be run simultaneously. This computing capability allowed for rapid parameter variation and multiple scenario testing. The AnyLogic Cloud platform is a scalable computing environment that allows parallel run execution. And, with each run taking two hours to compute nine hours of simulation, a solution that could speed up the process was welcome. In this case, 40 different fleet sizes were tested against different assignment methods. Each assignment method needed testing with parameter variations and in different scenarios. The research results from testing the various methods in an AnyLogic simulation model show that the Jonker-Volgenant-Castanon (JVC) assignment algorithm is superior when assigning tasks to transporters in a vehicle production facility.įaster AMR scenario analysis with cloud-based simulationĪfter creating the simulation model to test different assignment methods, it was necessary to conduct many simulation runs. ![]() The methods tested when designing a task assignment algorithm for autonomous mobile robots (click to enlarge) By contrast, the heuristic methods are based on approximation and may not be as accurate as exact methods, but are usually faster. The exact methods are algorithms that always produce one optimal solution, such as with linear optimization. ![]() In testing, both heuristics and exact methods were analyzed. ![]() Using custom code allowed the testing of any assignment algorithm that might best solve the AMR task allocation problem. While AnyLogic includes a variety of methods for assigning tasks to transporters, it also offers the flexibility of including custom code. Simulation model for testing task allocation algorithms for autonomous mobile robots (click to enlarge). The simulation uses both agent-based and discrete event modeling approaches. AnyLogic simulation software, with its multi-method modeling capabilities and its built-in Material Handling Library, allowed for quick modeling of the workspace, including the addition of automated transporters. To solve the assignment problem, a hybrid simulation model of a vehicle production line facility made it possible to test various methods. Solution: Simulation to test AMR task assignment methods A challenge that can broadly be characterized as the assignment problem. The research aimed to meet the goal of no late tasks with a minimum of transporter driving. The reduction of traffic has several desirable effects, including increased safety, less congestion, and fewer late tasks. In production facilities, the space available for pathways is a limited resource and, as a result, autonomous transporters must share routes with people and other vehicles. For BMW, avoiding production stoppages was the main aim of optimization work related to transporter operations. Late tasks lead to delays that reduce efficiency and increase costs. And secondly, the density of traffic in a production facility should be minimized. Primarily, optimization should result in no late tasks. The optimization of production line transporter operations has two objectives. Problem: How to efficiently assign tasks to an automated fleet As a result, AMR are more flexible in the tasks they can do, and they can be redeployed quickly with only a software update.Ĭompared to AGV, modern AMR technology is seen as being more cost-effective thanks to reduced infrastructure requirements and quicker deployment that does not cause production interruptions. AMR have greater software capabilities and navigate using maps, without the need for guiding wires or strips, so they are not restricted to fixed routes like AGV. In this case study, Tesla Material Flow Engineer and former BMW Group PhD Student and AMR researcher, Maximilian Selmair, describes standard industry practice when deploying large-scale transporter fleets and demonstrates how AnyLogic cloud-based simulation helps develop optimal task allocation algorithms.Īutonomous mobile robots are more capable than automated guided vehicles (AGV) because they are more complex. Automotive industry leaders use autonomous mobile robots (AMR) in their production facilities to improve productivity. ![]()
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