Complexity, Performance, and Search Efficiency: An Eye-Tracking Study on Assembly-Based Tasks among Construction Workers (Pipefitters)
Abstract
:1. Introduction
1.1. Eye-Tracking
1.2. Architecture, Urban Design, and the Built Environment
1.3. Construction Engineering
1.4. Differing Information Formats, Spatial Cognition, and Pipefitter Performance
2. Materials and Methods
2.1. Participants
2.2. Eye-Tracking
2.3. Variables of Interest
3. Results
3.1. Complexity and Pipefitter Interactions (Visit Metrics)
3.1.1. Pipefitter Interaction (Visit Count) by Visual Drawing Complexity (Number of Fittings, Pipes, and References)
3.1.2. Pipefitter Interaction (Average Visit Duration) by Visual Drawing Complexity (Number of Fittings, Pipes, and References)
3.2. Pipefitter Interactions (Visit Metrics) and Search Efficiency
3.3. Search Efficiency and Performance
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Pipefitter | Visit Count | Avg Visit Duration | Rework % | Assembly Time | # of Errors | Avg Convex Hull Coverage |
---|---|---|---|---|---|---|
Pipefitter 1 | 268 | 3.486 | 19.277 | 2490 | 2 | 0.049 |
Pipefitter 2 | 359 | 3.743 | 3.061 | 2917 | 2 | 0.045 |
Pipefitter 3 | 197 | 3.039 | 5.455 | 1634 | 2 | 0.042 |
Pipefitter 4 | 235 | 3.061 | 0 | 1648 | 0 | 0.04 |
Pipefitter 5 | 142 | 3.208 | 5.769 | 1565 | 1 | 0.045 |
Pipefitter 6 | 248 | 2.855 | 10.448 | 2012 | 0 | 0.042 |
Pipefitter 7 | 325 | 3.205 | 13.514 | 2220 | 2 | 0.043 |
Pipefitter 8 | 158 | 4.671 | 7.937 | 1892 | 0 | 0.05 |
Pipefitter 9 | 245 | 2.235 | 10.256 | 2337 | 0 | 0.037 |
Pipefitter 10 | 335 | 2.844 | 17.347 | 2921 | 4 | 0.06 |
Pipefitter 11 | 348 | 4.279 | 12.698 | 4314 | 3 | 0.071 |
Pipefitter 12 | 110 | 2.497 | 2.222 | 1334 | 0 | 0.036 |
Pipefitter 13 | 312 | 4.508 | 9.483 | 3488 | 2 | 0.06 |
Pipefitter 14 | 311 | 3.509 | 14.159 | 3371 | 2 | 0.035 |
Pipefitter 15 | 165 | 4.12 | 3.774 | 1584 | 0 | 0.04 |
Pipefitter 16 | 163 | 3.839 | 13.83 | 2574 | 2 | 0.048 |
Pipefitter 17 | 301 | 2.449 | 1.538 | 1942 | 0 | 0.039 |
Pipefitter 18 | 250 | 4.452 | 8.08 | 2787 | 0 | 0.031 |
Pipefitter 19 | 357 | 3.473 | 13.158 | 3420 | 2 | 0.051 |
Pipefitter 20 | 223 | 2.961 | 5.405 | 2217 | 0 | 0.031 |
Drawing Number | Total Visit Count | Avg Visit Duration | Fitting Count | Pipe Count | Reference Counts |
---|---|---|---|---|---|
1 | 405 | 3.83 | 5 | 9 | 4 |
2 | 573 | 4.78 | 4 | 7 | 4 |
3 | 777 | 3.99 | 5 | 9 | 5 |
4 | 422 | 3.16 | 3 | 5 | 3 |
5 | 528 | 3.16 | 6 | 10 | 5 |
6 | 329 | 2.82 | 2 | 3 | 2 |
7 | 804 | 3.09 | 8 | 12 | 6 |
8 | 563 | 3.46 | 4 | 6 | 3 |
9 | 374 | 2.69 | 3 | 5 | 3 |
10 | 277 | 2.18 | 4 | 5 | 2 |
Appendix B
- Collect eye-tracking data using the SMI Eye Tracking Glasses 2.0;
- Import all eye-tracking data and reference images (assembly drawings) into BeGaze
- In BeGaze, manually map all recorded fixation points to the appropriate locations on the appropriate reference images;
- Export eye-tracking event data from BeGaze as a text file and upload to Visual Eyes;
- Upload all reference images to Visual Eyes and specify the appropriate dimensions of each image;
- Create a comma-separated value file (.CSV) that lists additional metrics for each pipefitter;
- A. age, spatial cognition scores, etc.;
- Upload the comma-separated value file to Visual Eyes
- Specify a minimum fixation duration and maximum off-stimulus fixations value in Visual Eyes and generate visits;
- Export file of visit metrics from Visual Eyes, including visit counts, visit durations, and many other statistics.
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Terminology | Definition |
---|---|
Area of Interest (AOI) | The boundary defining the most important parts of a visual stimulus [8]. In this research, the pipe spool assembly components are the AOI. |
Glance | A quick look at visual stimuli [13]. |
Fixation | A grouping of gaze points that are relatively close to each other (20 to 50 pixels) within a short timeframe (200 to 300 ms) [8]. |
Gaze Point | The point where the eyes are looking at a certain time on a visual stimulus [7]. |
Saccade | The transition from one fixation to another [8]. |
Convex Hull | The area of a visual stimulus that was of interest to the viewer. Convex Hulls focus on the fixation points and saccades of interest to the researcher [14]. |
Visit | The number of times a pipefitter visited an assembly drawing. |
Min | Mean | Max | Std. Dev. | Skewness | Kurtosis | |
---|---|---|---|---|---|---|
Age (years) | 20 | 34.3 | 60 | 11.8 | 0.753 | −0.502 |
Years of Industry Experience | 1 | 11.4 | 39 | 10.6 | 1.301 | 1.163 |
Variables of Interest | Variables | Definition |
---|---|---|
Visual Complexity | Fitting Count | Total number of fittings in an assembly drawing |
Pipe Count | Total number of pipes in an assembly drawing | |
Reference Count | Number of tags in a drawing that refer to a different assembly drawing | |
Pipefitter Interactions (Visit Metrics) | Visit Count | Number of times a pipefitter visited an assembly drawing |
Average Visit Duration | Average time (s) each pipefitter spent per visit to an assembly drawing | |
Search Efficiency | Average Convex Hull Coverage | Polygon encompassing fixation points |
Performance | Assembly Time | Time required to complete pipe spool assembly task |
Number of Errors (# Errors) | Number of errors in the completed pipe spool assembly | |
Rework (%) | Proportion of time that a participant spent disassembling and reassembling components |
Min | Mean | Max | Med | Std. Dev. | Skew | Kurt | |
---|---|---|---|---|---|---|---|
Visit Count Per Pipefitter | 110.00 | 252.60 | 359.00 | 249.00 | 77.61 | −0.25 | −1.13 |
Avg Visit Duration | 2.23 | 3.42 | 4.67 | 3.34 | 0.72 | 0.23 | −0.89 |
Rework % | 0.00 | 8.87 | 19.28 | 8.78 | 5.44 | 0.15 | −0.86 |
Assembly Time | 1334 | 2433 | 4314 | 2278 | 790.6 | 0.70 | −0.01 |
# Errors | 0.00 | 1.20 | 4.00 | 1.50 | 1.24 | 0.50 | −0.67 |
Avg Convex Hull Coverage | 0.031 | 0.045 | 0.071 | 0.042 | 0.01 | 0.99 | 1.06 |
Min | Mean | Max | Med | Std. Dev | Skew | Kurt | |
---|---|---|---|---|---|---|---|
Visit Count Per Drawing | 277.00 | 505.20 | 804.00 | 475.00 | 179.17 | 0.63 | −0.61 |
Avg Visit Duration | 2.18 | 3.32 | 4.78 | 3.16 | 0.74 | 0.60 | 0.61 |
Reference Counts | 2.00 | 3.70 | 6.00 | 3.50 | 1.34 | 0.33 | −0.85 |
Fitting Count | 2.00 | 4.40 | 8.00 | 4.00 | 1.71 | 0.88 | 1.13 |
Pipe Count | 3.00 | 7.10 | 12.00 | 6.50 | 2.81 | 0.36 | −0.77 |
Pearson’s Correlation (r) | p-Value | |
---|---|---|
Fitting Count | 0.717 | 0.020 * |
Pipe Count | 0.760 | 0.011 * |
Reference Count | 0.861 | 0.001 * |
Dep. Variable | Ind. Variable | Constant | Beta | F(1, 8) | R2 | p |
---|---|---|---|---|---|---|
Visit Count | Fitting Count | 175.33 | 74.97 | 8.45 | 0.51 | 0.020 * |
Pipe Count | 160.93 | 48.49 | 10.91 | 0.58 | 0.010 * | |
Reference Count | 115.39 | 78.30 | 22.99 | 0.74 | 0.001 * |
Pearson’s Correlation (r) | p-Value | |
---|---|---|
Fitting Count | 0.153 | 0.673 |
Pipe Count | 0.346 | 0.976 |
Reference Count | 0.446 | 0.196 |
Pearson’s Correlation (r) | p-Value | |
---|---|---|
Visit Count | 0.390 | 0.0891 |
Avg Visit Duration | 0.709 | 0.000 * |
Dep. Variable | Ind. Variable | Constant | Beta | F(1, 18) | R2 | Adj R2 | p |
---|---|---|---|---|---|---|---|
Search Efficiency | Visit Count | 3.17 | 0.01 | 3.34 | 0.16 | 0.11 | 0.084 |
Avg Visit Duration | 2.59 | 0.55 | 3.23 | 0.15 | 0.10 | 0.089 |
Pearson’s Correlation (r) | p-Value | |
---|---|---|
Assembly Time (s) | 0.589 | 0.006 * |
Number of Errors | 0.709 | 0.000 * |
Rework (%) | 0.458 | 0.042 * |
Dep. Variable | Ind. Variable | Constant | Beta | F(1, 18) | R2 | Adj R2 | p |
---|---|---|---|---|---|---|---|
Assembly Time | Search Efficiency | 378.18 | 459.32 | 9.56 | 0.347 | 0.311 | 0.006 * |
# Errors | −2.68 | 0.87 | 18.23 | 0.503 | 0.476 | <0.001 * | |
Rework % | −2.13 | 2.46 | 4.77 | 0.209 | 0.166 | 0.042 * |
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Al-Haddad, S.; Sears, M.; Alruwaythi, O.; Goodrum, P.M. Complexity, Performance, and Search Efficiency: An Eye-Tracking Study on Assembly-Based Tasks among Construction Workers (Pipefitters). Buildings 2022, 12, 2174. https://doi.org/10.3390/buildings12122174
Al-Haddad S, Sears M, Alruwaythi O, Goodrum PM. Complexity, Performance, and Search Efficiency: An Eye-Tracking Study on Assembly-Based Tasks among Construction Workers (Pipefitters). Buildings. 2022; 12(12):2174. https://doi.org/10.3390/buildings12122174
Chicago/Turabian StyleAl-Haddad, Sara, Matthew Sears, Omar Alruwaythi, and Paul M. Goodrum. 2022. "Complexity, Performance, and Search Efficiency: An Eye-Tracking Study on Assembly-Based Tasks among Construction Workers (Pipefitters)" Buildings 12, no. 12: 2174. https://doi.org/10.3390/buildings12122174