Reducing Uncertainty in PHM by Accounting for Human Factors - A Case Study in the Biopharmaceutical Industry

The ultimate goal of prognostics within Through-life Engineering Services (TES) is to accurately predict the remaining useful life (RUL) of components. Prognostic frameworks inherently presume that there is predictability in the failure rate of the system, i.e. a system experiencing exclusively stochastic failure events cannot, by definition, be predictable. Prediction model uncertainties must be bound in some logical way. Therefore, to achieve an accurate prognostic model, uncertainty must first be reduced through the identification and elimination of the root causes of random failure events. This research investigates human error in maintenance activities as a major cause of random failure events, using a case study from the biopharmaceutical industry. Elastomer failures remain the number one contamination risk in this industry and data shows unexplained variability in the lifetime of real components when compared to accelerated lifetime testing in the lab environment. Technician error during installation and maintenance activities of elastomers is one possible cause for this and this research explores how these errors can be eliminated, reduced, or accounted for within the reliability modeling process. The initial approach followed was to improve technician training in order to reduce errors and thereby reduce the variability of random failure events. Subsequent data has shown an improvement in key metrics with failures now more closely matching data from lab testing. However, there is scope for further improvements and future research will explore the role of performance influencing factors in the maintenance task to identify additional causes of variation. These factors may then be incorporated as a process variable in a prognostics and health management (PHM) model developed for the system. The paper will present these data fusion approaches accounting for human factors as a roadmap to improving PHM model reliability

Fuzzy Human Reliability Analysis: Applications and Contributions Review

The applications and contributions of fuzzy set theory to human reliability analysis (HRA) are reassessed. The main contribution of fuzzy mathematics relies on its ability to represent vague information. Many HRA authors have made contributions developing new models, introducing fuzzy quantification methodologies. Conversely, others have drawn on fuzzy techniques or methodologies for quantifying already existing models. Fuzzy contributions improve HRA in five main aspects: (1) uncertainty treatment, (2) expert judgment data treatment, (3) fuzzy fault trees, (4) performance shaping factors, and (5) human behaviour model. Finally, recent fuzzy applications and new trends in fuzzy HRA are herein discussed

Performer selection in Human Reliability analysis: D numbers approach

Dependence assessment among human errors in human reliability analysis (HRA) is an significant issue. Many previous works discussed the factors influencing the dependence level but failed to discuss how these factors like "similarity of performers" determine the final result. In this paper, the influence of performers on HRA is focused, in addition, a new way of D numbers which is usually used to handle with the multiple criteria decision making (MCDM) problems is introduced as well to determine the optimal performer. Experimental result demonstrates the validity of proposed methods in choosing the best performers with lowest the conditional human error probability (CHEP) under the same circumstance

Diseño de un sistema de control Operacional en la Manufactura de Tapetes Artesanales de la Empresa Gobelins S.A.S

Gobelins nace a partir de la búsqueda del reconocimiento y valor del trabajo de los artesanos. Son la unión de la experiencia, talento y esfuerzo, creando una marca que apoya el trabajo hecho a mano, el tejido 100% colombiano y que llevara obras de arte como lo son los tapetes artesanales a todos los hogares de Colombia y del mundo, fabricados en diversos materiales como lo son: fibras naturales, metales, sedas, hilos y nylon. Dentro de los diagnósticos realizados a la organización se evidencia la ausencia de herramientas que le permitan a los funcionarios ser más eficientes en los procesos de fabricación de los tapetes artesanales, presentando en ocasiones demoras en los tiempos establecidos para la entrega del producto final, haciendo que en su proceso se perciban errores por falta de entrenamiento y control. Según el principio de intensificación del señor Henry Ford se centra en disminuir el tiempo de producción con el empleo adecuado e inmediato de la maquinaria, equipo y materia prima con la cual se dispone y la rápida colocación del producto terminado en el mercado. El estudio de métodos divide y desglosa la tarea en una parte razonable de operaciones. De esta manera se entiende mejor cómo se ejecuta la tarea, y de este modo sirve para unificar un método operativo para todos los implicados en su ejecución. Además, es el punto de partida para su mejoría, si bien se hace notar que el hecho de describir un método operativo ya es en sí una mejora, probablemente la más importante (Cruelles J. , 2012) El estudio de tiempos es una técnica de medición del trabajo empleada para registrar los tiempos de trabajo y actividades correspondientes a las operaciones de una tarea definida, efectuada en condiciones determinadas, con el fin de analizar los datos y poder calcular el tiempo requerido para poder efectuar la tarea según un método de ejecución establecido. Su finalidad consiste en establecer medidas o normas de rendimiento para la ejecución de una tarea (Cruelles J. , 2012) El siguiente proyecto tiene como propósito diseñar una propuesta que contribuya al control operativo en el área de producción de la empresa Gobelins S.A.S, analizando los procesos operativos que permitan determinar las inconsistencias por medio de un diagnóstico al interior de la organización, generando planes de mejora apoyados en las necesidades identificadas.Universidad Libre -- Facultad de Ciencias Económicas, Administrativas y Contables -- Administración de EmpresasGobelins was born from the search for recognition and value of the work of artisans. They are the union of experience, talent and effort, creating a brand that supports handmade work, 100% Colombian fabric and that will bring works of art such as handmade rugs to all homes in Colombia and the world, manufactured in various materials such as: natural fibers, metals, silks, threads and nylon. Within the diagnoses made to the organization, the absence of tools that allow officials to be more efficient in the manufacturing processes of handmade rugs is evident, sometimes presenting delays in the times established for the delivery of the final product, making errors are perceived in their process due to lack of training and control. According to the principle of intensification of Mr. Henry Ford, it focuses on reducing the production time with the adequate and immediate use of the machinery, equipment and raw material with which it is available and the rapid placement of the finished product in the market. Method study divides and breaks down the task into a reasonable part of operations. In this way it is better understood how the task is executed, and in this way it serves to unify an operating method for all those involved in its execution. In addition, it is the starting point for its improvement, although it is noted that the fact of describing an operating method is already an improvement in itself, probably the most important (Cruelles J. , 2012) Time study is a work measurement technique used to record the work times and activities corresponding to the operations of a defined task, carried out under determined conditions, in order to analyze the data and be able to calculate the time required to carry out the task according to an established execution method. Its purpose is to establish performance measures or standards for the execution of a task (Cruelles J. , 2012) The purpose of the following project is to design a proposal that contributes to operational control in the production area of the company Gobelins S.A.S, analyzing the operational processes that allow determining inconsistencies through a diagnosis within the organization, generating improvement plans based on the identified needs

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

A fuzzy set-based approach for modeling dependence among human errors

The assessment of dependence among human errors is an important aspect of human reliability analysis. When dependence between two tasks exists, the probability of the operators’ failure on one task is higher if they have failed on the preceding task, compared to when they have succeeded. In current practice, the task of assessing dependence among successive operator actions relies to a great extent to expert judgment, often with lack of traceability and repeatability. To overcome these limitations, this work presents a systematic framework for the elicitation of expert knowledge on the factors influencing the dependence between two successive tasks. The framework is based on a fuzzy expert system in which a set of transparent fuzzy logic rules is used to represent the relationship between the input factors and the conditional human error probability. The proposed modeling approach is applied to two tasks required in response to an accident scenario at a nuclear power plant. Given the methodological scope of the work, the fuzzy expert system is tested directly on a working model of dependence, whereas no actual exercise of expert judgment elicitation is carried out

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty