Human Error Assessment And Reduction Technique Research Articles

A pre-exercise screening of helicopter underwater escape training using a modified human reliability analysis with rule-based mechanism

This study conducts a human reliability analysis to develop a pre-exercise screening tool for helicopter underwater escape training (HUET) to proactively improve training facilities and to contribute attendees’ performance. In this context, a modified human error assessment and reduction technique (HEART) was adapted. The technique investigates error producing conditions (EPC) and general task type (GTT) variables considering attendees profile, training infrastructure conditions, and 16 sub-steps of HUET exercises. Since the identification of EPC and GTT is still a key limitation of traditional HEART, this study extends a basic rule-based mechanism based on if-then-else comparison matrix structure to enhance accuracy in practice. The case study underscores the feasibility of individual, provider, and procedural interventions, enhancing training success and practical application of skills in real incidents. The application of a rule-based selection algorithm for General Task Type (GTT) determination enhances objectivity, contributing to a more controlled identification and minimisation of errors. The case study, tailored specifically for practical training, delineates the feasibility of individual-based, training provider-based, and procedural-based interventions. Additionally, mitigating factors like ‘emotional stress’ and ‘unfamiliarity’ through advanced safety measures can boost attendees’ self-confidence, leading to improved training success and practical skill application in real-world scenarios.

Estimating the impact of label design on reducing the risk of medication errors by applying HEART in drug administration

Medication errors are one of the biggest problems in healthcare. The medicines’ poor labelling design (i.e. look-alike labels) is a well-recognised risk for potential confusion, wrong administration, and patient damage. Human factors and ergonomics (HFE) encourages the human-centred design of system elements, which might reduce medication errors and improve people’s well-being and system performance.ObjectiveThe aim of the present study is twofold: (i) to use a human reliability analysis technique to evaluate a medication administration task within a simulated scenario of a neonatal intensive care unit (NICU) and (ii) to estimate the impact of a human-centred design (HCD) label in medication administration compared to a look-alike (LA) label.MethodThis paper used a modified version of the human error assessment and reduction technique (HEART) to analyse a medication administration task in a simulated NICU scenario. The modified technique involved expert nurses quantifying the likelihood of unreliability of a task and rating the conditions, including medicine labels, which most affect the successful completion of the task.ResultsFindings suggest that error producing conditions (EPCs), such as a shortage of time available for error detection and correction, no independent checking of output, and distractions, might increase human error probability (HEP) in administering medications. Results also showed that the assessed HEP and the relative percentage of contribution to unreliability reduced by more than 40% when the HCD label was evaluated compared to the LA label.ConclusionIncluding labelling design based on HFE might help increase human reliability when administering medications under critical conditions.

An analysis of human error and reliability in the operation of fixed CO2 systems on cargo ships using HEART Dempster-Shafer evidence theory approach

CO2 fixed fire extinguishing system activation accidents may occur as a result of unintentional system activation or human error. Crew members present in the area could suffer serious consequences, including death, if CO2 gas is released into a protected compartment such as the engine room, CO2 room, or cargo area. It is therefore crucial to investigate and address the causes of such accidents. The use of Dempster-Shafer (D-S) theory and the Human Error Assessment and Reduction Technique (HEART) to the Human Reliability Analysis (HRA) of CO2 fixed fire extinguishing system activation accidents is discussed in this study. On the one hand, D-S theory allows for uncertainty-based reasoning and can be extremely advantageous, especially when analysing complex systems where there are many potential challenges. On the other hand, HEART is an organised method to examine and reduce human error in high-risk systems. Together, these techniques provide a powerful tool for identifying and addressing the underlying causes of CO2 fixed fire extinguishing system activation accidents. The study revealed that the total human error probability (HEP) for the CO2 fixed fire extinguishing system was 3.10E-01 and the reliability of human performance for the given process was 6.90E-01. The results of this paper highlight many factors such as equipment failure, inadequate training, and poor maintenance practices, as well as factors contributing to the risk of accidental system activation. By addressing these factors, the probability of CO2-fixed fire suppression system activation accidents can be significantly reduced.

A novel integrated methodology for human reliability assessment in hydrogen fuelling stations

Hydrogen fuel cell vehicles have proliferated in recent years, leading to a subsequent increase in hydrogen fuelling stations (HFSs). Operation and maintenance activities of an HFS prone to undesired events caused by human errors. Estimating and evaluating the risk associated with operators' performance can help to enhance the safety of such operations. The human error assessment and reduction technique (HEART) methodology has been widely used to assess the reliability of human performance. However, this technique is not entirely reliable since it depends on experts' experience and judgment, and the model's final outcome is subject to uncertainty. Besides, the HEART method ignores the dependencies of all the tasks required to assess human error probability (HEP). This paper presents a new integrated methodology for quantifying the impacts of different conditions on the reliability of operators' performances in HFSs. The proposed framework is constructed based on the Bayesian network (BN) for complimenting the application of HEART to deal with the lack of data and experts' judgment. Hence, it reduces the inaccuracy of HEP assessed by HEART by plotting it to a BN and considering the dependencies of all involved tasks. Subsequently, the best-worst method (BWM) is utilised to deal with the subjectivity of expert judgment. The integrated BN-BWM-HEART technique enhances the safety and reliability of the current operation and maintenance practices of an HFS. The results indicate that the integrated BN-BWM-HEART technique has the potential capacity to reduce the uncertainty associated with HEP estimation. So, the outcome of the developed methodology enhances the safety and reliability of operations and maintenance activities in an HFS.

A human reliability analysis for ship to ship LNG bunkering process under D-S evidence fusion HEART approach

LNG (Liquid Natural Gas) ship to ship bunkering process is quite a new concept for the maritime industry since the usage of LNG has been increasing worldwide. The LNG bunkering process poses a high risk due to human errors, while a minor error may be catastrophic. The expectation of the ship's crew is to carry out operations without any errors. Therefore, human reliability analysis (HRA) is paramount to improving operational safety during the ship to ship LNG bunkering process. In this context, this paper performs a systematic HRA under the D–S (Dempster-Shafer) evidence fusion-based HEART (human error assessment and reduction technique) approach. While the HEART quantifies human error for the tasks being performed, the extended D-S evidence fusion deals with the limitation of APOA (assessing the proportion of effect) calculation since it significantly relies on evaluating a single rater. The finding shows that human reliability for the ship to ship LNG bunkering process is 5.98E-01 and reasonable, but not at the desired level. The paper's outcomes will contribute to the utmost for LNG ship operators, safety inspectors, and ship owners to establish a safe and efficient ship to ship LNG bunkering process and minimise human error-based accidents.

Human reliability analysis in deep excavation projects using a fuzzy Bayesian HEART-5M integrated method: case of a residential tower in north Tehran

Objectives. Numerous labourers lose their lives or suffer from injuries and disabilities yearly due to the lack of safety enforcement in construction projects and accidents caused by excavation collapses. The identification and ranking of human errors have always been a central concern in civil engineering. Previous studies on excavation work and related risks have focused on retaining structure methods, while human errors may be a significant contributor to accidents and near misses. Methods. This study identified human errors in deep excavation projects using hierarchical task analysis (HTA) and a systematic human error reduction and prediction approach (SHERPA). Results. The fuzzy Bayesian human error assessment and reduction technique (HEART)-5M method was implemented to determine the human error probability (HEP) for all case-study tasks. Critical tasks were obtained as ‘drainage system execution’, ‘water and wastewater pipes’, ‘gas pipes’, ‘checking cracks in surrounding buildings’ and ‘checking soil slippage’ with probability levels of 0.46, 0.44, 0.44, 0.37 and 0.37, respectively. Finally, remedial measures were presented for crucial tasks. Conclusions. Six unbiased experts approved the model’s desirability. The suggested approach can serve as a valuable guide for all project stakeholders in identifying, evaluating and taking corrective actions in similar projects.

A Framework for Systematic Assessment of Human Error in Construction Sites – A Sustainable Approach

The construction industry is one of the most accident-susceptible sectors of the national economy and is characterized by a high rate of accidentality. The Human Error Assessment and Reduction Technique (HEART) is a generic method to identify human error. This technique uses generic task types and error producing conditions to calculate the probable human error. It is known that unsafe acts in the activity will also lead to unplanned events. Therefore, in this research, in addition to the existing factors, the probability of unsafe acts is also integrated. From the results, it is known that excavation (0.957), reinforcement erection for footing & column (0.631) and crane operation (0.269) are the tasks with a higher probability of human error. This can be minimized by frequent safety trainings to the workers and providing suitable personnel protective equipment (PPE) by the management. This proposed method may be applicable for all the workplaces, as it has a generic method to quantify human error with the task and error producing conditions. Knowledge of the circumstances of accidents will enable the formulation or modification of the labour law to be properly formulated, as well as the appropriate orientation of preventive measures and trainings in the field of occupational safety. All participants in the investment process: workers, construction site managers and supervisors, should be the recipients of these activities, who are also exposed to hazards and may suffer from accidents while performing their activities at a construction site. Parameters and the probable human error described by the authors allow for a comprehensive assessment of hazards and the probability of accident occurrences.

HEART Hybrid Methods for Assessing Human Reliability in Coal-Fired Thermal Power Plant Process

The assessment of human reliability is crucial in serious processes and operations, such as planned maintenance, unplanned maintenance, and troubleshooting in a coal-fired thermal power plant, as the nature of these processes poses significant threats. When the literature is examined, the evaluation of human reliability in any type of power plant, especially coal-fired thermal power plants, is limited. In order to fill this gap, we systematically assessed human reliability in an accident that occurred during a repair of a tube failure in a boiler in a coal-fired thermal power plant. The HEART (human error assessment and reduction technique) method was used in a hybrid way alongside the fuzzy AHP and SWARA (step weight assessment ratio analysis) methods. Although the HEART method is a practical, understandable, and easy-to-implement human reliability assessment method, the APOE (assessment of the proportion effect) value depends on the decision of a single decision maker. This study aimed to eliminate this deficiency and compare human error possibilities using HEART–fuzzy AHP and HEART–SWARA methods. This hybrid method can be used in the operation of all coal-fired thermal power plants and provides practical contributions to minimize human error.

Application of the HEART method to enhance patient safety in the intensive care unit.

The intensive care unit (ICU) is a complex, dynamic, high stress and time-sensitive place. While a variety of rules and regulations provided to reduce medication errors in recent years, many studies have emphasized that medication errors still happen. The purpose of this investigation is to predict, reveal and assess medication errors among surgical intensive care unit (SICU) nurses. This study was performed in one of the public hospitals in Shiraz, namely Shahid Faghihi hospital. The human error assessment and reduction technique (HEART) method was adopted to measure and assess medication errors in the ICU. Findings indicate that ICU nurses perform 27 main tasks and 125 sub-tasks. The results also showed that setting and using DC shock task has the highest human error probability value, and assessment of patients by a nutritionist has the lowest human error probability value. Medical errors are key challenges in the ICU. Therefore, alternative solutions to mitigate medication errors and enhance patient safety in the ICU are necessary. Although the technique can be used in healthcare; there is a need to localize the coefficients and definitions to achieve more accurate results and take appropriate controls. Employing experienced people and providing conditions that reduce the possibility of errors in nurses, increasing the number of staff, and developing specialized and simulated training were identified as the most important control strategies to reduce errors in nurses.

A practical application of the Hierarchical Task Analysis (HTA) and Human Error Assessment and Reduction Technique (HEART) to identify the major errors with mitigating actions taken after fire detection onboard passenger vessels

Fire onboard passenger ships is a major hazard not only for the personnel, passengers, and the environment, but also for the vessel itself. Therefore, the response actions carried out by crewmembers after a fire has been detected onboard a passenger vessel are of outermost importance. SAFEMODE project aims to promote contemporary safety thinking through a collection of carefully selected Human Factors (HFs) Fact Sheets that includes the most-known HFs techniques for accident investigations, to help accident investigators and safety managers within maritime organisations. Therefore, this paper proposes to apply two of the above-mentioned Fact Sheets, namely Hierarchical Task Analysis (HTA) and Human Error Assessment and Reduction Technique (HEART). Hence, this paper initially demonstrates how HTA can be applied to model the human response actions to a fire onboard a passenger vessel, and secondly, it utilises a systematic human error reduction and prediction approach, namely HEART, to predict and quantify which errors are likely to occur. Results from this paper reveal that six human response errors are most likely to occur, with a Human Error Probability of 0.16 according to the HEART analysis. Finally, this paper also suggests remedial measures to mitigate each error identified.

Fuzzy Logic in HEART and CREAM Methods to Assess Human Error and Find an Optimum Method Using a Hierarchical Fuzzy System: A Case Study in a Steel Factory

Numerous studies have been conducted to assess the role of human errors in accidents in different industries. Human reliability analysis (HRA) has drawn a great deal of attention among safety engineers and risk assessment analyzers. Despite all technical advances and the development of processes, damaging and catastrophic accidents still happen in many industries. Human Error Assessment and Reduction Technique (HEART) and Cognitive Reliability and Error Analysis Method (CREAM) methods were compared with the hierarchical fuzzy system in a steel industry to investigate the human error. This study was carried out in a rolling unit of the steel industry, which has four control rooms, three shifts, and a total of 46 technicians and operators. After observing the work process, reviewing the documents, and interviewing each of the operators, the worksheets of each research method were completed. CREAM and HEART methods were defined in the hierarchical fuzzy system and the necessary rules were analyzed. The findings of the study indicated that CREAM was more successful than HEART in showing a better capability to capture task interactions and dependencies as well as logical estimation of the HEP in the plant studied. Given the nature of the tasks in the studied plant and interactions and dependencies among tasks, it seems that CREAM is a better method in comparison with the HEART method to identify errors and calculate the HEP.

An extended HEART Dempster–Shafer evidence theory approach to assess human reliability for the gas freeing process on chemical tankers

Human reliability assessment is vital for most critical shipboard operations such as cargo loading, discharging, purging, gas freeing, etc. on chemical tanker ships since the nature of these processes poses significant threats. There are few human reliability studies particularly applied to shipboard operations in the maritime industry. To remedy this gap, the paper assesses human reliability systematically during the gas freeing process on a chemical tanker ship. To achieve this purpose, an extended HEART d-S (Dempster–Shafer) evidence theory approach is utilised. Although HEART (Human Error Assessment and Reduction Technique) presents a practical human reliability assessment tool, it heavily relies on the judgment of a single rater during APOE (assess proportion of effect). The paper adopts d-S evidence theory to remedy the aforementioned gap since it fuses raters’ opinions. The first novelty of the proposed hybrid method is the use of customized task analysis for shipboard applications within a second-generation HEART d-S evidence method in the maritime industry. Besides its theoretical background, the paper provides practical contributions to maritime safety professionals, chemical tanker ship owners, and safety inspectors to enhance their operational safety and to minimize the probability of human error during the gas freeing process on board chemical tanker ships.

Estimating human error probability in transporting steel cargo with bulk carriers using a hybrid approach

Maritime operations include potential human-made hazards. For this reason, evaluating human-made hazards for cost-effective ship management is of vital importance in the maritime industry. From past to present, researchers have attempted to offer preventive approaches to minimise human-made hazards. In this context, the present article proposes a hybrid approach through the integration of the Delphi, Analytic Hierarchy Process (AHP) and Human Error Assessment and Reduction Technique (HEART) methods. With this approach, human-made claims occurring during the handling and transport of steel cargo in bulk carriers were analysed. The outputs of the present article contribute to the improvement of overall safety levels of steel cargo and bulk carriers by considering the potential hazards in risk management.

A conceptual framework for minimizing construction site accidents using Task-Personnel Nexus Matrix

Majority of the construction site accidents are due to the influence of human factors such as negligence, lack of awareness and lack of training. This work proposes a conceptual framework for minimizing construction site accidents using Task-Personnel Nexus Matrix (TPM) which selects the right worker for a particular task. Each construction site task is evaluated for its risk and the probability of human error associated with the task using Hazard Identification and Risk Assessment (HIRA) and Human Error Assessment and Reduction Technique (HEART) techniques respectively from which a combined metric of Risk cum Human Error (RHE) is proposed to be evaluated. Kohonen algorithm is proposed to classify the workers database into two or more clusters, each of which is trained using the Back Propagation Neural Network (BNN) to predict the performance of the worker knowing his basic characteristic. The high performer is proposed to be assigned to higher risk tasks which correspond to a higher value of RHE. It is seen that the proposed method is highly promising in reducing the construction site accidents and is easy to implement by predicting, evaluating and assigning the right person for a right job in the construction site.

Hybrid Human Error Assessment Approach for Critical Aircraft Maintenance Practice in the Training Aircraft

ABSTRACT Objective In this study, a hybrid human error assessment (HHEA) approach is proposed to determine the probability of aircraft maintenance technician (AMT) error occurring during aircraft repair. Background The human error assessment and reduction technique (HEART) is the first-generation empirical human reliability analysis (HRA) approach. Although this technique is used in several industries, AMTs’ errors have not been assessed with HEART and interactions of error-producing conditions (EPCs) have not been considered in calculating the probability of AMTs’ errors. Method HHEA is proposed to reduce the subjectivity of experts’ judgments by calculating assessed proportion of affect of each EPC on human error probability (HEP) integrating HEART and the analytic network process (ANP) method. The proposed model has been applied in the maintenance of the elevator, which is one of the most important primary control surfaces for the Cessna 172 Series aircraft type. Results The HEP values of 3 subtasks are found to be higher than the average HEP value. These subtasks have the highest probability of human error due to time pressure, poor environmental conditions, and being a repetitive task. Conclusion This study could guide other aircraft maintenance organizations using this integration of human reliability assessment approach for critical maintenance practices to enhance flight safety and minimize human error.

A hybrid evaluation method for human error probability by using extended DEMATEL with Z-numbers: A case of cargo loading operation

Human error probability (HEP) evaluation and prediction is one of the most significant tasks to enhance human reliability in marine industry. Among various kinds of HEP evaluation techniques, the Human Error Assessment and Reduction Technique (HEART) technique is regarded as an effective and empirical tool that has been widely adopted in various fields. However, current HEART techniques are insufficient to address HEP evaluation problem in which the self-assurance of expert's judgment and inter-dependencies between Error-producing conditions (EPCs) are considered. Therefore, the purpose of this paper is to develop a hybrid HEART framework (H-HEART-F) to address this problem by integrating Z-numbers and the decision-making trial and evaluation laboratory (DEMATEL) method. First, the Z-numbers are introduced to model the uncertainty and self-assurance of evaluation information from various experts. Then, the Z-number power weighted average (Z-PWA) operator is proposed to aggregate the individual evaluation information into a group direct influenced matrix. Next, an extended DEMATEL method based on possibility degree measure is constructed to determine the proportion of effect of each EPC by considering the self-assurance of expert's judgment and inter-dependencies between EPCs. Finally, the HEP estimation for the cargo loading operation in oil or chemical tanker ship is presented to demonstrate the availability and feasibility of the H-HEART-F. After that, the sensitivity analysis and comparison study are conducted to further illustrate the reasonableness and effectiveness of the proposed method.

Identification and evaluation of maintenance error in catalyst replacement using the HEART technique under a fuzzy environment

Objectives. A necessity for this study was felt in the catalyst replacement process as a maintenance operation, because some fatal incidents have occurred due to human error in process industries during catalyst replacement operation. Identification and evaluation of human error is essential in predicting and reducing accidents in maintenance operation. Methods. The human error assessment and reduction technique (HEART) as a human reliability analysis was applied in this study. Because the HEART method uses expert judgment, it is possible to make a bias in the assessment. Fuzzification and aggregation opinions of a heterogeneous expert group in a trapezoidal fuzzy set were used to mitigate this deficiency. Results. Evaluation results showed that the subtask ‘Entering the reactor’ with human error probability (HEP) of 9.2E–1 and the subtask ‘Reduce temperature while reducing feed’ with HEP 1.3E–3 had the highest and lowest chance of human error, respectively. Conclusions. In order to reduce the likelihood of human error, it is necessary to take appropriate actions based on the task-specific error producing condition (EPC).

Ranking of occupational health and safety risks by a multi-criteria perspective: Inclusion of human factors and application of VIKOR

Nowadays, the Occupational Health and Safety (OHS) is more and more recognized as a crucial process to be properly managed and continuously improved by every organization. Primarily addressed to prevent workers’ injuries and diseases, it positively impacts on productivity, competitiveness and reputation as well as it contributes to cost savings in general. OHS management is grounded upon the risk assessment results, on the basis of which defining corrective measures to be taken to reduce risks to acceptable values. In this regard, the paper proposes a Multi-Criteria Decision Making (MCDM) based methodology addressed to the occupational risks prioritization. In order to overcome the shortcomings of the traditional risk matrix, the new methodology considers three evaluation criteria differently weighted by the Analytic Hierarchy Process (AHP) method. Among criteria, one specifically refers to the contribution of human factors to the occurrence of accidents, and a combination of Human Error Assessment and Reduction Technique (HEART) and Standardized Plant Analysis Risk-Human (SPAR-H) techniques is used to this aim. Afterwards, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method is applied to rank risks. The proposed approach is implemented in a Sicilian manufacturing company that produces and commercializes wooden products, together with the sale of outdoor furniture. The comparison of the obtained results with the ones arising from previous risk analyses performed by the company highlights the higher ability of the proposed methodology to differentiate risks.

Implementation of Heart and Dematel Integration to Steam Boiler Working Process

Human Error Assessment and Reduction Technique (HEART) is a practical and powerful approach to prioritize errors related to human actions, based on probabilities. HEART can determine error producing conditions (EPCs) which cause human errors for different processes including main duties (MDs) and sub-duties (SDs). HEART can be applied quickly for any process where human reliability is important. In this study, HEART and advanced version of Decision Making Trial and Evaluation Laboratory (AV-DEMATEL) integration proposed by Can and Delice in 2018 was performed for evaluating human related errors in steam boiler working process. In this way, the interactions between MDs, SDs and EPCs in a steam boiler working process were considered to compute process error probability (PEP). Additionally, the applicability of the proposed approach by Can and Delice (2018) was demonstrated again.

A Hybrid Methodology for Human Reliability Assessment in Maritime Cargo Accidents

The maritime cargo shipment is always looking for implementing new safety measures to reduce the cargo accident rates. However, it is challenging to find the root cause that led to a specific cargo accident. The accidents result from a complex chain of events, where there is usually more than one factor solely responsible for maritime cargo accidents. The present contribution aims to find the causal factor of the accidents and predict human error probability after the accidents using the hybrid methodology. The hybrid methodology that uses this study to assess human error of maritime cargo accidents is Human Error Assessment and Reduction Technique (HEART) – 4M and TOPSIS with Technique for Risk Perception. The HEART methodology assumes that any predicted reliability of task performance may be modified according to the presence of identified Error Promoting Conditions (EPCs). A technique for Risk Perception decomposes a task into sub-task steps for which quantification data are provided. The corresponding results show that the most common situation that maritime cargo accidents occurred due to the man factor is during the loading and unloading process.