AMCS technologies and Acreos develop simulator to improve crane operator training

The SIM 61 simulator allows selection of locations and sizes of job sites, cranes, and buildings

Training, Simulator, Amcs, Crane, Acreos

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French companies AMCS technologies and Acreos have partnered to develop a crane simulator called the SIM 61. The simulator allows creating a virtual job site by reproducing a 3D environment as close as possible to the real work environment and weather conditions, including the wind speed. It also allows to choose job site locations such as cities, deserts, and shipyards, job site sizes, types and sizes of machines such as tower cranes, luffing cranes, and mobile cranes, types and sizes of buildings including number of floors, and modify all the crane data such as jib length, load, and speed.

The SIM 61 simulator is activated by installing software on a computer connected via a wired connection (CAN communication network) to AMCS’ anti-collision devices DCS 60 or DCS 61-S. It simulates sensor data similar to actual slewing, trolley and travelling sensors installed on real cranes.


The goals of this partnership for AMCS technologies, which specialises in design and manufacturing of zoning and anti-collision systems for lifting equipment, will be to validate the systems of AMCS technologies, accelerate the development of their functionalities, guarantee their reliability, particularly on complex projects, as well as train future technicians of AMCS’s anti-collision systems.

For Acreos, which specialises in design and manufacturing of simulators to train operators of lifting equipment, the partnership will help improve its crane training solutions; for example, by sensitizing crane operators to anti-collision systems as soon as they are trained and expanding the scope of training for future crane operators. When Acreos’s students progress from simulators to training on real machines, Acreos will use the DCS 61-S system installed on a crane to collect data in real time with its data logger function. The trainer could then analyse the data to understand the strengths and progress of future operators. According to the profile of each student and information collected, it will be possible to adapt the training to each person to improve his or her precision work.

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