Pauli Adriano de Almada Garcia

A weight restricted DEA model for FMEA risk prioritization

In this paper we present a linear programming (LP) approach to risk prioritization in failure mode and effects analysis (FMEA). The LP is a data envelopment analysis (DEA)-based model considering weight restriction. In a FMEA, we commonly consider three criteria to prioritize the failure modes, occurrence, severity and detectability. These criteria are in an ordinal scale commonly varying from 1 to 10, higher the figure worse the result. Considering the values established for each criteria, in traditional FMEA one adopts a Risk Priority Number, calculated considering the product of criteria, which has been very criticized due to its shortcoming. Through the proposed approach a frontier is established considering the less critical failure modes. Considering this frontier, one can establish how much each failure mode must be improved to become relatively acceptable. A simplified case concerning an AFWS of a two loops PWR power plant is presented to shows the applicability of the proposed approach.

Aplicação de um modelo fuzzy DEA para priorizar modos de falha em sistemas nucleares

In this paper one presents a data envelopment analysis and fuzzy sets based hybrid model application, in order to establish a priority ranking for the failure modes evaluated in a failure mode and effect analysis. The main objective is to present the applicability of this hybrid model to analyze complex systems, as the chemical and volumetric control system of a pressurized water reactor power plant, where a great bunch of failure modes must typically be evaluated. The presented modeling makes it possible the consideration of linguistic variables, i.e., it permits that one considers most effectively expert opinion in a risk analysis context when scarce data is available, as may occur in the plant design phase. The results obtained demonstrated the powerfulness and the viability of use of the proposed hybrid modeling to establish a priority ranking among many failure modes concerning a complex system.

Multiobjective optimization of strategies for operation and testing of low-demand safety instrumented systems using a genetic algorithm and fault trees

Since low-demand safety instrumented systems (SISs) do not operate continuously, their failures are often only detected when the system is demanded or tested. The conduction of tests, besides adding costs, can raise risks of failure on demand during their execution and also increase the frequency of spurious activation. Additionally, it is often necessary to interrupt production to carry out tests. In light of this scenario, this paper presents a model to optimize strategies for operation and testing of these systems, applying modeling by fault trees associated with optimization by a genetic algorithm. Its main differences are: (i) ability to represent four modes of operation and test them for each SIS subsystem; (ii) ability to represent a SIS that executes more than one safety instrumented function; (iii) ability to keep track of the down-time generated in the production system; and (iv) alteration of a genetic selection mechanism that permits identification of more efficient solutions with smaller influence on the optimization parameters. These aspects are presented by applying this model in three case studies. The results obtained show the applicability of the proposed approach and its potential to help make more informed decisions.

Uma abordagem via análise envoltória de dados para o estabelecimento de melhorias em segurança baseadas na FMEA

Abstract: The present study presents a data envelopment analysis (DEA) based approach to establish guidelines for the improvement of the failure modes identified by a failure mode and effect analysis (FMEA). The traditional FMEA approach is based on risk priority number (RPN), which has been target of scientific criticism. In the present study, the RPN is based on DEA and considers the concept of efficiency frontier. Based on this concept and on the risk indexes, some improvement directives for the failure modes can be established. The obtained results concerning the two practical applications demonstrate the effectiveness of the proposed approach in dealing with this kind of problem. Keywords: Failure analysis. FMEA. Data envelopment analysis. Risk priority number. Risk analysis. Resumo: O presente trabalho apresenta uma abordagem baseada em analise envoltoria de dados ( Data Envelopment Analysis – DEA) para estabelecer direcionamentos de melhoria para os modos de falhas identificados na analise dos modos e efeitos de falha (FMEA). A abordagem tradicional da FMEA baseia-se num numero de priorizacao de riscos que vem sendo alvo de inumeras criticas embasadas em diversos artigos cientificos. No presente trabalho, o numero de priorizacao de risco e baseado em DEA. Por meio desse numero de priorizacao de risco DEA, considerando-se o conceito de fronteira de eficiencia, serao identificadas diretrizes de melhoria para os modos de falha com base nos indices de risco estabelecidos pela equipe executora da FMEA. Por meio dos resultados alcancados nas duas aplicacoes praticas, pode-se demonstrar a eficacia da abordagem proposta para tratar essa classe de problemas.

Uma abordagem baseada em análise relacional grey para a avaliação de programas de pós-graduação brasileiros em mestrado em administração de empresas

The education development in Brazil has been influenced by government policies, especially those directed at higher learning. To judge the effectiveness of these policies it is necessary to evaluate the quality of the teaching offered, particularly with respect to public education. In this context, there have been many initiatives for new postgraduate programs. To be accredited, these programs must be approved by the Coordination for the Improvement of Higher Education Personnel (CAPES), part of the Ministry of Education. Among the many criteria considered by CAPES, the academic production is the most important. Many works proposing approaches to classify college programs based on faculty bibliographical output have been published; among these, those based on data envelopment analysis stand out. The present work uses grey relational analysis based approach. Another difference is that the information is considered on a master’s program not yet accredited, that is, one that still needs to be evaluated by CAPES. A classification is established for this program in relation to the ones already accredited along with a way to identify the improvement points and an improvement factor for each attribute considered. The results indicate that the approach is efficient in relation to that based on traditional data envelopment analysis and suggest areas for future research in this area.

Patento-scientometric indicators for the selection of projects by investment funds

Purpose – This paper aims to assess a method that applies scientometric and patentometric indicators in the selection process of projects by seed capital funds. There is increasing interest in technology-based enterprises, for their capacity to contribute to economic and social development. Nevertheless, in practice, there is some difficulty in assessing non-financial criteria associated with technology for the purposes of choosing investment opportunities. Design/methodology/approach – The literature has presented various methods to instrumentalize the process of evaluation and selection of investment projects. This study focuses on an enterprise that received an investment by the largest seed capital fund in Brazil, to assess to what extent scientific and technological indicators can contribute to understanding the market potential of the firm’s technology. Findings – The results show that the use of scientometric and patentometric indicators favors the process of judging non-financial criteria, in part...