A THERP/ATHEANA Analysis of the Latent Operator Error in Leaving EFW Valves Closed in the TMI-2 Accident

This paper aims at performing a human reliability analysis using THERP (Technique for Human Error Prediction) and ATHEANA (Technique for Human Error Analysis) to develop a qualitative and quantitative analysis of the latent operator error in leaving EFW (emergency feed-water) valves closed in the TMI-2 accident. The accident analysis has revealed a series of unsafe actions that resulted in permanent loss of the unit. The integration between THERP and ATHEANA is developed in a way such as to allow a better understanding of the influence of operational context on human errors. This integration provides also, as a result, an intermediate method with the following features: (1) it allows the analysis of the action arising from the plant operational context upon the operator (as in ATHEANA), (2) it determines, as a consequence from the prior analysis, the aspects that most influence the context, and (3) it allows the change of these aspects into factors that adjust human error probabilities (as in THERP). This integration provides a more realistic and comprehensive modeling of accident sequences by considering preaccidental and postaccidental contexts, which, in turn, can contribute to more realistic PSA (Probabilistic Safety Assessment) evaluations and decision making

Development of a Team Human Reliability Tool (ROCCI)

Human Reliability Assessments (HRA) have been developed so designers and users can understand how likely it is for a human to make an error when using a product or system in the workplace. This is called the reliability of the product. Approximately twenty-six techniques exist to assess the reliability of an individual human in a process. However, often a team of people interact within a system and not just one individual on their own. Hence a new generation of HRAs is needed to assess the effects of teamwork on reliability. This EPSRC CASE studentship, supported by BAE systems, develops a prototype, which enables a designer to quantify and answer to the question: “If I allocate this team to execute that task in System X, how likely is it that they will succeed?” This prototype assumes that a process can be defined in the form of a flow diagram and that roles can be allocated to execute it. Then, using one of those twenty-six techniques, individual reliabilities can be calculated. These are then modulated, by considering how the team interaction affects the three core elements of Trust, Communication and Decision Making Power Distance. This creates an ‘interactive reliability’ factor for each individual in the team. These individual reliability factors are combined according to the team architecture for the process in order to determine the overall team reliability factor. The methods of development include: stakeholder interviews; the evolution of requirements specification; sensitivity analysis; and a stakeholder review of the tool. The information from these analyses produced a model about team interaction and the requirements for the new tool together with statements and algorithms that need to be used in the new tool: ROCCI. This technique is useful for use in the early stages of the design process. The successful prototype can be extended into applications for operations and used to assess and adapt products and systems, which involve teams

Multi-criteria decision methods to support the maintenance management of complex systems

[ES] Esta tesis doctoral propone el uso de métodos de toma de decisiones multi-criterio (MCDM, por sus iniciales en inglés) como herramienta estratégica para apoyar la gestión del mantenimiento de sistemas complejos. El desarrollo de esta tesis doctoral se enmarca dentro de un acuerdo de cotutela entre la Università degli Studi di Palermo (UNIPA) y la Universitat Politècnica de València (UPV), dentro de sus respectivos programas de doctorado en 'Ingeniería de Innovación Tecnológica' y 'Matemáticas'. Estos programas están estrechamente vinculados a través del tópico MCDM, ya que proporciona herramientas cruciales para gestionar el mantenimiento de sistemas complejos reales utilizando análisis matemáticos serios. El propósito de esta sinergia es tener en cuenta de forma sólida la incertidumbre al atribuir evaluaciones subjetivas, recopilar y sintetizar juicios atribuidos por varios responsables de la toma de decisiones, y tratar con conjuntos grandes de esos elementos. El tema principal del presente trabajo de doctorado es el gestionamiento de las actividades de mantenimiento para aumentar los niveles de innovación tecnológica y el rendimiento de los sistemas complejos. Cualquier sistema puede ser considerado objeto de estudio, incluidos los sistemas de producción y los de prestación de servicios, entre otros, mediante la evaluación de sus contextos reales. Esta tesis doctoral propone afrontar la gestión del mantenimiento a través del desarrollo de tres líneas principales de investigación estrechamente vinculadas. ¿ La primera es el núcleo, e ilustra la mayoría de los aspectos metodológicos de la tesis. Se refiere al uso de métodos MCDM para apoyar decisiones estratégicas de mantenimiento, y para hacer frente a la incertidumbre que afecta a los datos/evaluaciones, incluso cuando están involucrados varios responsables (expertos en mantenimiento) en la toma de decisiones. ¿ La segunda línea desarrolla análisis de fiabilidad para sistemas complejos reales (también en términos de fiabilidad humana) sobre cuya base se debe implementar cualquier actividad de mantenimiento. Estos análisis consideran la configuración de fiabilidad de los componentes del sistema en estudio y las características específicas del entorno operativo. ¿ La tercera línea de investigación aborda aspectos metodológicos importantes de la gestión de mantenimiento y enfatiza la necesidad de monitorizar el funcionamiento de las actividades de mantenimiento y de evaluar su efectividad utilizando indicadores adecuados. Se ha elaborado una amplia gama de casos de estudio del mundo real para evaluar la eficacia de los métodos MCDM en el mantenimiento y así probar la utilidad del enfoque propuesto.[CA] Aquesta tesi doctoral proposa l'ús de mètodes de presa de decisions multi-criteri (MCDM, per les seves inicials en anglès) com a eina estratègica per donar suport a la gestió del manteniment de sistemes complexos. El desenvolupament d'aquesta tesi doctoral s'emmarca dins d'un acord de cotutela entre la Università degli Studi di Palermo (UNIPA) i la Universitat Politècnica de València (UPV), dins dels seus respectius programes de doctorat en 'Enginyeria d'Innovació Tecnològica' i ' Matemàtiques '. Aquests programes estan estretament vinculats a través del tòpic MCDM, ja que proporciona eines crucials per gestionar el manteniment de sistemes complexos reals utilitzant anàlisis matemàtics profunds. El propòsit d'aquesta sinergia és tenir en compte de forma sòlida la incertesa en atribuir avaluacions subjectius, recopilar i sintetitzar judicis atribuïts per diversos responsables de la presa de decisions, i tractar amb conjunts grans d'aquests elements en els problemes plantejats. El tema principal del present treball de doctorat es la gestió de les activitats de manteniment per augmentar els nivells d'innovació tecnològica i el rendiment dels sistemes complexos. Qualsevol sistema pot ser considerat objecte d'estudi, inclosos els sistemes de producció i els de prestació de serveis, entre d'altres, mitjançant l'avaluació dels seus contextos reals. Aquesta tesi doctoral proposa afrontar la gestió del manteniment mitjançant el desenvolupament de tres línies principals d'investigació estretament vinculades. ¿ La primera és el nucli, i il·lustra la majoria dels aspectes metodològics de la tesi. Es refereix a l'ús de mètodes MCDM per donar suport a decisions estratègiques de manteniment, i per fer front a la incertesa que afecta les dades/avaluacions, fins i tot quan estan involucrats diversos responsables (experts en manteniment) en la presa de decisions. ¿ La segona línia desenvolupa anàlisis de fiabilitat per a sistemes complexos reals (també en termes de fiabilitat humana) sobre la qual base s'ha d'implementar qualsevol activitat de manteniment. Aquestes anàlisis consideren la configuració de fiabilitat dels components del sistema en estudi i les característiques específiques de l'entorn operatiu. ¿ La tercera línia d'investigació aborda aspectes metodològics importants de la gestió de manteniment i emfatitza la necessitat de monitoritzar el funcionament de les activitats de manteniment i d'avaluar la seva efectivitat utilitzant indicadors adequats. S'ha elaborat una àmplia gamma de casos d'estudi del món real per avaluar l'eficàcia dels mètodes MCDM en el manteniment i així provar la utilitat de l'enfocament proposat.[EN] This doctoral thesis proposes using multi-criteria decision making (MCDM) methods as a strategic tool to support maintenance management of complex systems. The development of this doctoral thesis is framed within a cotutelle (co-tutoring) agreement between the Università degli Studi di Palermo (UNIPA) and the Universitat Politècnica de València (UPV), within their respective programmes of doctorates in 'Technological Innovation Engineering' and 'Mathematics'. Regarding this thesis, these programmes are closely linked through the topic of MCDM, providing crucial tools to manage maintenance of real complex systems by applying in-depth mathematical analyses. The purpose of this connection is to robustly take into account uncertainty in attributing subjective evaluations, collecting and synthetizing judgments attributed by various decision makers, and dealing with large sets of elements characterising the faced issue. The main topic of the present doctoral work is the management of maintenance activities to increase the levels of technological innovation and performance of the analysed complex systems. All kinds of systems can be considered as objects of study, including production systems and service delivery systems, among others, by evaluating their real contexts. Thus, this doctoral thesis proposes facing maintenance management through the development of three tightly linked main research lines. ¿ The first is the core and illustrates most of the methodological aspects of the thesis. It refers to the use of MCDM methods for supporting strategic maintenance decisions, and dealing with uncertainty affecting data/evaluations even when several decision makers are involved (experts in maintenance). ¿ The second line develops reliability analyses for real complex systems (also in terms of human reliability analysis) on the basis of which any maintenance activity must be implemented. These analyses are approached by considering the reliability configuration of both the components belonging to the system under study and the specific features of the operational environment. ¿ The third research line focuses on important methodological aspects to support maintenance management, and emphasises the need to monitor the performance of maintenance activities and evaluate their effectiveness using suitable indicators. A wide range of real real-world case studies has been faced to evaluate the effectiveness of MCDM methods in maintenance and then prove the usefulness of the proposed approach.Carpitella, S. (2019). Multi-criteria decision methods to support the maintenance management of complex systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11911

Conceito, classificação e quantificação da fiabilidade humana na relação homem-máquina

O estudo da fiabilidade é um tema imprescindível para qualquer sistema homem-máquina que pretenda adquirir os melhores índices de segurança e rendimento. Se a fiabilidade dos equipamentos é um campo onde já muito foi estudado, debatido e provado no terreno e onde os novos desenvolvimentos irão apenas acontecer devido aos avanços tecnológicos que permitam melhor predizer as potenciais falhas dos equipamentos, já a fiabilidade humana é uma área de estudo relativamente nova e onde muito há a desenvolver, particularmente devido ás características inatas do ser humano. Ao contrário da evolução tecnológica, onde a melhoria dos materiais e processos obedece a um aperfeiçoamento relativamente gradual e crescente e que pode ser avaliado e melhorado, o comportamento e o aperfeiçoamento do ser humano apresentam dificuldades e complexidades variadas porque o mesmo é único e sofre influências adversas e imprevisíveis do meio em que vive, as quais têm influência directa no seu comportamento. Assim este trabalho académico propõe-se estudar e identificar as principais causas de erros humanos, através do conhecimento adquirido acerca dos processos cognitivos mais comuns do Homem, bem como definir os conceitos e procedimentos adjacentes à fiabilidade humana e às suas principais ferramentas de avaliação

Advanced system engineering approaches to dynamic modelling of human factors and system safety in sociotechnical systems

Sociotechnical systems (STSs) indicate complex operational processes composed of interactive and dependent social elements, organizational and human activities. This research work seeks to fill some important knowledge gaps in system safety performance and human factors analysis using in STSs. First, an in-depth critical analysis is conducted to explore state-of-the-art findings, needs, gaps, key challenges, and research opportunities in human reliability and factors analysis (HR&FA). Accordingly, a risk model is developed to capture the dynamic nature of different systems failures and integrated them into system safety barriers under uncertainty as per Safety-I paradigm. This is followed by proposing a novel dynamic human-factor risk model tailored for assessing system safety in STSs based on Safety-II concepts. This work is extended to further explore system safety using Performance Shaping Factors (PSFs) by proposing a systematic approach to identify PSFs and quantify their importance level and influence on the performance of sociotechnical systems’ functions. Finally, a systematic review is conducted to provide a holistic profile of HR&FA in complex STSs with a deep focus on revealing the contribution of artificial intelligence and expert systems over HR&FA in complex systems. The findings reveal that proposed models can effectively address critical challenges associated with system safety and human factors quantification. It also trues about uncertainty characterization using the proposed models. Furthermore, the proposed advanced probabilistic model can better model evolving dependencies among system safety performance factors. It revealed the critical safety investment factors among different sociotechnical elements and contributing factors. This helps to effectively allocate safety countermeasures to improve resilience and system safety performance. This research work would help better understand, analyze, and improve the system safety and human factors performance in complex sociotechnical systems

Human Reliability assessment in oil tanker operations

This research is carried out to improve Human Reliability Analysis (HRA) in oil tanker operations in general, to extend and enhance in specific Cognitive Reliability and Error Analysis Method (CREAM), with the aim of reducing human error and thus subsequently preventing oil tanker spills. It is concentrated on oil tanker operations to address the limitation of availability of human reliability data in the maritime domain. The continual occurrence of oil tanker spills, which was substantiated with analysis of historical data of oil tanker incidents/accidents from 1970 to 2008, provides a judicious reason to conduct this research. The critical review of Formal Safety Assessment (FSA) and HRA results in the development of a conceptual framework of HRA facilitating FSA and incorporating Human Organisational Factors (HOF), which addresses the shortcomings of the generic HRA and FSA methodologies that exist independently in the management of oil tankers to prevent oil spills. The CREAM is reviewed due to its prominent use in identifying the root causes of human error. However, its inability of providing solutions to an incident/accident investigation and robust quantification of human reliability features stimulates the development of an advanced CREAM and a human reliability quantification model using a combined Analytic Hierarchical Process (AHP) and fuzzy logic approach in this research. In addition to facilitating identification of the root causes of human error, the advanced CREAM also provides the solutions to a quantification model, which enables the development of HRA data in the maritime domain. Furthermore, lack of CREAM studies on relationships among Common Performance Conditions (CPCs) is addressed by proposing a Decision Making Trial and Evaluation Laboratory (DEMATEL) model, which allows for a comprehensive understanding of relationships and interdependencies among the CPCs. The model could also be used toappreciate and assimilate the relationships and interdependencies among human factor variables involved in other transportation systems and industrial fields. Finally, the research is concluded with an integrated AHP and fuzzy Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) model for determining the selection of an appropriate risk control option (RCO) while performing an incident/accident investigation by taking subjective judgments of decision makers into consideration. This research as a pioneer work in developing and applying advanced techniques to improve the generic CREAM in oil tanker operations establishes a foundation for future effort to improve the use of CREAM in other industries. The techniques developed can also be tailored to investigate and deal with an incident/accident effectively, resulting in the reduction of human error within the system management of any organisatio

Quantitative human reliability assessment in Marine Engineering Operations

Marine engineering operations rely substantially on high degrees of automation and supervisory control. This brings new opportunities as well as the threat of erroneous human actions, which account for 80-90% of marine incidents and accidents. In this respect, shipping environments are extremely vulnerable. As a result, decision makers and stakeholders have zero tolerance for accidents and environmental damage, and require high transparency on safety issues. The aim of this research is to develop a novel quantitative Human Reliability Assessment (HRA) methodology using the Cognitive Reliability and Error Analysis Method (CREAM) in the maritime industry. This work will facilitate risk assessment of human action and its applications in marine engineering operations. The CREAM model demonstrates the dynamic impact of a context on human performance reliability through Contextual Control Model controlling modes (COCOM-CMs). CREAM human action analysis can be carried out through the core functionality of a method, a classification scheme and a cognitive model. However, CREAM has exposed certain practical limitations in its applications especially in the maritime industry, including the large interval presentation of Human Failure Probability (HFP) values and the lack of organisational factors in its classification scheme. All of these limitations stimulate the development of advanced techniques in CREAM as well as illustrate the significant gap between industrial needs and academic research. To address the above need, four phases of research study are proposed. In the first phase, the adequacy of organisation, one of the key Common Performance Conditions (CPCs) in CREAM, is expanded by identifying the associated Performance Influencing Factors (PIFs) and sub-PIFs in a Bayesian Network (BN) for realising the rational quantification of its assessment. In the second phase, the uncertainty treatment methods' BN, Fuzzy Rule Base (FRB) , Fuzzy Set (FS) theory are used to develop new models and techniques' that enable users to quantify HFP and facilitate the identification of possible initiating events or root causes of erroneous human action in marine engineering operations. In the third phase, the uncertainty treatment method's Evidential Reasoning (ER) is used in correlation with the second phase's developed new models and techniques to produce the solutions to conducting quantitative HRA in conditions in which data is unavailable, incomplete or ill-defined. In the fourth phase, the CREAM's prospective assessment and retrospective analysis models are integrated by using the established Multiple Criteria Decision Making (MCDM) method based on, the combination of Analytical Hierarchical Process (AHP), entropy analysis and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). These enable Decision Makers (DMs) to select the best developed Risk Control Option (RCO) in reducing HFP values. The developed methodology addresses human actions in marine engineering operations with the significant potential of reducing HFP, promoting safety culture and facilitating the current Safety Management System (SMS) and maritime regulative frameworks. Consequently, the resilience of marine engineering operations can be further strengthened and appreciated by industrial stakeholders through addressing the requirements of more safety management attention at all levels. Finally, several real case studies are investigated to show end users tangible benefits of the developed models, such as the reduction of the HFPs and optimisation of risk control resources, while validating the algorithms, models, and methods developed in this thesis