# The factors affecting the performance of the tunnel wall drilling task and their priority

## TL;DR

This study identifies key factors affecting tunnel wall drilling performance and prioritizes improvements based on their impact and dissatisfaction levels.

## Contribution

A novel approach combining factor analysis and structural equation modeling to prioritize man–machine environmental factors affecting tunnel drilling performance.

## Key findings

- Tools have the greatest impact on tunnel wall drilling task performance.
- Convenient functional maintenance and improved working environment quality are critical for performance improvement.
- Human factors have the least influence on task performance compared to tools and environment.

## Abstract

Clarifying the relationship between the man–machine environment and its impact on the tunnel wall drilling task performance (TWDTP) is crucial for enhancing the task performance. Based on a questionnaire survey, indicators of the man–machine environment that affect the TWDTP were proposed in this study, and exploratory factor analysis and a structural equation model were employed to examine the potential factors influencing the task performance and their degrees of influence. By comparing the discrepancy between the perceived performance and importance, the satisfaction of potential factors was evaluated, and the priority order for optimizing these factors was determined by considering the degree of influence and dissatisfaction. The results of survey data analysis based on actual tunnel drilling operation scenarios indicated that tools had the greatest impact on the TWDTP, followed by the quality of the physical environment, while human factors had the least influence on the task performance. Convenient functional maintenance is the key to improving the TWDTP, along with enhancing the quality of the working environment. Once these main aspects are optimized, it is important to consider additional factors such as availability of spare tools, efficient personnel organization, man–tool matching, and safety and health assurance. This research approach provides significant guidance in understanding the relationships between the man–machine environmental factors affecting the performance of complex engineering tasks and identifying key influencing factors, thus providing essential insights for optimizing the TWDTP.