Assessment and prediction of technical condition of dump truck life components using the Shewhart control charts

This article reviews the current methods available for the assessment and prediction of technical condition of dump trucks. The main shortage revealed are the high economic and human resources required for the implementation of these methods. The conclusion is drawn that it is necessary to develop a new approach to the technical condition management for the machine life components. The presented new method of technical condition assessment and prediction for the machine life components, as against the other methods of statistical control, assesses diagnostic parameters using the Shewhart control charts in combination with the conventional prediction of endurance of the machine components. In combination with the means of nondestructive control, the new procedure makes it possible to prepare basic data for making decisions on placement of equipment under repair for different periods of prediction. Implementation of this method of technical condition assessment and prediction in terms of the vital elements of dump trucks can enable prompt decision-making on maintenance and repair of the machines, which unconditionally can enhance operating efficiency of dump trucks.

Keywords: dump trucks, procedure of technical condition assessment of mining machines, technical condition prediction of mining machines, technical condition monitoring, intelligence transport systems, enhanced mining machine use efficiency, resource elements, mining machine diagnostics.

For citation:

Safiullin R. N., Safiullin R. R., Sorokin K. V. Assessment and prediction of technical condition of dump truck life components using the Shewhart control charts. MIAB. Mining Inf. Anal. Bull. 2024;(7):111-124. [In Russ]. DOI: 10.25018/0236_1493_2024_7_0_111.

Acknowledgements:

About authors:

R.N. Safiullin¹, Dr. Sci. (Eng.), Professor, e-mail: safravi@mail.ru, ORCID ID: 0000-0002-8765-6461,
R.R. Safiullin¹, Cand. Sci. (Eng.), Assistant Professor, e-mail: safiyllin@yandex.ru, ORCID ID: 0000-0003-2315-3678,
K.V. Sorokin¹, Graduate Student, e-mail: kiros_00@bk.ru, ORCID ID: 0009-0006-3781-1407,
¹ Empress Catherine II Saint-Petersburg Mining University, 199106, Saint-Petersburg, Russia.

 

For contacts:

R.N. Safiullin, e-mail: safravi@mail.ru.

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