"The connection between distortion risk measures and ordered weighted averaging operators"

Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between distortion risk measures and the OWA and WOWA operators for discrete and nite random variables is presented. This connection oers a new interpretation of distortion risk measures and, in particular, Value-at-Risk and Tail Value-at-Risk can be understood from an aggregation operator perspective. The theoretical results are illustrated in an example and the degree of orness concept is discussed.Fuzzy systems; Degree of orness; Risk quantification; Discrete random variable JEL classification:C02,C60

\u3ci\u3eThe Symposium Proceedings of the 1998 Air Transport Research Group (ATRG), Volume 2\u3c/i\u3e

UNOAI Report 98-4https://digitalcommons.unomaha.edu/facultybooks/1153/thumbnail.jp

Occupational Cultures as a Challenge to Technological Innovation

This paper explains conflict over technological process innovation in cultural terms, drawing primarily on a case study of electric power distribution and strategies to automate its operation

Study of FSRU-LNGC System Based on a Quantitative Multi-cluster Risk Informed Model

PresentationThe offshore LNG terminal, referred to as LNG floating storage unit or floating storage and re- gasification unit (FSRU), performs well on both building process and operation process. The LNG FSRU is a cost-effective and time efficient solution for LNG transferring in the offshore area, and it brings minimal impacts to the surrounding environment as well. This paper proposed a systematic method to integrate chemical process safety with maritime safety analysis. The evaluation network was adopted to process a comparison study between two possible locations for LNG offshore FSRU. This research divided the whole process into three parts, beginning with the LNG Carrier navigating in the inbound channel, the berthing operation and ending with the completion of LNG transferring operation. The preferred location is determined by simultaneously evaluating navigation safety, berthing safety and LNG transferring safety objectives based on the quantitative multi-cluster network multi-attribute decision analysis (QMNMDA) method. The maritime safety analysis, including navigational process and berthing process, was simulated by LNG ship simulator and analyzed by statistical tools; evaluation scale for maritime safety analysis were determined by analyzing data from ninety experts. The chemical process safety simulation was employed to LNG transferring events such as connection hose rupture, flange failure by the consequence simulation tool. Two scenarios, i.e., worst case scenario and maximum credible scenario, were taken into consideration by inputting different data of evaluating parameters. The QMNMDA method transformed the evaluation criteria to one comparable unit, safety utility value, to evaluate the different alternatives. Based on the final value of the simulation, the preferred location can be determined, and the mitigation measures were presented accordingly

Fuzzy Cost Modelling of Diving Chamber Control Measures under Uncertainties

The diving chamber is an important system needed for diving operations in the oil and gas industry. Divers use it for various purposes. Thus, the safety level of the diving chamber needs to be very high at all times and the system needs to be in a good state. To achieve this, various control measures such as control measures 1 and 2 can be adopted in preventing failures/hazards or mitigate their consequences. In this study, fuzzy cost algorithm is used to estimate the cost of using control measures 1 and 2 in ensuring optimal operational level for the diving chamber, while the preference degree approach is adopted in prioritizing the aforementioned cost of control measures 1 and 2. The result of the analysis indicated that control measure 2 is the most cost effective approach

Decision Support System for Production Planning from a Sustainability Perspective

Manufacturing enterprises supply our global demand for products, creating economic value. Moreover, they are also responsible for several environmental and social impacts, e.g., green-house gases, waste, and poor working conditions. These impacts cause climate change, air and sea pollution, and social inequality, which are a few examples of current challenges for global sustainability strategies. However, researchers have widely addressed these impacts and warned politicians and society about the risk of the collapse of ecosystems. Despite these warnings, manufacturing enterprises still have difficulties improving the sustainability of their production processes. Therefore, new technologies are required to support enterprises and help determine their production processes’ sustainability status by considering multiple aspects (economic, environmental, and social). Moreover, advice should be given on how the identified issues can be avoided, reduced, or compensated for future production activities. This research presents a fuzzy decision support system and an experimental study for sustainability-based production planning. For this approach, systematic literature reviews were made, analysing concept methods for sustainability-based production management and planning. The results show, among other things, that current methods for sustainability-production planning are focused on single aspects of sustainability (e.g., energy or waste planning). Therefore, a fuzzy decision support system was developed that simultaneously evaluates social, environmental, and economic aspects. The decision support system's model identifies the most significant opportunities to improve the production program's sustainability and gives recommendations on how to change it. The decision support system was tested and validated in an experimental study in the production planning laboratory at Emden University of Applied Sciences. The study results discuss problems, needs, and challenges affecting sustainability-based production planning. Moreover, opportunities for future research were identified based on the limitations of the experimental study.As empresas transformadoras satisfazem a procura global de produtos, criando valor económico. No entanto, também são responsáveis por vários impactos ambientais e sociais, por exemplo, gases de efeito estufa, resíduos e más condições de trabalho. Estes impactos originam alterações climáticas, poluição do ar e do mar e desigualdade social, que constituem alguns exemplos dos desafios que se colocam atualmente às estratégias globais de sustentabilidade. De notar que os investigadores têm abordado amplamente estes impactos e alertado os políticos e a sociedade sobre o risco do colapso dos ecossistemas. Apesar destes alertas, as empresas transformadoras ainda têm dificuldades em melhorar a sustentabilidade dos seus processos produtivos. Como tal, são necessárias novas tecnologias para apoiar as empresas, ajudando a caracterizar o estado de sustentabilidade dos seus processos de produção, considerando múltiplos fatores (económicos, ambientais e sociais). Além disso, devem ser dados conselhos sobre o modo como os problemas identificados podem ser evitados, reduzidos ou compensados em atividades de produção futuras. A investigação realizada contribuiu para o desenvolvimento de um sistema de apoio à decisão difuso, aplicado a um estudo de caso de planeamento da produção baseado na sustentabilidade. Para o efeito, foram conduzidas revisões sistemáticas da literatura, analisando os conceitos associados aos métodos para gestão e planeamento da produção baseado na sustentabilidade. Os resultados revelam, entre outras conclusões, que os métodos atuais para o planeamento da produção sustentável estão focados em fatores isolados de sustentabilidade (e.g., planeamento energético ou de resíduos). Perante este contexto, foi desenvolvido um sistema de apoio à decisão difuso, que avalia simultaneamente fatores sociais, ambientais e económicos. O modelo do sistema de apoio à decisão identifica as oportunidades mais significativas para melhorar a sustentabilidade do programa de produção e fornece recomendações sobre o modo como este pode ser alterado. O sistema de apoio à decisão foi testado e validado num estudo de caso simulado no laboratório de planeamento da produção na Universidade de Ciências Aplicadas de Emden. Os resultados do estudo de caso permitiram analisar os problemas, necessidades e desafios que afetam o planeamento da produção baseado na sustentabilidade. Complementarmente, foram identificadas oportunidades de investigação futuras, considerando as limitações do estudo de caso realizado

Computer Aided Home Energy Management system

High prices are associated with the peak electricity demand and thus, price can be used as an indicator of power system condition in the peak load management programs. This paper investigates the potential of peak load management based on price-responsive load control for the residential sector. The Computer Aided Home Energy Management (CAHEM) system controls residential demand in response to the hourly market data including price, load and temperature data. A fuzzy demand controller incorporates customer preferences in determining operational settings of residential appliances. A prototype CAHEM system is demonstrated using X10 home networking technology. The aggregate level effects of the CAHEM system on peak load reduction are simulated for the Pennsylvania-New Jersey-Maryland market during the summer of 1999. The study also estimates the optimal level of large-scale adoption of the CAHEM system

Condition-Based Maintenance of HVAC on a High-Speed Train for Fault Detection

Reliability-centered maintenance (RCM) is a well-established method for preventive maintenance planning. This paper focuses on the optimization of a maintenance plan for an HVAC (heating, ventilation and air conditioning) system located on high-speed trains. The first steps of the RCM procedure help in identifying the most critical items of the system in terms of safety and availability by means of a failure modes and effects analysis. Then, RMC proposes the optimal maintenance tasks for each item making up the system. However, the decision-making diagram that leads to the maintenance choice is extremely generic, with a consequent high subjectivity in the task selection. This paper proposes a new fuzzy-based decision-making diagram to minimize the subjectivity of the task choice and preserve the cost-efficiency of the procedure. It uses a case from the railway industry to illustrate the suggested approach, but the procedure could be easily applied to different industrial and technological fields. The results of the proposed fuzzy approach highlight the importance of an accurate diagnostics (with an overall 86% of the task as diagnostic-based maintenance) and condition monitoring strategy (covering 54% of the tasks) to optimize the maintenance plan and to minimize the system availability. The findings show that the framework strongly mitigates the issues related to the classical RCM procedure, notably the high subjectivity of experts. It lays the groundwork for a general fuzzy-based reliability-centered maintenance method.This research received no external fundin