Project description

The Liebherr family-owned company is one of the world's largest manufacturers of construction machinery. The Mining division supplies the international mining industry with large machines for the mining of raw materials in opencast mining. These activities are coordinated by the division's parent company Liebherr-Mining Equipment SAS in Colmar (France). In order to take full advantage of the performance of an excavator, M&M, together with Liebherr, developed a state-of-the-art system to support the user and thus improve the performance of the machine. The assistance system displays all current machine and performance data. For example, intelligent sensors and targeted evaluation support the machine operators of the mining excavator when loading the dump trucks. The operator has the option of selecting the type of dump truck to be loaded via a touch panel and immediately receives information on its maximum loading capacity.
With the beginning of the loading process, the system determines the load of the excavator shovel (bucket) on the one hand and at the same time displays the remaining load volumes in the truck. The system also records and displays whether the full load percentage of the bucket has been reached or whether the capacity has fallen below the specified level. This analysis optimizes loading processes, saves energy and reduces costs per ton of material to a minimum.
The assistance system records all error messages in a database. In case of maintenance they can quickly be read out by the responsible service technician. Extensive troubleshooting is kept to a minimum, downtimes are reduced significantly, and the maximum operating time is thus increased by a significant margin.

 

End customer benefits

  • Direct access to machine and performance data, thus increasing operating time and energy savings
  • The work of machine operators is assisted and more efficient

Over view

Branch(s): Heavy equipment

Customer: Liebherr-Mining Equipment Colmar SAS

Development process: Agil

 

Applied technologies

HTML5; CSS; TypeScript; Angular; Ionic; Electron; SQL; MQTT; Socket.io; Node.js

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