Reliability Engineering Techniques Applied to the Human Failure Analysis Process

2022 ◽  
pp. 162-179
Author(s):  
Vicente González-Prida ◽  
Carlos Parra ◽  
Adolfo Crespo ◽  
Fredy A. Kristjanpoller ◽  
Pablo Viveros Gunckel

Human reliability and human error are factors that are present in all areas: industrial, economic, social, etc. All these areas require to a greater or lesser extent a physical and mental effort to satisfy their own needs, those of others, or established requirements that, depending on the circumstances and the nature of the person, can lead to errors. Certainly, it is not possible to find a single human reliability method that can meet all the expectations and technical demands related to the analysis of human errors. However, it is important to note that the orientation of all human reliability methods is focused on the study and analysis of the risk factor (frequency by consequences). In other words, as can be observed throughout this chapter, all human reliability methodologies seek to help us reduce the uncertainty in the process of evaluating the frequencies of unforeseen events (human errors) and the consequences that such human errors can bring to safety, the environment, and the operations within the framework of an industrial production process.

2011 ◽  
Vol 97-98 ◽  
pp. 825-830 ◽  
Author(s):  
Yong Tao Xi ◽  
Chong Guo

Safety is the eternal theme in shipping industry. Research shows that human error is the main reason of maritime accidents. Therefore, it is very necessary to research marine human errors, to discuss the contexts which caused human errors and how the contexts effect human behavior. Based on the detailed investigation of human errors in collision avoidance behavior which is the most key mission in navigation and the Performance Shaping Factors (PSFs), human reliability of mariners in collision avoidance was analyzed by using the integration of APJE and SLIM. Result shows that this combined method is effective and can be used for the research of maritime human reliability.


Author(s):  
Oladokun Sulaiman Olanrewaju

The traditional approach to the study of human factors in the maritime field involves the analysis of accidents without considering human factor reliability analysis. The main approaches being used to analyze human errors are statistical approach and probability theory approach. Another suitable approach to the study of human factors in the maritime industry is the quasi-experimental field study where variations in performance (for example attention) can be observed as a function of natural variations in performance shaping factors. This chapter analyzes result of modelling for human error and human reliability emanating from the use of technology on board ship navigation in coastal water areas by using qualitative and quantitative tools. Accident reports from marine department are used as empirical material for quantitative analysis. The literature on safety is based on common themes of accidents, the influence of human error resulting from technology usage design, accident reports from MAIB, and interventions information are used for qualitative assessment. Human reliability assessment involves analysis of accidents in waterways emanating from human-technology factors. The chapter reports enhancement requirement of the methodological issues with previous research study, monitoring, and deduces recommendations for technology modification of the human factors necessary to improve maritime safety performance. The result presented can contribute to rule making and safety management leading to the development of guidelines and standards for human reliability risk management for ships navigating within inland and coastal waters.


Author(s):  
Marilia A. Ramos ◽  
Alex Almeida ◽  
Marcelo R. Martins

Abstract Several incidents in the offshore oil and gas industry have human errors among core events in incident sequence. Nonetheless, human error probabilities are frequently neglected by offshore risk estimation. Human Reliability Analysis (HRA) allows human failures to be assessed both qualitatively and quantitatively. In the petroleum industry, HRA is usually applied using generic methods developed for other types of operation. Yet, those may not sufficiently represent the particularities of the oil and gas industry. Phoenix is a model-based HRA method, designed to address limitations of other HRA methods. Its qualitative framework consists of three layers of analysis composed by a Crew Response Tree, a human response model, and a causal model. This paper applies a version of Phoenix, the Phoenix for Petroleum Refining Operations (Phoenix-PRO), to perform a qualitative assessment of human errors in the CDSM explosion. The CDSM was a FPSO designed to produce natural gas and oil to Petrobras in Brazil. On 2015 an explosion occurred leading to nine fatalities. Analyses of this accident have indicated a strong contribution of human errors. In addition to the application of the method, this paper discusses its suitability for offshore operations HRA analyses.


2011 ◽  
Vol 225-226 ◽  
pp. 395-398 ◽  
Author(s):  
Dan Dan Li ◽  
Lei Li

Now human error has caused lots of accidents of dam break, but there is no direct method to calculate the probability of human error in dam risk analysis. So the paper invite the suggestion of introducing the human reliability into dam risk analysis, which can perfect the dam risk theory. It used improved HCR(Human Cognitive Reliability) method to calculate human reliability of dam risk, but the concrete parameters need further research combined with engineering practice.


Author(s):  
B. J. KIM ◽  
RAM R. BISHU

Human error is regarded as a critical factor in catastrophic accidents such as disasters at nuclear power plants, air plane crashes, or derailed trains. Several taxonomies for human errors and methodologies for human reliability analysis (HRA) have been proposed in the literature. Generally, human errors have been modeled on the basis of probabilistic concepts with or without the consideration of cognitive aspects of human behaviors. Modeling of human errors through probabilistic approaches has shown a limitation on quantification of qualitative aspects of human errors and complexity of attributes from circumstances involved. The purpose of this paper is to investigate the methodologies for human reliability analysis and introduce a fuzzy logic approach to the evaluation of human interacting system's reliability. Fuzzy approach could be used to estimate human error effects under ambiguous interacting environments and assist in the design of error free work environments.


2019 ◽  
Vol 8 (4) ◽  
pp. 12830-12833

In India agriculture and its practices plays the vital role, since more number of people are employed in that process. The agricultural process goes on with the sowing, maintenance and yield. The yield of the crop purely depends on the season, maintenance and the nutrient content available in the soil. Soil nutrient analysis has been made before sowing period with the help of soil testing laboratory, based on the laboratory results and the selected crops. End of the analysis process the fertilizer suggestion would be given to the farmer. In the existing system the analysis process is done manually and farmers would be given direct suggestion about the fertilizer. Since the process is repetitive it consumes more time and there may be chance of human error which may majorly affect the yield. The main aim of the proposed work is to design an Automated Fertilizer Suggestion (AFS) application to give effective suggestions to farmers about the fertilizers with respect to crops based on the soil test results. Our proposed application reduces the time, controls the human errors, avoids the over dumping of fertilizer in the soil and improves the yield.


Author(s):  
Romney B. Duffey ◽  
John W. Saull

Reactor safety and risk are dominated by the potential and major contribution for human error in the design, operation, control, management, regulation and maintenance of the plant, and hence to all accidents. Given the possibility of accidents and errors, now we need to determine the outcome (error) probability, or the chance of failure. Conventionally, reliability engineering is associated with the failure rate of components, or systems, or mechanisms, not of human beings in and interacting with a technological system. The probability of failure requires a prior knowledge of the total number of outcomes, which for any predictive purposes we do not know or have. Analysis of failure rates due to human error and the rate of learning allow a new determination of the dynamic human error rate in technological systems, consistent with and derived from the available world data. The basis for the analysis is the “learning hypothesis” that humans learn from experience, and consequently the accumulated experience defines the failure rate. A new “best” equation has been derived for the human error, outcome or failure rate, which allows for calculation and prediction of the probability of human error. We also provide comparisons to the empirical Weibull parameter fitting used in and by conventional reliability engineering and probabilistic safety analysis methods. These new analyses show that arbitrary Weibull fitting parameters and typical empirical hazard function techniques cannot be used to predict the dynamics of human errors and outcomes in the presence of learning. Comparisons of these new insights show agreement with human error data from the world’s commercial airlines, the two shuttle failures, and from nuclear plant operator actions and transient control behavior observed in transients in both plants and simulators. The results demonstrate that the human error probability (HEP) is dynamic, and that it may be predicted using the learning hypothesis and the minimum failure rate, and can be utilized for probabilistic risk analysis purposes.


Author(s):  
Danilo T. M. P. Abreu ◽  
Marcos C. Maturana ◽  
Marcelo R. Martins ◽  
Siegberto R. Schenk

Abstract During a ship life cycle, one of the most critical phases in terms of safety refers to harbor maneuvers, which take place in restricted and congested waters, leading to higher collision and grounding risks in comparison to open sea navigation. In this scenario, a single accident may stop the harbor’s traffic as well as incur into patrimonial damage, environmental pollution, human casualties and reputation losses. In order to support the vessel’s captain during the maneuver, local experienced maritime pilots stay on board coordinating the ship navigation while in restricted waters. Because of their shorter relative duration, harbor maneuvers accidents are more probable to occur due to human errors — reinforced by the inherent surrounding difficulties —, rather than machinery failures, for instance. The human errors are object of study of the human reliability analysis (HRA). Aiming to assess the main factors contributing to human errors in pilot-assisted harbor ship maneuvers, this work proposes a Bayesian network model for HRA, supported by a prospective human performance model for quantification. Similar works focus mainly on open sea navigation and collision accidents, which do not reflect the strict conditions found on port areas. Additionally, most of the models are highly dependent on expert’s opinion for quantification. Therefore, the novelty of this work resides into two aspects: a) incorporation of harbor specific conditions for maritime navigation HRA, including the performance of ship’s crew and maritime pilots; and b) the use of a prospective human performance model as an alternative to expert’s opinion for quantification purposes. To illustrate the usage of the proposed methodology, this paper presents an analysis of the route keeping task along waterways, starting from the quantification of human error probabilities (HEP) and including the ranking of the main external factors that contribute to the HEP.


2021 ◽  
Vol 11 (2) ◽  
pp. 749
Author(s):  
Yaniel Torres ◽  
Sylvie Nadeau ◽  
Kurt Landau

Manual assembly operations are sensitive to human errors that can diminish the quality of final products. The paper shows an application of human reliability analysis in a realistic manufacturing context to identify where and why manual assembly errors occur. The techniques SHERPA and HEART were used to perform the analysis of human reliability. Three critical tasks were selected for analysis based on quality records: (1) installation of three types of brackets using fasteners, (2) fixation of a data cable to the assembly structure using cushioned loop clamps and (3) installation of cap covers to protect inlets. The identified error modes with SHERPA were: 36 action errors, nine selection errors, eight information retrieval errors and six checking errors. According to HEART, the highest human error probabilities were associated with assembly parts sensitive to geometry-related errors (brackets and cushioned loop clamps). The study showed that perceptually engaging assembly instructions seem to offer the highest potential for error reduction and performance improvement. Other identified areas of action were the improvement of the inspection process and workers’ provision with better tracking and better feedback. Implementation of assembly guidance systems could potentially benefit worker’s performance and decrease assembly errors.


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