Analyzing Factors Affecting Human Productivity in Logging Machinery Operation

Lalit Sharma

Analyzing Factors Affecting Human Productivity in Logging Machinery Operation

Authors: Lalit Sharma

Published: 2025-02-21 13:58:09.237

Abstract

This paper investigates the factors affecting human productivity when operating logging machinery, with a specific focus on the impact of training machines and simulators. It evaluates how these tools influence the results of training and examines the psychophysiological traits that affect the precision of guiding the logging machine both on the horizontal plane and through boom extension. The study presents a novel approach for testing these traits using author-developed methods, which were applied to a group of cadets. The results of the tests are compared with those obtained from final examinations required to complete logging machinery operation training. The findings suggest that the author-developed testing methods provide an effective measure of operator precision and productivity in comparison with traditional evaluation methods. Furthermore, the research highlights the role of simulators in improving training outcomes by enhancing operator skills and reducing errors. The paper concludes that using advanced testing techniques can better assess the psychophysiological factors influencing logging machinery operation and contribute to more efficient training programs. This research will be of particular interest to professionals in human-machine interaction and logging machine training, providing valuable insights into optimizing training processes and improving operator performance in the forestry industry.

Keywords

Logging machinery, Human productivity, Training simulators, Psychophysiological traits, Human-machine interaction, equipment operation, Precision of machine guidance.

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How to Cite

Lalit Sharma, (2025-02-21 13:58:09.237). Analyzing Factors Affecting Human Productivity in Logging Machinery Operation. Abhi International Journal of Applied Engineering, Volume tSY7h55GzzcyRY5B54Uw, Issue 1.

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Abhi International Journal of
Applied Engineering ( AIJAE )