Allocation of performance shaping factors in the risk assessment of an offshore installation

Dynamic modeling of human error in industrial maintenance through structural analysis and system dynamics

Human error constitutes a significant cause of accidents across diverse industries, leading to adverse consequences and heightened disruptions in maintenance operations. Organizations can enhance their decision-making process by quantifying human errors and identifying the underlying influencing factors, thereby mitigating their repercussions. Consequently, it becomes crucial to examine the value of human error probability (HEP) during these activities. The objective of this paper is to determine and simulate HEP in maintenance tasks at a cement factory, utilizing performance shaping factors (PSFs). The research employs the cross-impact matrix multiplication applied to classification (MICMAC) analysis method to evaluate the dependencies, impacts, and relationships among the factors influencing human error. This approach classifies and assesses the dependencies and impacts of different factors on HEP, occupational accidents, and related costs. The study also underscores that PSFs can dynamically change under the influence of other variables, emphasizing the necessity to forecast the behavior of human error over time. Therefore, this paper utilizes the MICMAC method to analyze the interdependencies, relationships, and impact levels among different variables. These relationships are then utilized to optimize the implementation of the system dynamics (SD) method. An SD model is employed to forecast the system's behavior, and multiple scenarios are presented. By considering the HEP value, managers can adjust organizational conditions and personnel to ensure acceptability. The paper also presents various scenarios related to HEP to assist managers in making informed decisions.

Risk assessment for handling hazardous substances within the European industry: Available methodologies and research streams

After the Seveso disaster occurred more than 40 years ago, there has been an increasing awareness of the potential impacts that similar accident events can occur in a wide range of process establishments, where the handling and production of hazardous substances pose a real threat to society and the environment. In these industrial sites denominated "Seveso sites," the urgent need for an effective strategy emerged markedly to handle hazardous activities and to ensure safe conditions. Since then, the main challenging research issues have focused on how to prevent such accident events and how to mitigate their consequences leading to the development of many risk assessment methodologies. In recent years, researchers and practitioners have tried to provide useful overviews of the existing risk assessment methodologies proposing several reviews. However, these reviews are not exhaustive because they are either dated or focus only on one specific topic (e.g., liquefied natural gas, domino effect, etc.). This work aims to overcome the limitations of the current reviews by providing an up-to-date and comprehensive overview of the risk assessment methodologies for handling hazardous substances within the European industry. In particular, we have focused on the current techniques for hazards and accident scenarios identification, as well as probability and consequence analyses for both onshore and offshore installations. Thus, we have identified the research streams that have characterized the activities of researchers and practitioners over the years, and we have then presented and discussed the different risk assessment methodologies available concerning the research stream that they belong to.

Many faces of survey equipment failures during marine research at sea-Risk analysis

Research of the marine environment is still a huge challenge for humanity. Each survey campaign is a complex project, where research vessels and relevant survey equipment is used. One of the problems that limit the success of working at sea are failures of survey equipment. The aim of this paper was to identify the most common survey equipment failures during marine research, find their causes and analyze identified risks. The authors employ risk assessment methodology in maritime research at sea and present its practical utility and contribution in social and organizational development. For this purpose we based the analysis on the review of relevant project documentation (Daily Progress Reports, Observation Cards) and the questionnaire addressed to specialists who carry out their survey work on board research vessels and also people involved in the implementation of offshore projects. The research reveals that 76.3% respondents participated in a project which had to be stopped due to a failure of the survey equipment that required return to the port which highlights that the problem which was analyzed is of particular importance. The questionnaire form was designed to obtain as much information as possible on the types of failures with examples and also their causes according to three groups: human factors, technical factors and forces of nature. Twelve risks were identified and analyzed. The authors also stress the relationship between the quality of research project management and its implementation in the context of the failure rate of measuring equipment.

A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H

Unsafe crew acts (UCAs) related to human errors are the main contributors to maritime accidents. The prediction of unsafe crew acts will provide an early warning for maritime accidents, which is significant to shipping companies. However, there exist gaps between the prediction models developed by researchers and those adopted by practitioners in human risk analysis (HRA) of the maritime industry. In addition, most research regarding human factors of maritime safety has concentrated on hazard identification or accident analysis, but not on early warning of UCAs. This paper proposes a Bayesian network (BN) version of the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method to predict the probability of seafarers' unsafe acts. After the identification of performance-shaping factors (PSFs) that influence seafarers' unsafe acts during navigation, the developed prediction model, which integrates the practicability of SPAR-H and the forward and backward inference functions of BN, is adopted to evaluate the probabilistic risk of unsafe acts and PSFs. The model can also be used when the available information is insufficient. Case studies demonstrate the practicability of the model in quantitatively predicting unsafe crew acts. The method allows evaluating whether a seafarer is capable of fulfilling their responsibility and providing an early warning for decision-makers, thereby avoiding human errors and sequentially preventing maritime accidents. The method can also be considered as a starting point for applying the efforts of HRA researchers to the real world for practitioners.

Methodology for Evaluating Risk of Visual Inspection Tasks of Aircraft Engine Blades

Risk assessment methods are widely used in aviation, but have not been demonstrated for visual inspection of aircraft engine components. The complexity in this field arises from the variety of defect types and the different manifestation thereof with each level of disassembly. A new risk framework was designed to include contextual factors. Those factors were identified using Bowtie analysis to be criticality, severity, and detectability. This framework yields a risk metric that describes the extent to which a defect might stay undetected during the inspection task, and result in adverse safety outcomes. A simplification of the framework provides a method for go/no-go decision-making. The results of the study reveal that the defect detectability is highly dependent on specific views of the blade, and the risk can be quantified. Defects that involve material separation or removal such as scratches, tip rub, nicks, tears, cracks, and breaking, are best shown in airfoil views. Defects that involve material deformation and change of shape, such as tip curl, dents on the leading edges, bents, and battered blades, have lower risk if edge views can be provided. This research proposes that many risk assessments may be reduced to three factors: consequence, likelihood, and a cofactor. The latter represents the industrial context, and can comprise multiple sub-factors that are application-specific. A method has been devised, including appropriate scales, for the inclusion of these into the risk assessment.