A taxonomy of performance shaping factors for shield tunnel construction

Abstract

Purpose On shield tunnel construction (STC) site, human error is widely recognized as essential to accident. It is necessary to explain which factors lead to human error and how these factors can influence human performance. Human reliability analysis supports such necessity through modeling the performance shaping factors (PSFs). The purpose of this paper is to establish and validate a PSF taxonomy for the STC context. Design/methodology/approach The approach taken in this study mainly consists of three steps. First, a description of the STC context is proposed through the analysis of the STC context. Second, the literature which stretch across the PSF methodologies, cognitive psychology and human factors of STC and other construction industries are reviewed to develop an initial set of PSFs. Finally, a final PSF set is modified and validated based on STC task analysis and STC accidents cases. Findings The PSF taxonomy constituted by 4 main components, 4 hierarchies and 85 PSFs is established for human behavior modeling and simulation under the STC context. Furthermore, by comparing and evaluating the performance of STC PSF and existing PSF studies, the proposed PSF taxonomy meets the requirement for qualitative and quantitative analysis. Practical implications The PSF taxonomy can provide a basis and support for human behavior modeling and simulation under the STC context. Integrating PSFs into a behavior simulation model provides a more realistic and integrated assessment of human error by manifesting the influence of each PSFs on the cognitive processes. The simulation results can suggest concrete points for the improvement of STC safety management. Originality/value This paper develops a taxonomy of PSFs that addresses the various unique influences of the STC context on human behaviors. The harsh underground working conditions and diverse resources of system information are identified as key characteristics of the STC context. Furthermore, the PSF taxonomy can be integrated into a human cognitive behavior model to predict the worker’s behavior on STC site in future work.

Multi-agent based safety computational experiment system for shield tunneling projects

“…As Figure 1 illustrates, the physical safety system of shield tunneling projects is featured by human-machine-environment interaction (Li et al , 2018a, b). Human, shield machine and underground environment are the core elements of the physical safety system.…”

“…The cognitive decision-making module is used to simulate the manager agent's cognitive and decision process. As the previous work of our research group, Li et al (2018a, b) identified a set of PSFs under the context of shield tunneling construction. In this study, nine key PSFs of them are considered, which is the age, personality, experience, time-constraint load, cognitive load, stress, fatigue, task critically and task consequence.…”

“…Viewed from another perspective, the first three PSFs are static, while the last six are dynamic. For these PSFs, Lin et al (2013) and Li et al (2018a, b) have comprehensively evaluated the impacts on operators' behaviors. By incorporating empirical findings from metro tunnel construction with this theoretical analysis, the quantitative assessments of the PSFs are proposed as in Table 1.…”

“…For the manager and operator, age, personality and work experience could directly affect their cognition and behaviors. Unsafe behaviors often result from them and finally lead to safety accidents (Li et al , 2018a, b). For shield machine, thrust force, cutter speed, screw conveyor speed, and grouting pressure are considered as very important technical factors to guarantee safety in the shield tunneling process (Suwansawat and Einstein, 2006).…”

Identifying and clustering performance shaping factors for nuclear power plant commissioning tasks

“…In spite of the HRA methods and topics, expansive studies have been conducted on PSF frameworks in specific domains, including NPP (Ekanem et al, 2016; Groth & Mosleh, 2012; J. W. Kim & Jung, 2003; J. Kim & Park, 2012; A. R. Kim et al, 2016; Lee et al, 2011; Liu et al, 2016; etc. ), industrial maintenance (Franciosi, Pasquale, Iannone, & Miranda, 2019), navigation (Gould, Røed, Koefoed, Bridger, & Moen, 2006), radiotherapy (Pandya, Podofillini, Emert, Lomax, & Dang, 2018), surgery (Onofrio & Trucco, 2018), offshore structures (Bea, 2000), marine (Xi & Hu, 2012), spaceflight (Mindock & Klaus, 2011), tunnel construction (Li, Yu, & Wang, 2018), civil flight (L. Wang, Wang, Chen, & Dong, 2018), human–automation interaction (Fereidunian et al, 2010), railways (Kyriakidis, Majumdar, Grote, & Ochieng, 2012; Lindner, Milius, Schwencke, & Lemmer, 2013), driving (W. H. Wang, Cao, Ikeuchi, & Bubb, 2010), etc. PSF frameworks have been proposed for specific domains with specific characteristics of humans, systems, and working conditions.…”