Masonry is a highly physical occupation with a low retention rate in the workforce beyond 5 years. Predominantly, workers leave the workforce because of injuries. In particular, musculoskeletal disorders are depleting the construction workforce. Previous studies have contrasted the safety records of journeymen versus novices. However, no study to date has examined the combined effects of experience level on safety, productivity, and the balance between them. The purpose of this study is to fill this gap and to investigate the underlying reasons for these effects. Twenty-one masons distributed in four experience levels were recruited to build a 72-block six-course wall using standard concrete masonry units. Participants’ body kinematics were tracked using inertial measurement units and video cameras simultaneously. Biomechanical analysis was carried out to examine the loads experienced by major body joints during bricklaying. Results indicate that journeymen with more than 5 years of experience as well as novice masons work in ergonomically safer ways than apprentices with 1 and 3 years of experience. It was found that apprentices gain proficiency and increase productivity at the cost of higher risk of musculoskeletal injury. The results indicate that those masons who gain experience in ergonomic safety and productivity in tandem are more likely to remain in the workforce beyond the 5-year mark. Thus, it is essential to alter apprentice training to guarantee this outcome.

Masons regularly perform physically strenuous and demanding duties that may exceed a safe limit. Such activities can contribute to an early retirement for masons, resulting in a shortage of skilled craft workers. Previous ergonomic studies have observed that workers develop safer and more productive work techniques as they gain experience. This study aims to analyze relationships between body loads, experience, and work methods. Specifically, we expanded a previous pilot study by increasing the number of participants from 21 masons to 66 masons. Participants completed a prebuilt standard concrete masonry unit (CMU) lead wall using 45 CMUs. Motion capture suits were used to capture masons’ motions, and a combined biomechanical-productivity analysis was carried out to determine the loads experienced by major body joints. Exploiting the larger dataset, this study assessed how different experience groups load their joints and adjust their work techniques as the work height changes. The results suggested that experienced journeymen adopt similar work techniques distinct from those of less experienced workers. Further, training apprentices to adopt these work methods can help reduce occupational injuries and improve productivity. The results show that the journeymen with more than 20 years of experience adopt safer and more productive work techniques distinct from those of less experienced workers. The present study contributes to the body of knowledge on masons’ safety and productivity by providing an in-depth understanding of the linkage between body loads, work experience, techniques, and productivity. Additionally, the findings in this study are expected to have a greater impact when they are adopted to apprentice-training methods and applied to other high musculoskeletal-disorders-risk trades.

Summary: Due to physically demanding tasks in construction, workers are exposed to significant safety and health risks. Measuring and evaluating body kinematics while performing tasks helps to identify the fundamental causes of excessive physical demands, enabling practitioners to implement appropriate interventions to reduce them. Recently, non-invasive or minimally invasive motion capture approaches such as vision-based motion capture systems and angular measurement sensors have emerged, which can be used for in-field kinematics measurements, minimally interfering with on-going work. Given that these approaches have pros and cons for kinematic measurement due to adopted sensors and algorithms, an in-depth understanding of the performance of each approach will support better decisions for their adoption in construction. With this background, the authors evaluate the performance of vision-based (RGB-D sensor-, stereovision camera-, and multiple camera-based) and an angular measurement sensor-based (i.e., an optical encoder) approach to measure body angles through experimental testing. Specifically, measured body angles from these approaches were compared with the ones obtained from a marker-based motion capture system that has less than 0.1 mm of errors. The results showed that vision-based approaches have about 5–10 degrees of error in body angles, while an angular measurement sensor-based approach measured body angles with about 3 degrees of error during diverse tasks. The results indicate that, in general, these approaches can be applicable for diverse ergonomic methods to identify potential safety and health risks, such as rough postural assessment, time and motion study or trajectory analysis where some errors in motion data would not significantly sacrifice their reliability. Combined with relatively accurate angular measurement sensors, vision-based motion capture approaches also have great potential to enable us to perform in-depth physical demand analysis such as biomechanical analysis that requires full-body motion data, even though further improvement of accuracy is necessary. Additionally, understanding of body kinematics of workers would enable ergonomic mechanical design for automated machines and assistive robots that helps to reduce physical demands while supporting workers' capabilities.

I.A.A.R.C. - International Association for Automation and Robotics in Construction Civil Engineering

I.A.A.R.C. - International Association for Automation and Robotics in Construction Civil Engineering