4. Selection of the most optimal tuning pattern of rigid dump trucks for each site

There are various haul road patterns at mine sites including slippery, twisted and uphill roads, and 'ConSite® Mine' offers a function to tune certain parameters such as the engine rotating speed and the accelerator responsiveness of dump trucks to reduce fuel consumption. Up to now, service mechanics had to sequentially try various settings of each parameter to set an optimal tuning, which took a long period of time. With 'ConSite® Mine,' since traveling data of a rigid dump truck is automatically collected and the effects of each parameter on fuel consumption and traveling performance are automatically analyzed, the most optimal tuning can be determined in a short period of time. We will further strive to develop a function to auto-propose the most optimal parameter settings and one to auto-judge each parameter.

5. Application of ConSite® OIL

ConSite® OIL, which has a high reputation for medium- and small-sized construction equipment, will be applied to ultra-large hydraulic excavators. By utilizing sensors which monitor the excavator's hydraulic and other oils, the condition of these oils and associated components can be evaluated. Since maintenance, inspection and replacement of parts can be implemented according to conditions of the parts and components, the excavators are kept in a good working condition, which contributes to stable operation of mines.

6. Recording chronologically of mining equipment operation data in the cloud

Equipment operations data and operators' operational patterns can be recorded in the cloud. This data can be used by the customer's maintenance personnel and the Hitachi Construction Machinery dealers to investigate the cause of the incident over time, and can also be used to train the operators to reduce the risk of the incident and improve safety.

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HCM - Hitachi Construction Machinery Co. Ltd. published this content on 30 September 2020 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 30 September 2020 02:09:01 UTC