Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

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

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

A NOVEL RISK EVALUATION APPROACH FOR FREQUENTLY ENCOUNTERED RISKS IN SHIP ENGINE ROOMS

The purpose of this study is to evaluate risks which are frequently encountered in the engine room on-board. In this context, twenty common risks are assessed using the neutrosophic analytic hierarchy process (N-AHP) and trapezoidal fuzzy technique for order preference by similarity to ideal solution (TrF-TOPSIS). In maritime risk evaluation, since it is frequently required the linguistic assessment of decision-makers to achieve a robust risk assessment tool, neutrosophic sets and fuzzy sets are used together in this study. Neutrosophic sets represent real-world problems effectively by considering all aspects of decision-making situations, (i.e. truthiness, indeterminacy, and falsity). Therefore, AHP is integrated with neutrosophic sets to assign weights of risk parameters initially. Then, the encountered risks are prioritized by TrF-TOPSIS. Finally, preventative actions for the risks have been discussed. In conclusion of the study, it is shown that skin exposure to the fuels/oils, exposure to chemicals and exposure to high pressure and temperature liquids are the most important risks through the engine room on-board. This study both emphasizes the importance of preventing damage to crew in the risk assessment of ship engine rooms and aims to increase the level of safety control and minimize the potential environmental impacts of a ship\u27s damage

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Current Application Fields of ELECTRE and PROMETHEE: A Literature Review

Multi-criteria decision making techniques are widely used today. In this study, it was examined the current usage areas of ELECTRE and PROMETHEE, which are in the class of outranking-based multiple criteria decision techniques, in Turkey and the world. In this regard, the studies carried out in 2016 and the first four months of 2017 were scanned with the help of Google Scholar. Thus, it is aimed to put forward the latest state of development of ELECTRE and PROMETHEE, and to give an idea about their future application forms and fields. As a result, it was seen that application problems of ELECTRE and PROMETHEE in various fields was tried to remove, and designed appropriate methods for special cases in studies. Furthermore, evaluation according to scenario variations, solving complex decision problems with metaheuristics, common usage of hesitant fuzzy implementations, proliferation of group decision preference, increasing the number of applications of hybrid techniques, used softwares, sensitivity analyses, two linguistic approaches taking an important place in fuzzification have been identified as remarkable results

Project risk evaluation by using a new fuzzy model based on Elena guideline

The complexity and dynamics of the executive projects have coped contractors with substantial hazards and losses. Project risk management is a critical tool for authority to improve its performance and secure the success of the organization. However, a number of standards and approaches have been developed to formulate the projects based on their risks. The Elena guideline is a systematic standard developed by Iran Project Management Association. This guideline provides the full cycle of the risk management process. Risk evaluation is the key part of the risk management process. On the other hand, different techniques have been developed to model a risk evaluation problem. Fuzzy inference system is one of the most popular techniques that is capable of handling all types of the uncertainty involved in projects. This paper proposes a three-stage approach based on the fuzzy inference system under the environment of the Elena guideline to cope with the risky projects. Finally, an illustrative example of the risk evaluation is presented to demonstrate the potential application of the proposed model. The results show that the proposed model evaluates the risky projects efficiently and effectively

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Approaches to selecting information systems projects under uncertainty

The rapid advance in information and communication technologies has effectively facilitated the development and implementation of information systems (IS) projects in modern organizations for reorganizing their business processes and streamlining the provision of their products and services in today's dynamic environment. Such a development brings organizations with numerous benefits including increased automation of business processes, improved customer service, and timely provision of effective decision support. As a result, evaluating and selecting the most appropriate IS project for development and implementation from a pool of available IS projects becomes a critical decision to make in modern organizations. Evaluating and selecting appropriate IS projects for development in an organization, however, is complex and challenging. The complexity of the evaluation and selection process is due to the multi-dimensional nature of the decision making process, the conflicting nature of the multiple selection criteria, and the presence of subjectiveness and imprecision of the human decision making process. The challenging of the evaluation and selection comes from the need for making transparent and balanced decisions based on a comprehensive evaluation of all available IS projects in a timely manner. Much research has been done on the development of various approaches for evaluating and selecting IS projects, and numerous applications of those approaches for addressing real world IS project evaluation and selection problems have been reported in the literature. In general, existing approaches can be classified into (a) cost-benefit analysis based approaches, (b) utility based approaches, and (c) optimization oriented approaches. These approaches, however, are not totally satisfactory due to various shortcomings including (a) the inability to tackle the subjectiveness and imprecision of the selection process, (b) the failure to adequately handle the multi-dimensional nature of the problem, and (c) cognitively very demanding on the decision maker. To address these issues above, this research has developed three novel approaches for effectively solving the IS project evaluation and selection problem under uncertainty in an organization. The first approach is developed for helping the decision maker better model the subjectiveness and imprecision inherent in the decision-making process with the use of linguistic variables approximated by fuzzy numbers. The second approach is designed to reduce the cognitive demanding on the decision maker in the IS project evaluation and selection process with the introduction of fuzzy pairwise comparison. The third approach is formulated with respect to the use of intelligent decision support systems for facilitating the use of specific multi-criteria analysis approaches in relation to individual IS project evaluation and selection situations. The developed approaches have been applied for solving three IS project evaluation and selection problems in the real world settings. The results show that the three developed ap proaches are of practical significance for effectively and efficiently solving the IS project evaluation and selection problem due to (a) the simplicity and comprehensibility of the underlying concept, (b) the adequate handling of inherent uncertainty and imprecision, and (c) the ability to help the decision maker better understand the IS project selection problem and the implications of their decision behaviours