Next Article in Journal
Panic Food Purchasing amid COVID-19 Pandemic: Does the Impact of Perceived Severity, Anxiety and Self-Isolation Really Matter?
Next Article in Special Issue
Evacuation in Buildings Based on BIM: Taking a Fire in a University Library as an Example
Previous Article in Journal
Mediating Effects of Rehabilitation Motivation between Social Support and Health-Related Quality of Life among Patients with Stroke
Previous Article in Special Issue
An Institutional System Proposal for Advanced Occupational Safety and Labor Standards in the Turkish Construction Industry
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Analyzing Construction Workers’ Unsafe Behaviors in Hoisting Operations of Prefabricated Buildings Using HAZOP

1
School of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215000, China
2
Department of Construction Management, East Carolina University, Greenville, NC 27858, USA
3
Hangzhou Yongdu Real Estate Development Ltd., Hangzhou 311400, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(22), 15275; https://doi.org/10.3390/ijerph192215275
Submission received: 4 October 2022 / Revised: 19 October 2022 / Accepted: 27 October 2022 / Published: 18 November 2022
(This article belongs to the Special Issue Occupational Safety and Risks in Construction)

Abstract

:
Along with the increasing number of prefabricated buildings being constructed in China each year, the incident rate of hoisting operations has been continuously rising. In order to improve construction safety in hoisting operations of prefabricated buildings, this paper analyzes the construction workers’ unsafe behaviors using the Hazard and Operability (HAZOP) method. A questionnaire survey and a literature review were first performed to gather information on safety risks and influencing factors during each stage of hoisting operations, and the survey results were statistically analyzed using the SPSS software. Next, HAZOP was applied to identify the deviation and change of the unsafe behaviors as well as their causes, consequences, and countermeasures. Finally, a case study was presented to verify the effectiveness of the countermeasures through a comparison and evaluation method from experimental economics. This paper demonstrates the use of HAZOP to analyze construction workers’ unsafe behaviors in hoisting operations of prefabricated buildings, and effective countermeasures in each stage of hoisting operations are proposed to mitigate unsafe behaviors. This paper therefore provides an innovative method and a theoretical foundation for reducing unsafe behaviors in hoisting operations of prefabricated buildings and serves as a reference for decision-making for hoisting safety policies in prefabricated construction projects.

1. Introduction

The number of prefabricated building projects has been growing rapidly in China under the strong support of recent policies. The Opinions on Promoting Green Development of Urban and Rural Construction press conference in October 2021 revealed that the gross area of new prefabricated construction projects in China reached 740 million square meters in 2021, an increase of 18% compared with 2020, accounting for roughly a quarter of all new construction project types; around two-thirds of the new prefabricated construction projects were concrete structures with a total gross area of 490 million square meters [1]. Along with this growth in prefabricated buildings, the incident rate of hoisting operations has been continuously rising. The Ministry of Housing and Urban-Rural Development of China defines a construction safety incident as an accident that occurs suddenly in the production and operation activities of the on-site construction unit, harming personal safety and health, damaging equipment and facilities, or causing economic losses, resulting in the temporary suspension or permanent termination of the original production and operation activities. The Ministry’s 2021 Housing and Municipal Engineering Production Safety Accidents Report, as shown in Table 1, reveals that 99 safety incidents and 123 deaths occurred during the first quarter of 2021, an increase of 17 incidents (21%) and 22 deaths (22%) compared with the same period of the previous year. Among the fatalities, 54 were falls and 12 were from crane injuries.
Because most of these fatalities occurred in the construction and hoisting stage and have posed a serious threat to the safety of workers, it is of significant importance that construction workers’ unsafe behaviors in hoisting operations of prefabricated buildings are identified and analyzed. To achieve this goal, this study uses the Hazard and Operability (HAZOP) method combined with survey questionnaires, statistical analysis, and field verification through a case study to improve construction safety in the hoisting operations of prefabricated buildings.

2. Literature Review

Safety behavior refers to behavior that will not infringe, endanger, harm, or cause los, and which is affected by personality traits [2], emotion control [3], work–life conflicts [4,5], etc. The unsafe behaviors of employees can cause many injury incidents, especially in the construction industry. At present, research on the unsafe behavior of construction workers mainly focuses on the safety culture at the group level and behavioral safety at the individual level. For example, He [6] discussed the differences between supervisors and workers in the dimensions of safety environment and safety behavior at the group level, while Zhang [7] started from the perspective of the individual level. The paper adopts a psychological method to study how personality traits affect the occurrence of unsafe behaviors of construction workers.
Quantitative analysis methods are widely used in the study of workers’ unsafe behavior. Guo [8] used the skeleton-based real-time identification method, developed by Guo to capture the dynamic movement of workers, to identify unsafe behaviors. Qi [9] revealed the occurrence mechanism of workers’ unsafe behaviors from the perspective of occupational stress through the developed structural equation model. Hung [10] used a deep convolutional neural network to propose a system to identify workers’ dangerous behaviors and classify unsafe behaviors. Qualitative analysis methods have also been used in studying workers’ unsafe behaviors and have focused on areas such as social psychology and modular construction. Khan [11] evaluated fire safety performance according to the characteristics of multi-story garment (RMG) buildings in India, and Zermane [12] used fault tree analysis to assess the risk of high-altitude work in Malaysian buildings. Chih [13] studied the negative impact of psychological contract breach (PCB) on workers’ safety, Guo [14] used an intelligent video surveillance method to carry out an early warning of workers’ illegal behaviors, and Chatzimichailidou [15] studied the safety risk of modular construction in the construction industry. Although these studies have revealed the causes of workers’ unsafe behaviors to a certain extent, they are limited to traditional buildings and rarely involve new trends such as prefabricated buildings.
The research on occupational safety in the field of prefabricated construction mainly focuses on safety-influencing factors and intervention measures. James [16] proposed that the standardized use of mechanical equipment can effectively reduce the occurrence of safety accidents in prefabricated construction. Lee [17] used the AHP method to analyze the weight of the influencing index of safety management in prefabricated construction and evaluated project safety based on it. Francisco [18] put forward a risk assessment theory applicable to the construction site of prefabricated buildings, which concluded that safety accidents due to falling from high altitude and lifting injury accounted for a high proportion and suggested that the causes of accidents in the process of installation and demolition were due to non-compliance with operating procedures and other unsafe behaviors. Fard [19] made statistics on the data of safety accidents of prefabricated buildings in the United States in recent years and concluded that in falls from height, instability of the connection points of prefabricated members was the main factor inducing unsafe behaviors. In a study of intervention measures, Zou [20] focused on the relationship between prefabricated construction personnel and the management system and concluded that the key to safety management for prefabricated construction lies in human management. Xu [21] and Zhang [22] identified and analyzed the unsafe behaviors of construction workers using computer vision and proposed targeted prevention and treatment measures. Chang [23] reduced the construction safety risk level of prefabricated buildings to the maximum extent through a novel dual-objective optimization model. However, most of the above studies focused on the whole process of prefabricated building construction: the analysis was not detailed enough due to the large scope of involvement. In addition, more attention was paid to the hazard factors leading to unsafe behaviors, while less attention was paid to the possible consequences of unsafe behaviors and subsequent preventive measures.
The main research fields for HAZOP analysis are concentrated in petrochemical, thermal, and chemical engineering. Marhavilas [24] used HAZOP–DMRA technology to evaluate the safety of petrochemical industry operations, while Sirima [25] chose fault tree analysis and HAZOP analysis to explore the risks in the steam production process. Patle [26] proposed a holistic method for the safety analysis of the formic acid production process by using the improved HAZOP model. HAZOP analysis is often used in combination with sensitivity analysis and survey questionnaires. Sbaaei [27] used a sequential module simulation method and automated HAZOP study to conduct dynamic modeling. Zhao [28] used the deep learning method to improve the safety assessment process of HAZOP in the chemical production process. Danko [29] and Yang [30] both used survey questionnaires to simulate the “expert brainstorming” segment of HAZOP analysis. Some scholars also applied HAZOP analysis to the field of construction; for example, Niu [31] used HAZOP analysis to identify and manage the unsafe behavior of crane workers, and Wang [32] combined this method with accident analysis to build a knowledge database of construction expert systems.
Although various studies have investigated the unsafe behaviors of construction workers, few have focused on the unsafe behaviors during the construction and hoisting operation of prefabricated buildings. Since the HAZOP analysis method can be utilized to identify the deviation and change of unsafe behaviors as well as their causes, consequences, and countermeasures, it was applied in this study to investigate the unsafe behaviors during hoisting operations of prefabricated buildings. The application of HAZOP provides an innovative method and theoretical foundation for reducing unsafe behaviors in hoisting operations of prefabricated buildings and serves as a reference for decision-making for hoisting safety policies in prefabricated construction projects.

3. Methodology

Based on the findings of the literature review, a survey questionnaire was first developed and administered at selected construction sites of prefabricated buildings to gather respondents’ perceptions of potential safety risks and influencing factors. The collected survey dataset was then statistically analyzed using the SPSS software to ensure its integrity and reliability. Next, the survey results were summarized to identify the safety risks and safety-influencing factors during each stage of hoisting operations. After that, HAZOP was applied to identify the deviation and change of the unsafe behaviors as well as their causes, consequences, and countermeasures. Finally, a case study was presented to verify the effectiveness of the countermeasures through comparison and evaluation method in experimental economics.

3.1. Survey Questionnaire

The survey was administered at a construction site of prefabricated buildings located in the city of Zibo, China to ensure the sample size and representativeness. A total of 300 survey questionnaires were distributed on-site to hoisting workers, of which 263 were recovered (87.7%). After sorting out the incomplete questionnaires, 203 were determined to be valid (67.7%).
The questionnaires are divided into four sections with objective questions in each section, including (1) basic personal information such as gender, age, occupation, etc., (2) workers’ perception of risks during hoisting operations, (3) the most common safety hazards during hoisting operations, and (4) the causes of safety hazards during hoisting operations. The workers’ perception of risks during hoisting operations describes the degree of danger perceived in different phases of hoisting operations. The most common safety hazards during hoisting operations include a list of 33 potential safety hazards concluded from the literature review based on a 5-point Likert scale. The causes of safety hazards include a list of 16 potential factors contributing to the occurrence of safety hazards based on a 5-point Likert scale.

3.2. HAZOP Analysis

Since the HAZOP analysis method can be utilized to identify the deviation and change of unsafe behaviors as well as their causes, consequences, and countermeasures, it was applied in this study to investigate the unsafe behaviors during hoisting operations of prefabricated buildings. The lead words of the HAZOP analysis were first created to define the workers’ behaviors and describe the various conditions that can occur during hoisting operations. Table 2 presents the lead words and their meaning used in the HAZOP analysis, which guide the identification of deviations of safety factors in hoisting operations.

3.3. Case Study

A residential prefabricated building project was selected as the case study for the HAZOP analysis. The case study uses the comparison and evaluation method in experimental economics, which is able to obtain the density relationship between the evaluation results and the probability distribution after applying independent variables, allowing a clearer view of the impact of independent variables on the evaluation results. As a result, the comparison and evaluation method can be used to verify the validity of the hypothesis.

4. Results

4.1. Survey Statistics

The analysis of valid questionnaires showed that male workers accounted for 89.4%, while female workers accounted for 10.6%, indicating a typical male-dominated workforce in the construction industry. Table 3 illustrated the distribution of age and years of work experience of the surveyed construction workers. Construction workers over 50 years old accounted for the largest proportion (37%) of the surveyed population, suggesting a serious aging trend among construction workers in China. While construction workers with 1–3 years of work experience account for the largest proportion, those with over 5 years of work experience account for the smallest proportion, indicating a lack of experienced workers in the field of prefabricated construction and that many workers have transitioned from traditional fields of the construction industry in recent years.
Next, the statistical software package SPSS 26.0 was used to analyze the reliability of the questionnaire survey results, as shown in Table 4. The number of valid observations included in the analysis was 203 (77.2%), and the missing value was 60 (22.8%). The calculation result of Cronbach α coefficient α = 0.986 indicates good reliability of the survey data.

4.2. Safety Risks

The hoisting operations in prefabricated buildings were divided into six phases according to the typical prefabricated construction sequence, which include component loading and unloading, stacking, lifting, installation, positioning, and correction. Out of the 33 potential safety hazards concluded from the literature review, 23 were determined to be high-risk safety hazards from the survey results and reliability analysis with a coefficient above the average score of 4.62 based on a 5-point Likert scale. These 23 safety risks are detailed in Table 5 and categorized into each of the six phases of hoisting operations.

4.3. Safety Influencing Factors

After analyzing the survey results, 13 safety factors affecting the hoisting operations of prefabricated buildings were determined to be significant among the 16 potential factors with a coefficient above the average score of 4.58 based on a 5-point Likert scale. In addition, these safety factors were classified into four safety evaluation indicator categories, namely human, material, environmental, and managerial, based on the research findings of Bao [33], Wang [34], and Singh [35]. The influencing factor of each safety factor is identified and summarized in Table 6.

4.4. Unsafe Behaviors

HAZOP analyses were performed for each of the six phases of hoisting operations in prefabricated buildings identified in Table 5 using the selected lead words in Table 2. The results of HAZOP analysis for each phase present the deviation, reasons, consequences, and countermeasures for construction workers’ unsafe behaviors in hoisting operations of prefabricated buildings. Table 7 shows the HAZOP analysis results for the loading and unloading phase, where countermeasures are proposed to strengthen the inspection and maintenance of equipment and improve the safety risk protection skills of hoisting workers.
Table 8 shows the HAZOP analysis results for the stacking phase, where the proposed countermeasures include strengthening regular inspection and maintenance, hanging code warning signs, isolating the stacking site, and implementing the reward and punishment mechanism.
Table 9 presents the HAZOP analysis results for the lifting phase, where the countermeasures are proposed to improve and implement a comprehensive acceptance system for components entering the site, rationally arrange the lifting points of components, pay attention to warnings during lifting operations, and install a torque limiter to prevent the crane from overturning.
Table 10 presents the HAZOP analysis results for the installation phase, where the countermeasures are proposed to carry out special drill activities for construction safety, implement safety protection measures at the operation site (such as safety fences, double hanging points to secure exterior wall scaffold, etc.), verify the construction plan, and assign special personnel for power management.
Table 11 presents the HAZOP analysis results for the positioning phase, where the countermeasures are proposed to emphasize the importance of worker safety and protection, strengthen on-site safety inspection, and check whether the operation meets the operating standards.
Table 12 shows the HAZOP analysis results for the correction phase, where the proposed countermeasures include strengthening on-site inspection and template connection.

4.5. Countermeasures

Based on the HAZOP analysis results, the significant unsafe behaviors in the six phases of hoisting operation in prefabricated buildings can be summarized as follows: (1) in the component loading and unloading phase, it is easy to hurt workers; (2) in the stacking phase, component collapse easily occurs; (3) in the lifting phase, components easily fall or cause injury due to illegal equipment operation; (4) in the installation phase, workers are easily injured by components or due to the lack of safety protection at the operation site; (5) in the positioning phase, collapse of cast-in-place structure easily occurs; (6) in the correction phase, formwork collapse or mold-moving incidents easily occur. Based on these significant unsafe behaviors determined by the HAZOP analyses, the following prevention and control countermeasures are proposed:
  • Countermeasures to prevent workers from being injured in the component loading and unloading phase:
    • Strengthen the technical training of operation personnel and improve the safety risk protection skills of hoisting workers.
    • Improve and implement a comprehensive acceptance system of component entry.
    • Strengthen the regular inspection and maintenance of loading and unloading equipment such as component transport frames and the hoisting crane.
  • Countermeasures to prevent the collapse of components in the stacking phase:
    • Improve and implement a safety disclosure system, a reward and punishment mechanism, and a comprehensive safety control assessment system, and prohibit the occurrence of too many layers of prefabricated components or missing pads.
    • Hang safety warning signs at the component stacking site, and take moisture-proofing and rainproofing.
    • Improve the security and stability of the component storage frame.
    • Replace the component storage rack with potential safety hazards in time.
  • Countermeasures to prevent falling or injury incidents caused by illegal equipment operation in the component lifting phase:
    • Calculate the maximum lifting mass and use it as a reference to select the appropriate equipment model.
    • Rationalize the arrangement of hanging points to meet requirements.
    • Use red flags to temporarily isolate the affected area of lifting operation from other operating areas.
    • Ensure that the weight balance bar and guide rope are reasonably configured in the process of lifting to avoid the flipping phenomenon caused by wind factors.
    • Clean up foreign matter in the lifting point before lifting the member, and check whether the lifting clip pin and the bending ring are closely connected.
    • Install a torque limiter to prevent the crane from overturning.
  • Countermeasures to prevent component injuries to workers and worker casualties caused by a lack of safety protection at the operation site during the component installation phase:
    • Use double hanging points to secure exterior wall scaffolding.
    • Ensure that hoisted workers hook the steel bar of the column head with the self-locking safety belt through the core when installing prefabricated columns, walls, and plates.
    • Carry out special drills for construction safety periodically.
    • Give priority to the installation of the main safety cable when the main beam is hoisted.
    • Ensure that the height of the floor enclosure is strictly greater than 1.8 m.
    • Ensure that, for electricity use, cable lines are laid in accordance with regulations.
  • Countermeasures to prevent cast-in-place structure collapse during the component positioning phase:
    • Strengthen the on-site inspection of cast-in-place concrete strength.
    • Put up safety signs.
    • Implement a punishment system for unsafe behaviors.
  • Countermeasures to prevent template collapse or mold-moving incidents during the component correction phase:
    • Define the scope of responsibility and work content for departments or individuals through the system in detail, and ensure that responsibilities are met.
    • Ensure a good template connection and reinforcement support.
    • Carry out regular inspection of on-site operation safety to eliminate potential safety hazards.
The proposed countermeasures for workers’ unsafe behaviors in the six stages of hoisting operations are further summarized into four categories based on the classification of safety-evaluation indicators, as shown in Table 13.

5. Field Verification

5.1. Experiment Design

The residential project selected for the case study consists of 14 separate residential buildings numbered Building 1 through Building 14, each containing eleven levels above ground and two levels underground, with a total height of 33.35 m and an elevation difference of 0.45 m between the interior and exterior floor height. The building structure was rated at safety grade two, seismic fortification intensity seven degrees, building site category three, and building anti-floating design grade b.
One independent variable was selected in the case study experiment in order to avoid the uncertain influence of variable mixing and crossing in the experiment, which was whether to implement HAZOP analysis for unsafe behaviors and countermeasures. The countermeasures for workers’ unsafe behaviors in hoisting operations of prefabricated buildings were obtained from the results of the HAZOP analyses presented in this paper.
Two hoisting construction teams in this project were marked as Team A and Team B, and both teams had 30 hoisting workers after adjustment. Team A was selected as the experimental group and strictly implemented the HAZOP analysis for unsafe behaviors and countermeasures in six phases of hoisting operations, whereas Team B was selected as the control group, which maintained its original working habits and did not implement any of the countermeasures for the unsafe behaviors. The duration of the case study was 20 days, which was roughly the schedule to complete the main structure of the four-story building. Due to the maintenance of the structural concrete of each floor, hoisting operations were performed alternatively between two buildings for both teams.
All hoisting workers were asked to wear a wristband sensor to detect when and what unsafe behaviors happened. The jobsite was equipped with 24-h surveillance cameras to capture the type and severity of hoisting workers’ unsafe behaviors. Drone footage was also used to analyze safety risks due to negligence. Through these monitoring measures, the probability density between the independent variable and a reduction in unsafe behaviors was calculated, which consequently determined whether the countermeasures from the HAZOP analysis did help reduce the occurrence of hoisting workers’ unsafe behaviors.

5.2. Experiment Results

The actual experiment case study lasted for 22 days from 29 July to 19 August 2021, including two days of delay due to typhoon weather. Team A completed four floors, including Building 3 floors 2 and 3 and Building 5 floors 2 and 3, while Team B also completed four floors, including Building 1 floors 3 and 4 and Building 6 floors 4 and 5.
By analyzing the wristband sensor data, on-site surveillance images, and drone footage, the unsafe behaviors of the two teams were compared with the safety deviation obtained by the HAZOP analysis method above. After removing the unsafe events that were irrelevant to this study, such as worker heatstroke, fighting, etc., three unsafe behaviors were found in Team A and nine unsafe behaviors were identified in Team B, as shown in Table 14.
A comparison of worker unsafe behaviors between the two hoisting teams in the case study experiment demonstrates that the HAZOP analysis method can be effectively applied to the study of construction workers’ unsafe behaviors and that the countermeasures obtained by the HAZOP analysis method can significantly reduce the occurrence of unsafe behaviors in prefabricated building hoisting operations.

6. Conclusions

Safety management of hoisting operations in prefabricated construction plays a significant role in the overall construction safety of prefabricated building projects. Based on the construction process, hoisting operations in prefabricated buildings were divided into six separate phases in this paper, and the HAZOP method was utilized to systematically analyze workers’ unsafe behaviors. Through survey questionnaires, 23 unsafe behaviors of hoisting workers were identified during the six hoisting phases, and 13 safety influencing factors were determined through a comprehensive literature review. The results of HAZOP analyses revealed significant unsafe behaviors in each of the six phases of hoisting operation in prefabricated buildings and proposed respective countermeasures. In addition, the results of HAZOP analyses were verified by using a comparison and evaluation method from experimental economics through a case study experiment. The findings of this paper provide a theoretical foundation for the analysis and research of construction workers’ unsafe behaviors in hoisting operations and have significant importance in reducing the incident rate in prefabricated building construction. This paper also serves as a reference for decision-making for hoisting safety policies in prefabricated construction projects.

Author Contributions

Writing—original draft preparation, L.Z., H.M., X.L., X.X. and Z.S.; writing—review and editing, L.Z., H.M. and Y.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was collectively funded by Jiangsu Bureau of Housing and Urban and Rural Development, grant number 2018ZD165; Suzhou University of Science and Technology College Students’ Innovative Entrepreneurial Program, grant number 091811104, 091991111; Jiangsu Chinese-Foreign Cooperative Education Demonstration Program; and 2021 National Level 1 Four-Year Construction Management Program, grant number 082110007.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Zhenqun Shi has been involved as a consultant and expert witness in Hangzhou Yongdu Real Estate Development Ltd. The company had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. State Council Information Office. Opinions on Promoting Green Development of Urban and Rural Construction Conference; State Council Information Office: Beijing, China, 2021.
  2. Pereira, V.; Bamel, U.; Paul, H.; Varm, A. Personality and safety behavior: An analysis of worldwide research on road and traffic safety leading to organizational and policy implications. J. Bus. Res. 2022, 151, 185–196. [Google Scholar] [CrossRef]
  3. Guo, Y.; Li, J. The Effect of Emotional Intelligence on Unsafe Behavior of Miners: The Role of Emotional Labor Strategies and Perceived Organizational Support. Int. J. Occup. Saf. Ergon. 2022. accepted author version posted online. [Google Scholar] [CrossRef]
  4. Bandeira, R.; Chambel, M.J.; Carvalho, V.S. Influence of the Work-Family Relationship on Perceived Health 5-Years Later: The Moderating Role of Job Insecurity. Soc. Indic. Res. 2020, 153, 635–650. [Google Scholar] [CrossRef] [PubMed]
  5. Xie, Q.; Xia, N.; Yang, G. Do Family Affairs Matter? Work–Family Conflict and Safety Behavior of Construction Workers. J. Manag. Eng. 2022, 38, 04021074. [Google Scholar] [CrossRef]
  6. He, C.; McCabe, B.; Jia, G.; Sun, J. Effects of Safety Climate and Safety Behavior on Safety Outcomes between Supervisors and Construction Workers. J. Constr. Eng. Manag. 2020, 146, 04019092. [Google Scholar] [CrossRef]
  7. Zhang, J.; Xiang, P.; Zhang, R.; Chen, D.; Ren, Y. Mediating Effect of Risk Propensity between Personality Traits and Unsafe Behavioral Intention of Construction Workers. J. Constr. Eng. Manag. 2020, 146, 04020023. [Google Scholar] [CrossRef]
  8. Guo, H.; Yu, Y.; Ding, Q.; Skitmore, M. Image-and-Skeleton-Based Parameterized Approach to Real-Time Identification of Construction Workers’ Unsafe Behaviors. J. Constr. Eng. Manag. 2018, 144, 04018042. [Google Scholar] [CrossRef] [Green Version]
  9. Liang, Q.; Zhou, Z.; Ye, G.; Shen, L. Unveiling the mechanism of construction workers’ unsafe behaviors from an occupational stress perspective: A qualitative and quantitative examination of a stress–cognition–safety model. Saf. Sci. 2022, 145, 105486. [Google Scholar] [CrossRef]
  10. Hung, P.D.; Su, N.T. Unsafe Construction Behavior Classification Using Deep Convolutional Neural Network. Pattern Recognit. Image Anal. 2021, 31, 271–284. [Google Scholar] [CrossRef]
  11. Khan, R.M.; Bhuiyan, S.A.M.; Haque, F.M.; Rahman, M.A. Effects of unsafe workplace practices on the fire safety performance of ready-made garments (RMG) buildings. Saf. Sci. 2021, 144, 105470. [Google Scholar] [CrossRef]
  12. Zermane, A.; Mohd, T.M.Z.; Baharudin, M.R.; Yusoffa, H.M. Risk assessment of fatal accidents due to work at heights activities using fault tree analysis: Case study in Malaysia. Saf. Sci. 2022, 151, 105724. [Google Scholar] [CrossRef]
  13. Chih, Y.Y.; Kiazad, K.; Li, M.; Capezio, A.; Zhou, L.; Restubog, S.L.D. Broken Promises: Implications for the Job Insecurity and Job Performance of Chinese Construction Workers. J. Constr. Eng. Manag. 2016, 143, 04016114. [Google Scholar] [CrossRef]
  14. Guo, S.; Xiong, C.; Gong, P. A real-time control approach based on intelligent video surveillance for violations by construction workers. J. Civ. Eng. Manag. 2018, 24, 67–78. [Google Scholar] [CrossRef] [Green Version]
  15. Chatzimichailidou, M.; Ma, Y. Using BIM in the safety risk management of modular construction. Saf. Sci. 2022, 154, 105852. [Google Scholar]
  16. James, J.; Ikuma, L.H.; Nahmens, I.; Aghazadeh, F. The impact of Kaizen on safety in modular home manufacturing. Int. J. Adv. Manuf. Technol. 2014, 70, 725–734. [Google Scholar]
  17. Lee, B.; Kim, H. Measuring effects of safety-reminding interventions against risk habituation. Saf. Sci. 2022, 154, 105857. [Google Scholar] [CrossRef]
  18. Forteza, F.J.; Sesé, A.; Carretero-Gómez, J.M. CONSRAT. Construction sites risk assessment tool. Saf. Sci. 2016, 89, 338–354. [Google Scholar] [CrossRef]
  19. Fard, M.M.; Terouhid, S.A.; Kibert, C.J.; Hakim, H. Safety concerns related to modular/prefabricated building construction. Int. J. Consum. Prod. Saf. 2017, 24, 10–23. [Google Scholar] [CrossRef]
  20. Zou, P.X.W.; Sunindijo, R.Y. Skills for managing safety risk, implementing safety task, and developing positive safety climate in construction project. Autom. Constr. 2013, 34, 92–100. [Google Scholar] [CrossRef]
  21. Xu, G. Analysis of Safety Behavior of Prefabricated Building Workers’ Hoisting Operation Based on Computer Vision. Math. Probl. Eng. 2022, 2022, 1715332. [Google Scholar] [CrossRef]
  22. Zhang, Y. Thoughts and Views on Safety of Prefabricated Buildings based on the Computer Technology. J. Phys. Conf. Ser. 2021, 1744, 022090. [Google Scholar] [CrossRef]
  23. Chang, C.; Wu, X.; Yan, X. Multiobjective Optimization of Safety Risk of Prefabricated Building Construction considering Risk Correlation. Math. Probl. Eng. 2020, 2020, 3923486. [Google Scholar] [CrossRef]
  24. Marhavilas, P.K.; Filippidis, M.; Koulinas, G.K.; Koulouriotis, D.E. Safety-assessment by hybridizing the MCDM/AHP & HAZOP-DMRA techniques through safety’s level colored maps: Implementation in a petrochemical industry. Alex. Eng. J. 2022, 61, 6959–6977. [Google Scholar]
  25. Sirima, M.H.; Naon, B.; Bationo, F. Assessment of Industrial Risks Related to Steam Production in a Thermal Production Service: Case of the Ouaga North of Burkina Faso Thermal Production Service. World J. Eng. Technol. 2021, 9, 916–928. [Google Scholar] [CrossRef]
  26. Patle, D.S.; Agrawal, V.; Sharma, S.; Rangaiahbd, G.P. Plantwide control and process safety of formic acid process having a reactive dividing-wall column and three material recycles. Comput. Chem. Eng. 2021, 147, 107248. [Google Scholar] [CrossRef]
  27. Sbaaei, E.S.; Fouad, M.M.K.; Ahmed, T.S. Dynamic Modeling and Analysis of Process Constraints for Improvement for an Industrial Unipol Polypropylene Fluidized Bed Reactor. Arab. J. Sci. Eng. 2022, 47, 6135–6154. [Google Scholar] [CrossRef]
  28. Zhao, Y.; Zhang, B.; Gao, D. Construction of petrochemical knowledge graph based on deep learning. J. Loss Prev. Process Ind. 2022, 76, 104736. [Google Scholar] [CrossRef]
  29. Danko, M.; Labovský, J.; Jelemenský, L. Model based hazard identification: Process time accelerated by GPU redesigning approach. Comput. Chem. Eng. 2021, 144, 107129. [Google Scholar] [CrossRef]
  30. Yang, R.; Utne, I.B. Towards an online risk model for autonomous marine systems (AMS). Ocean. Eng. 2022, 251, 111100. [Google Scholar] [CrossRef]
  31. Niu, Y.; Chen, Q. Identification and management of unsafe behaviors of lifting workers on the construction site based on HAZOP. In Proceedings of the 2018 International Forum on Construction, Aviation and Environmental Engineering-Internet of Things, Guangzhou, China, 11–13 May 2018; Edp Sciences 2018. pp. 203–206. [Google Scholar]
  32. Wang, F.; Gao, J. A novel knowledge database construction method for operation guidance expert system based on HAZOP analysis and accident analysis. J. Loss Prev. Process Ind. 2012, 25, 905–915. [Google Scholar] [CrossRef]
  33. Bao, X. Grey Clustering Evaluation of Prefabricated Building Construction Safety Based on Anp. J. Phys. Conf. Ser. 2022, 2202, 012031. [Google Scholar] [CrossRef]
  34. Wang, G.; Zhou, J. Lightweight Neural Networks-Based Safety Evaluation for Smart Construction Devices. Comput. Intell. Neurosci. 2022, 2022, 3192552. [Google Scholar] [CrossRef] [PubMed]
  35. Singh, A.; Misra, S.C.; Kumar, V.; Kumar, U. Identification and ordering of safety performance indicators using fuzzy TOPSIS: A case study in Indian construction company. Int. J. Qual. Reliab. Manag. 2021, 39, 77–114. [Google Scholar] [CrossRef]
  36. Orogun, B.; Issa, M.H. Developing, Validating and Implementing Performance Metrics to Evaluate the Health and Safety Performance of Sustainable Building Projects. Int. J. Occup. Saf. Ergon. 2021. accepted author version posted online. [Google Scholar] [CrossRef]
  37. Du, M.; Han, T.; Shang, Y. Safety risk control in construction engineering based on the interval analytic hierarchy process and technique for order preference by similarity to ideal solution. Eng. Rep. 2021, 4, e12473. [Google Scholar] [CrossRef]
Table 1. Comparison of statistics on construction safety incidents in China.
Table 1. Comparison of statistics on construction safety incidents in China.
Construction Incident TypeQ1 2021Q1 2020
Construction safety incidents9982
Death toll123101
  From falling incidents54-
  From lifting injury incidents12-
Table 2. Lead words and meaning of the HAZOP analysis.
Table 2. Lead words and meaning of the HAZOP analysis.
Lead WordsMeanings
noneThe established workflow is not followed at all
moreExcessive working hours or intensity
lessSome protective measures are missing
as well asThere are unnecessary actions to achieve the goal
part ofOnly part of the goal is achieved
reverseThe operation process is completely different from the requirements
other thanEvents that do not meet the design requirements occur
Table 3. Distribution of age and years of work experience of surveyed construction workers.
Table 3. Distribution of age and years of work experience of surveyed construction workers.
AgeYears of Work Experience
20–303517%<1 years3115%
31–406130%1–3 years8944%
41–503316%3–5 years7336%
>507437%>5 years105%
Table 4. Reliability statistics of survey data.
Table 4. Reliability statistics of survey data.
Reliability Statistics
Cronbach’s AlphaCronbach’s Alpha Based on Standardized ItemsN of Items
0.9860.98749
Table 5. Identification of safety risks in hoisting operations of prefabricated buildings.
Table 5. Identification of safety risks in hoisting operations of prefabricated buildings.
Hoisting Operation PhaseSafety Risks
Component loading and unloadingThe special iron frame for transportation is not fixed
Component imbalances
Component stackingThe stiffness of the member storage frame is poor
Incorrect position of wooden support
Obstacles in the stacking area
Too many stacked prefabricated floors (>6)
Component liftingThe embedded lifting ring of the component falls off
The lifting point deviates from the center of gravity of the component
Workers stay within the moving range of mechanical boom
Overload operation of lifting equipment
Crane overturning and lifting parts falling
Component installationThe lowering speed of components is too fast, or the components are not kept horizontal when falling
Collapse of exterior wall scaffold
The lower hanging point of the member is not connected by a hoist
No guardrail is installed in elevator shaft and other places
Embedded rebar trips workers
High-altitude-edge working equipment or personnel fall
Neglecting electrical safety
Component positioningPrefabricated overlap plate-positioning correction squeezing hands
Transverse collision of precast outer wall
The strength of concrete does not meet the design requirements when removing the limiter
Component correctionCollapse of prefabricated composite plate support
Precast wall panels collapse
Table 6. Safety-influencing factors in hoisting operations of prefabricated buildings.
Table 6. Safety-influencing factors in hoisting operations of prefabricated buildings.
CategorySafety FactorsInfluencing Factors
HumanTechnical level of employees [36]Hoisting workers’ technical mastery and technical proficiency.
Employee collaboration literacyThe ability of workers to cooperate with each other in construction.
Safety awareness level of construction personnel [37]Safety awareness and habits of site operators.
MaterialQuality of assembled componentsPrefabricated part factory quality or whether damage occurs during transportation.
Hoisting machine selectionWhether the maximum lifting mass of the selected lifting equipment is lower than the maximum mass of the components.
Stability of support system [35]Whether scaffold and support system are stable.
Protection degree of field operationWhether there is protection around the foundation pit, whether there is a protection net, guardrail, etc.
EnvironmentalSevere natural weatherWhether workers operate in fog, typhoon, snowstorm, and similar environments.
Site safety atmosphere [36]Whether the site hangs safety banners, whether the construction team emphasizes safety risks.
ManagerialSafety trainingWhether lifting worker safety training is organized on a regular basis.
Safety management systemWhether there is a perfect and reasonable safety management system.
On-site safety supervision inspectionWhether the construction site supervisor often carries out inspections.
Construction scheme planningWhether the management keeps the operators fully informed of the construction scheme and planning.
Table 7. HAZOP analysis of the components loading and unloading phase.
Table 7. HAZOP analysis of the components loading and unloading phase.
Lead WordDeviationReasonConsequenceCountermeasure
noneThe special iron frame for transportation is not fixedThe stability of the support system is poorPrefabricated parts hurting workersRegular inspection and maintenance of special transport frame
reverseComponent imbalancesThe technical level of employees is lowPrefabricated parts hurting workersHoisting point layout rationalization design
Table 8. HAZOP analysis of the components stacking phase.
Table 8. HAZOP analysis of the components stacking phase.
Lead WordDeviationReasonConsequenceCountermeasure
other thanThe stiffness of the member storage frame is poorThe stability of the support system is poorPrefabricated parts hurting workersCheck and maintain component storage regularly
reverseIncorrect position of wooden supportLow level of safety awareness among workersMember collision with workers when liftingWarning board for specifications of suspension skids
as well asObstacles in the stacking areaNo hidden danger investigation was carried out at the stacking siteWorker injury due to crane collision with an obstacleTake isolation measures at the stacking site
moreToo many stacked prefabricated floors (>6)Lack of safety operation trainingWorkers injury due to prefabricated floors collapseEstablish and implement a corresponding reward and punishment mechanism
Table 9. HAZOP analysis of the components lifting phase.
Table 9. HAZOP analysis of the components lifting phase.
Lead WordDeviationReasonConsequenceCountermeasure
part ofThe embedded lifting ring of the component falls offThe quality of assembled parts is poorA member falls from a high altitude and injures workersImprove and implement a comprehensive acceptance system for the entry of components
reverseThe lifting point deviates from the center of gravity of the componentPractitioners have low cooperation literacyA member falls from a high altitude and injures workersIntroduce a hoisting point layout rationalization design
other thanWorkers stay within the moving range of mechanical boomThe level of safety awareness of construction personnel is lowMechanical boom collides with workersFlag the working area is with red pennants
moreOverload operation of lifting equipmentWrong hoisting machine selectionEquipment failure resulted in worker injuryCalculate the maximum lifting mass and select the equipment model based on it
other thanCrane overturning and lifting parts fallingSevere natural weatherWorker casualties and economic lossesAdd a moment limiter and conduct qualified acceptance for crane support foundation
Table 10. HAZOP analysis of the component installation phase.
Table 10. HAZOP analysis of the component installation phase.
Lead WordDeviationReasonConsequenceCountermeasure
moreThe lowering speed of components is too fast, or the components are not kept horizontal when fallingThe level of safety awareness of construction personnel is lowStructural injuries to workersPeriodically carry out construction safety drills
as well asCollapse of external wall scaffoldThe supervision of hanging point installation is not strictWorker death by high-altitude fallAdopt an installation mode of hanging points and double fuses
noneThe lower hanging point of the member is not connected by a hoistThe technical level of employees is lowWorker injury due to component slippage during the lifting processHave the construction plan verified by experts
noneNo guardrail is installed in elevator shaft and other placesThe protection degree of field operation is weakWorker falls due to stepping into the airSet a safety barrier with a height greater than 1.8 m
as well asEmbedded rebar trips workersThe protection degree of field operation is poorWorker injuryLabel and cover embedded parts with film
as well asHigh-altitude-edge working equipment or personnel fallThe protection degree of field operation is weakLift workers fall to death or injure workers belowInstall safety barriers and wear self-locking belts
lessNeglecting electrical safetyOn-site safety supervision inspection is not strictWorker death by electrocutionRestrict operation and work to specially assigned and certificated personnel
Table 11. HAZOP analysis of the components positioning phase.
Table 11. HAZOP analysis of the components positioning phase.
Lead WordDeviationReasonConsequenceCountermeasure
as well asPrefabricated overlap plate-positioning correction squeezing handsPoor safe operation trainingWorker injuryEquip workers with protective equipment
other thanTransverse collision of precast outer wallPractitioners have low cooperation literacyWorker injury or death by fallingCheck to ensure that the angle between the sling and the plate plane is between 45° and 60°
lessThe strength of concrete does not meet the design requirements when removing the limiterConstruction scheme planning is not comprehensiveCollapse of concrete causes worker injury or deathStrengthen on-site supervision and inspection
Table 12. HAZOP analysis of the component correction phase.
Table 12. HAZOP analysis of the component correction phase.
Lead WordDeviationReasonConsequenceCountermeasure
part ofCollapse of prefabricated composite plate supportThe stability of the support system is poorWorker death and injuryHarden template connections
part ofPrecast wall panel collapseThe stability of the support system is poorWorker death and injuryUse wall braces and seven-letter codes for reinforcement
Table 13. A summary of countermeasures for workers’ unsafe behaviors in hoisting operations.
Table 13. A summary of countermeasures for workers’ unsafe behaviors in hoisting operations.
CategoryCountermeasure
HumanStrengthen the technical training and assessment of operators
MaterialStrengthen regular inspection and maintenance of equipment
EnvironmentalImprove and implement rules and regulations for operation in severe weather conditions
Strengthen the safe working atmosphere of the construction team
ManagerialImprove and implement various safety management systems
Carry out special drills for construction safety periodically
Implement regular inspection of on-site operation safety
Table 14. Comparison of workers’ unsafe behaviors between the two hoisting teams.
Table 14. Comparison of workers’ unsafe behaviors between the two hoisting teams.
No.DateLocationDescription
Team A14 AugustBuilding 3 Floor 2Portions of scaffolding safety net are not fully secured.
24 AugustBuilding 5 Floor 2The outer wall component fell off during lifting.
317 August A worker squeezed his finger while positioning and correcting the laminated plates.
Team B12 August A worker squeezed his finger while positioning and correcting the laminated plates.
22 AugustBuilding 6The third batch of prefabricated laminated slabs were stacked too high.
35 AugustBuilding 1The windowed wall members of the kitchen were not stacked correctly with special storage racks.
411 AugustBuilding 6 Floor 4The outer wall component fell off during lifting.
513 AugustBuilding 1 Floor 4The stair safety guardrail shelter is not complete
613 AugustBuilding 1 Floor 4The elevator shaft protection shelter is not complete.
713 August Overturning of concrete pump truck
816 AugustBuilding 1Multiple machines used the same circuit breaker.
917 AugustBuilding 6 Floor 5The mold moved when the floor was being poured.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Zhu, L.; Ma, H.; Huang, Y.; Liu, X.; Xu, X.; Shi, Z. Analyzing Construction Workers’ Unsafe Behaviors in Hoisting Operations of Prefabricated Buildings Using HAZOP. Int. J. Environ. Res. Public Health 2022, 19, 15275. https://doi.org/10.3390/ijerph192215275

AMA Style

Zhu L, Ma H, Huang Y, Liu X, Xu X, Shi Z. Analyzing Construction Workers’ Unsafe Behaviors in Hoisting Operations of Prefabricated Buildings Using HAZOP. International Journal of Environmental Research and Public Health. 2022; 19(22):15275. https://doi.org/10.3390/ijerph192215275

Chicago/Turabian Style

Zhu, Lianbo, Hongxin Ma, Yilei Huang, Xun Liu, Xiaojin Xu, and Zhenqun Shi. 2022. "Analyzing Construction Workers’ Unsafe Behaviors in Hoisting Operations of Prefabricated Buildings Using HAZOP" International Journal of Environmental Research and Public Health 19, no. 22: 15275. https://doi.org/10.3390/ijerph192215275

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop