A review of crane safety in the construction industry

Identification of the effective crane hook's cross-section by incorporating finite element method and programming language

The crane hook is a widely utilized component in several industries for the purpose of lifting things. The crane hook must possess the capacity to withstand the intended load without encountering any complications, hence ensuring the safety of both personnel and the objects being lifted. The process of analysis is crucial for the effective utilization of a crane hook. The primary aim of this study was to determine the most efficient cross-sectional crane hook among five distinct geometric profiles. This was achieved through the application of finite element analysis using Solidworks software. Subsequently, the identified cross-sectional profile was further examined using the Python programming language, taking into account the classical equation of a curved beam. The five cross-sectional shapes seen in the study were circular, rectangular, trapezoidal, I-shaped, and T-shaped. For the purposes of this investigation, the chosen material for each cross-sectional crane hook model was 34CrMo4 steel. Despite the identical boundary constraints imposed on all the chosen cross-sectional crane hook profiles, it was observed that the trapezoidal cross-sectional crane hook exhibited superior performance compared to the others. The trapezoidal cross-sectional crane hook model exhibited a Von Mises stress of 203 MPa, with a corresponding factor of safety of 3.20. Further experimentation was conducted using Python to examine the trapezoidal profile. The results indicated that an increased level of parallelism in the inner side of the trapezoidal shape corresponded to a higher factor of safety. Hence, it is advisable to maintain the trapezoidal cross-sectional profile of the crane hook, with due consideration given to maximizing the length of the inner parallel side. The enhancement of design leads to a decrease in the likelihood of failure and the occurrence of undesirable accidents.

Identification and analysis of hoisting safety risk factors for IBS construction based on the AcciMap and cases study

Hoisting is an essential aspect of Industrial Building System (IBS) construction. Although research on hoisting safety in China has made strides to focus on "worker," "data," "task," "site," and "accident," there still needs to be more approaches based on multi-dimensional social system thinking. Therefore, the paper aims to fill this gap. We investigated 105 hoisting accidents in China and found that hoisting accidents occurred most frequently in China's southeast coastal region; truck-mounted cranes and tower cranes were the most common types of machinery involved in accidents; hoisting load off, capsizing of crane machinery, and workers falling from height are the three most common accident types; the average impact of a single hoisting accident is approximately RMB 2.43 million direct economic loss, 1.543 deaths and 0.829 injured. This study used three algorithms (Rindge regression, Lasson regression, and partial least squares regression) to explore the impact of deaths and injuries on direct economic losses. By combining Rasmussen's risk framework with the characteristics of hoisting construction, six risk domains and thirty-six safety risk factors were identified. Finally, we used AcciMap technology to construct a qualitative IBS hoisting management model, which exhaustively presents the systematic levels and propagation paths of the influencing factors by the PDCA method. The research helps academics explore strategies to improve the safety of hoisting construction in IBS. Moreover, the study outcomes can inform the policy-making process towards promoting healthy and sustainable construction development.

Design of Twin Builder-Based Digital Twin Online Monitoring System for Crane Girders

The crossbeam is frequently subjected to alternating loads during work as an essential load-bearing part of the crane. However, due to the large volume and the limitations of detection technology, it is impossible to realize online monitoring of the mechanical state. The ongoing advancement of ROMing and digital twin technology plays a pivotal role in facilitating the resolution of this particular issue. In this paper, we take the crane beam as the physical entity and combine the Twin Builder reduced-order technology and Deployer digital twin deployment technology to establish a digital twin of the beam. The load recognition model within the twin system exhibits a prediction error rate of ±5%. Furthermore, the accuracy of the ROM surpasses that of conventional machine learning models by a factor of 25. Upon deployment on the web platform, the results are delivered within 0.5 s, representing a substantial improvement as it is merely 1/15 of the time required for traditional 3D displays. The digital twin online monitoring system has the advantages of high accuracy and low requirements for monitoring equipment, which can be widely used in engineering practice to solve the problem that the mechanical state of large parts cannot be accurately monitored online.

Soft-Computing-Based Estimation of a Static Load for an Overhead Crane

Payload weight detection plays an important role in condition monitoring and automation of cranes. Crane cells and scales are commonly used in industrial practice; however, when their installation to the hoisting equipment is not possible or costly, an alternative solution is to derive information about the load weight indirectly from other sensors. In this paper, a static payload weight is estimated based on the local strain of a crane's girder and the current position of the trolley. Soft-computing-based techniques are used to derive a nonlinear input-output relationship between the measured signals and the estimated payload mass. Data-driven identification is performed using a novel variant of genetic programming named grammar-guided genetic programming with sparse regression, multi-gene genetic programming, and subtractive fuzzy clustering method combined with the least squares algorithm on experimental data obtained from a laboratory overhead crane. A comparative analysis of the methods showed that multi-gene genetic programming and grammar-guided genetic programming with sparse regression performed similarly in terms of accuracy and both performed better than subtractive fuzzy clustering. The novel approach was able to find a more parsimonious model with its direct implantation having a lower execution time.

Data mining of the essential causes of different types of fatal construction accidents

Accident analysis is used to discover the causes of workplace injuries and devise methods for preventing them in the future. There has been little discussion in the previous studies of the specific elements contributing to deadly construction accidents. In contrast to previous studies, this study focuses on the causes of fatal construction accidents based on management factors, unsafe site conditions, and workers' unsafe actions. The association rule mining technique identifies the hidden patterns or knowledge between the root causes of fatal construction accidents, and one hundred meaningful association rules were extracted from the two hundred and fifty-three rules generated. It was discovered that many fatal construction accidents were caused by management factors, unsafe site circumstances, and risky worker behaviors. These analyses can be used to demonstrate plausible cause-and-effect correlations, assisting in building a safer working environment in the construction sector. The study findings can be used more efficiently to design effective inspection procedures and occupational safety initiatives. Finally, the proposed method should be tested in a broader range of construction situations and scenarios to ensure that it is as accurate as possible.

Epidemiology of occupational injuries in construction workers between 2009 and 2018 in South Korea

BACKGROUND

This study aimed to investigate the characteristics of occupational injuries based on fatality, sex, and classification of occupations among construction workers using workers' compensation (WC) insurance data in South Korea.

METHODS

We collected WC insurance data from the Korea Workers' Compensation & Welfare Service for all construction workers between 2009 and 2018. Data from 158,947 accepted claims for occupational injury were extracted, and the demographic features, occupational injury types, and annual trends were analyzed for fatal and nonfatal cases. The annual incidence and mortality trends of occupational injury were estimated using negative binomial regression and Poisson regression models, for injury incidence and mortality respectively.

RESULTS

Among a total of 158,947 occupational injury cases, there were 155,772 (98%) nonfatal injuries and 3175 (2%) fatal injuries. For all occupational injuries, Construction Elementary Workers (6th Korean Standard Classification of Occupations (KSCO) 910; 45.7%) was the most frequent occupation, followed by Construction-Related Technical Workers (6th KSCO 772; 39.2%). The most frequent injury type was a fracture, followed by ruptures or lacerations and contusions. The incidence of all occupational injuries increased from 700.36 per 100,000 persons in 2009 to 1,195.98 per 100,000 persons in 2018. Further, deaths from injuries at work followed a significantly increasing annual trend [mortality rate ratio 1.04 (95% CI: 1.03-1.05)] from 2009 to 2018.

CONCLUSION

The over two-thirds increased incidence of occupational injuries and significantly increasing mortality trends for occupational injuries during the last 10 years indicate the need for aggressive intervention in occupational safety and health management within the Korean construction industry.

Trends in Catastrophic Occupational Incidents among Electrical Contractors, 2007-2013

This study used methodologies of descriptive and quantitative statistics to identify the contributing factors most affecting occupational accident outcomes among electrical contracting enterprises, given an accident occurred. Accident reports were collected from the Occupational Safety and Health Administration's fatality and catastrophe database. To ensure the reliability of the data, the team manually codified more than 600 incidents through a comprehensive content analysis using injury-classification standards. Inclusive of both fatal and non-fatal injuries, the results showed that most accidents happened in nonresidential buildings, new construction, and small projects (i.e., $50,000 or less). The main source of injuries manifested in parts and materials (46%), followed by tools, instruments, and equipment (19%), and structure and surfaces (16%). The most frequent types of injuries were fractures (31%), electrocutions (27%), and electrical burns (14%); the main injured body parts were upper extremities (25%), head (23%), and body system (18%). Among non-fatal cases, falls (37%), exposure to electricity (36%), and contact with objects (19%) caused most injuries; among fatal cases, exposure to electricity was the leading cause of death (50%), followed by falls (28%) and contact with objects (19%). The analysis also investigated the impact of several accident factors on the degree of injuries and found significant effects from such factors such as project type, source of injury, cause of injury, injured part of body, nature of injury, and eventtype. In other words, the statistical probability of a fatal accident-given an accident occurrence-changes significantly based on the degree of these factors. The results of this study, as depicted in the proposed decision tree model, revealed that the most important factor for predicting the nature of injury (electrical or non-electrical) is: whether the source of injury is parts and materials; followed by whether the source of injury is tools, instruments, and equipment. In other words, in predicting (with a 94.31% accuracy) the nature of injury as electrical or non-electrical, whether the source of injury is parts and materials and whether the source of injury is tools, instruments, and equipment are very important. Seven decision rules were derived from the proposed decision tree model. Beyond these outcomes, the described methodology contributes to the accident-analysis body of knowledge by providing a framework for codifying data from accident reports to facilitate future analysis and modeling attempts to subsequently mitigate more injuries in other fields.

Proposal for Tower Crane Productivity Indicators Based on Data Analysis in the Era of Construction 4.0

This article proposes a methodology to measure the productivity of a construction site through the analysis of tower crane data. These data were obtained from a data logger that records a time series of spatial and load data from the lifting machine during the structural phase of a construction project. The first step was data collection, followed by preparation, which consisted of formatting and cleaning the dataset. Then, a visualization step identified which data was the most meaningful for the practitioners. From that, the activity of the tower crane was measured by extracting effective lifting operations using the load signal essentially. Having used such a sampling technique allows statistical analysis on the duration, load, and curvilinear distance of every extracted lifting operation. The build statistical distribution and indicators were finally used to compare construction site productivity.

Priority of Accident Cause Based on Tower Crane Type for the Realization of Sustainable Management at Korean Construction Sites

Construction safety is a key factor among the many factors related to the sustainable management of construction sites. Although research is underway to reduce potential accidents in the construction industry in Korea, the number of tower crane (T/C) accidents is consistently increasing based on the increased use of such cranes. In this study, the priorities of accident causes for each T/C type were derived and utilized for the sustainable management of construction sites. An analytic hierarchy process (AHP) questionnaire was completed by experts such as construction engineers, construction managers, safety engineers, and T/C operators with more than ten years of field experience. The results of the AHP questionnaire revealed that the leading cause of cab-control T/C accidents is poor operator visibility, while the leading cause of accidents related to remote-control T/Cs is the poor management of lifting objects and control of surroundings. The high-ranking causes derived in this study should be managed and priority measures should be implemented to reduce the number of T/C accidents.

Causes and prevention of mobile crane-related accidents in South Korea

Mobile cranes account for a considerable proportion of crane-related accidents in South Korea. The authors used descriptive and non-parametric statistics to analyse 245 fatal accidents in South Korea from 2007 to 2016. The results showed that human error and crane problems were the main cause of accidents; riggers accounted for the largest number of deaths. To reduce the number of mobile crane fatalities, the authors made recommendations in four areas: educational aspects, mobile crane aspects, technical aspects and other issues. Firstly, business owners need to establish a systematic education system suitable for workers in mobile crane operations. Secondly, efforts should be made to tighten the quality of safety inspections of cranes and supervision of workplaces. Thirdly, efforts should be made to develop more human error-free equipment. Lastly, it is necessary to develop a systematic accident reporting system containing more detailed information to allow a fuller understanding of accident causation.

A cyber–physical system (CPS) for planning and monitoring mobile cranes on construction sites

Various ways of improving mobile crane safety on construction sites have been introduced and adopted, such as visualisation of mobile crane operations, algorithm-based lift planning and spatial conflict identification. However, these focus only on either planning or monitoring aspects – there is no effective method for planning and monitoring mobile crane operations consistently with real-time control feedback. Developments in information technology, notably cyber–physical systems, are changing the way that planning and monitoring can be done. This paper explores the applicability of such systems to mobile cranes on construction sites. A five-layer system architecture is proposed, and the key components and the enabling technologies in each layer are investigated. The potential benefits and barriers in the implementation of the proposed system are also highlighted. By enabling bidirectional communication and coordination between physical components and their virtual representations, the system offers advantages in managing mobile cranes in such a way as to facilitate effective planning, proactively monitor crane operations, provide rich multimodal feedback to crane operators and, ultimately, avoid mobile crane failures and mobile-crane-related accidents.

Trends of occupational fatalities involving machines, United States, 1992-2010

BACKGROUND

This paper describes trends of occupational machine-related fatalities from 1992-2010. We examine temporal patterns by worker demographics, machine types (e.g., stationary, mobile), and industries.

METHODS

We analyzed fatalities from Census of Fatal Occupational Injuries data provided by the Bureau of Labor Statistics to the National Institute for Occupational Safety and Health. We used injury source to identify machine-related incidents and Poisson regression to assess trends over the 19-year period.

RESULTS

There was an average annual decrease of 2.8% in overall machine-related fatality rates from 1992 through 2010. Mobile machine-related fatality rates decreased an average of 2.6% annually and stationary machine-related rates decreased an average of 3.5% annually. Groups that continued to be at high risk included older workers; self-employed; and workers in agriculture/forestry/fishing, construction, and mining.

CONCLUSION

Addressing dangers posed by tractors, excavators, and other mobile machines needs to continue. High-risk worker groups should receive targeted information on machine safety.

Analysis of Material Handling Safety in Construction Sites and Countermeasures for Effective Enhancement

One of many hazardous workplaces includes the construction sites as they involve several dangerous tasks. Many studies have revealed that material handling equipment is a major cause of accidents at these sites. Though safety measures are being followed and monitored continuously, accident rates are still high as either workers are unaware of hazards or the safety regulations are not being strictly followed. This paper analyses the safety management systems at construction sites through means of questionnaire surveys with employees, specifically referring to safety of material handling equipment. Based on results of the questionnaire surveys, two construction sites were selected for a safety education program targeting worker safety related to material handling equipment. Knowledge levels of the workers were gathered before and after the program and results obtained were subjected to a t-test analysis to mark significance level of the conducted safety education program.

Modelling safety of gantry crane operations using Petri nets

Being a powerful tool in modelling industrial and service operations, Petri net (PN) has been extremely used in different domains, but its application in safety study is limited. In this study, we model the gantry crane operations used for industrial activities using generalized stochastic PNs. The complete cycle of operations of the gantry crane is split into three parts namely inspection and loading, movement of load, and unloading of load. PN models are developed for all three parts and the whole system as well. The developed PN models have captured the safety issues through reachability tree. The hazardous states are identified and how they ultimately lead to some unwanted accidents is demonstrated. The possibility of falling of load and failure of hook, sling, attachment and hoist rope are identified. Possible suggestions based on the study are presented for redesign of the system. For example, mechanical stoppage of operations in case of loosely connected load, and warning system for use of wrong buttons is tested using modified models.

A practical application combining wireless sensor networks and Internet of Things: Safety Management System for Tower Crane Groups

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things.

Occupational demands and health effects for bricklayers and construction supervisors: A systematic review

BACKGROUND

knowledge was gathered on occupational demands and health effects of two occupations in the construction industry, bricklayers and supervisors, in order to design a job-specific workers' health surveillance (WHS) for construction workers.

METHODS

we systematically searched MEDLINE, EMBASE, PsycINFO, HSELINE, NIOSHTIC-2, and Picarta up to December 2008.

RESULTS

a total of 60 articles were included. Evidence was found for the following demands for bricklayers: energetic load (exceeding 25% heart rate reserve), load on the lower back (exceeding the NIOSH-threshold value of 3.4 kN), repetitive force exertions of the upper extremities, frequent bending with trunk flexion exceeding 60° and working with the arms more than 60° elevated. Environmental demands include: dust and quartz exposure (exceeding the limit values of 3.0 and 0.05 mg/m(3), respectively), vibration and noise (exceeding the limit value of 80 dBA). Bricklayers are at increased risk of lung cancer, low back pain, complaints of arms and legs and getting injuries. Among construction supervisors are walking and standing common physically demanding activities. Psychosocial demands with evidence for supervisors were mental demands, workload, time pressure, working long hours, and social-organizational factors. Supervisors are at increased risk of lung cancer and injuries.

CONCLUSIONS

for bricklayers evidence was found for physical demands and risk on low back pain and complaints of arms and legs, for construction supervisors on psychosocial demands. Both occupations are at increased risk of lung cancer and injuries. Job-specific demands and health effects should be incorporated in WHS for construction workers.