Inferring determinacy and mutual exclusion in logic programs using mode and type analysis.

We propose an analysis for detecting procedures and goals that are deterministic (i.e., that produce at most one solution at most once), or predicates whose clause tests are mutually exclusive (which implies that at most one of their clauses will succeed) even if they are not deterministic. The analysis takes advantage of the pruning operator in order to improve the detection of mutual exclusion and determinacy. It also supports arithmetic equations and disequations, as well as equations and disequations on terms, for which we give a complete satisfiability testing algorithm, w.r.t. available type information. We have implemented the analysis and integrated it in the CiaoPP system, which also infers automatically the mode and type information that our analysis takes as input. Experiments performed on this implementation show that the analysis is fairly accurate and efficient.

Evaluation and FMEA of Fabrication Techniques for Metallic Grating Couplers on Polymer Substrates with Low Glass Transition Temperatures

The main task is to analyze the state of the art of grating couplers production and low-cost polymer substrates. Then to provide a recommendation of a new or adapted process for the production of metallic gratings on polymer sheets, based on a Failure Mode and Effect Analysis (FMEA). In order to achieve that, this thesis is divided into four chapters. After the first introductory chapter, the second section provides details about the state-of-the-art in optical technology platforms with focus on polymers and their main features for the aimed application, such as flexibility, low cost and roll to roll compatibility. It defines then the diffraction gratings and their specifications and closes with the explanation of adhesion mechanisms of inorganic materials on polymer substrates. The third chapter discusses processing of grating couplers. It introduces the basic fabrication methods and details a selection of current fabrication schemes found in literature with an assessment of their potential use for the desired application. The last chapter is a FMEA analysis of the retained fabrication process, called Flip and Fuse, in order to check its capability to realize the grating structure.

Risk management in research and development (R&D) projects: the case of South Australia

A definition of the effective methods of risk management in R&D projects has remained elusive. Similarly, there have been calls to devise effective risk management methods in R&D projects. To develop this area further, the purpose of this study is twofold. First, it validates the veracity of claims about the urgency of introducing effective methods of risk management to R&D projects in South Australia based on nine unstructured interviews with experts. Second, the study presents the outcomes of two case studies that deployed the extended version of the failure mode and effect analysis, namely, the RFMEA method in a South Australian organisation, to investigate how the method can facilitate the identification of effective contingency plans to mitigate high-priority risks. The findings showed that the RFMEA method would be effective for project managers in dealing with risk management issues in R&D projects. The discussions presented will provide guidelines for practitioners in the industry.

Análise dos modos de falha e seus efeitos (FMEA) aplicada a um secador industrial

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

A guided rule reduction system for prioritization of failures in fuzzy FMEA

Traditional Failure Mode and Effect Analysis (FMEA) utilizes the Risk Priority Number (RPN) ranking system to evaluate the risk level of failures, to rank failures, and to prioritize actions. Although this method is simple, it suffers from several shortcomings. In this paper, use of fuzzy inference techniques for RPN determination in an attempt to overcome the weaknesses associated with the traditional RPN ranking system is investigated. However, the fuzzy RPN model, suffers from the combinatorial rule explosion problem. As a result, a generic rule reduction approach, i.e. the Guided Rule Reduction System (GRRS), is proposed to reduce the number of rules that need to be provided by users during the fuzzy RPN modeling process. The proposed approach is evaluated using real-world case studies pertaining to semiconductor manufacturing. The results are analyzed, and implications of the proposed approach are discussed.

A non-linear programming-based similarity reasoning scheme for modelling of monotonicity-preserving multi-input fuzzy inference systems

In this paper, the zero-order Sugeno Fuzzy Inference System (FIS) that preserves the monotonicity property is studied. The sufficient conditions for the zero-order Sugeno FIS model to satisfy the monotonicity property are exploited as a set of useful governing equations to facilitate the FIS modelling process. The sufficient conditions suggest a fuzzy partition (at the rule antecedent part) and a monotonically-ordered rule base (at the rule consequent part) that can preserve the monotonicity property. The investigation focuses on the use of two Similarity Reasoning (SR)-based methods, i.e., Analogical Reasoning (AR) and Fuzzy Rule Interpolation (FRI), to deduce each conclusion separately. It is shown that AR and FRI may not be a direct solution to modelling of a multi-input FIS model that fulfils the monotonicity property, owing to the difficulty in getting a set of monotonically-ordered conclusions. As such, a Non-Linear Programming (NLP)-based SR scheme for constructing a monotonicity-preserving multi-input FIS model is proposed. In the proposed scheme, AR or FRI is first used to predict the rule conclusion of each observation. Then, a search algorithm is adopted to look for a set of consequents with minimized root means square errors as compared with the predicted conclusions. A constraint imposed by the sufficient conditions is also included in the search process. Applicability of the proposed scheme to undertaking fuzzy Failure Mode and Effect Analysis (FMEA) tasks is demonstrated. The results indicate that the proposed NLP-based SR scheme is useful for preserving the monotonicity property for building a multi-input FIS model with an incomplete rule base.

Fuzzy FMEA with a guided rules reduction system for prioritization of failures

Purpose – To propose a generic method to simplify the fuzzy logic-based failure mode and effect analysis (FMEA) methodology by reducing the number of rules that needs to be provided by FMEA users for the fuzzy risk priority number (RPN) modeling process.

Design/methodology/approach – The fuzzy RPN approach typically requires a large number of rules, and it is a tedious task to obtain a full set of rules. The larger the number of rules provided by the users, the better the prediction accuracy of the fuzzy RPN model. As the number of rules required increases, ease of use of the model decreases since the users have to provide a lot of information/rules for the modeling process. A guided rules reduction system (GRRS) is thus proposed to regulate the number of rules required during the fuzzy RPN modeling process. The effectiveness of the proposed GRRS is investigated using three real-world case studies in a semiconductor manufacturing process.

Findings – In this paper, we argued that not all the rules are actually required in the fuzzy RPN model. Eliminating some of the rules does not necessarily lead to a significant change in the model output. However, some of the rules are vitally important and cannot be ignored. The proposed GRRS is able to provide guidelines to the users which rules are required and which can be eliminated. By employing the GRRS, the users do not need to provide all the rules, but only the important ones when constructing the fuzzy RPN model. The results obtained from the case studies demonstrate that the proposed GRRS is able to reduce the number of rules required and, at the same time, to maintain the ability of the Fuzzy RPN model to produce predictions that are in agreement with experts' knowledge in risk evaluation, ranking, and prioritization tasks.

Research limitations/implications – The proposed GRRS is limited to FMEA systems that utilize the fuzzy RPN model.

Practical implications – The proposed GRRS is able to simplify the fuzzy logic-based FMEA methodology and make it possible to be implemented in real environments.

Originality/value – The value of the current paper is on the proposal of a GRRS for rule reduction to enhance the practical use of the fuzzy RPN model in real environments.

On the use of fuzzy inference techniques in assessment models : part II : industrial applications

In this paper, we study the applicability of the monotone output property and the output resolution property in fuzzy assessment models to two industrial Failure Mode and Effect Analysis (FMEA) problems. First, the effectiveness of the monotone output property in a single-input fuzzy assessment model is demonstrated with a proposed fuzzy occurrence model. Then, the usefulness of the two properties to a multi-input fuzzy assessment model, i.e., the Bowles fuzzy Risk Priority Number (RPN) model, is assessed. The experimental results indicate that both the fuzzy occurrence model and Bowles fuzzy RPN model are able to fulfill the monotone output property, with the derived conditions (in Part I) satisfied. In addition, the proposed rule refinement technique is able to improve the output resolution property of the Bowles fuzzy RPN model.

An evolutionary-based similarity reasoning scheme for monotonic multi-input fuzzy inference systems

In this paper, an Evolutionary-based Similarity Reasoning (ESR) scheme for preserving the monotonicity property of the multi-input Fuzzy Inference System (FIS) is proposed. Similarity reasoning (SR) is a useful solution for undertaking the incomplete rule base problem in FIS modeling. However, SR may not be a direct solution to designing monotonic multi-input FIS models, owing to the difficulty in getting a set of monotonically-ordered conclusions. The proposed ESR scheme, which is a synthesis of evolutionary computing, sufficient conditions, and SR, provides a useful solution to modeling and preserving the monotonicity property of multi-input FIS models. A case study on Failure Mode and Effect Analysis (FMEA) is used to demonstrate the effectiveness of the proposed ESR scheme in undertaking real world problems that require the monotonicity property of FIS models.

Application of fuzzy inference techniques to FMEA

In traditional Failure Mode and Effect Analysis (FMEA), the Risk Priority Number (RPN) ranking system is used to evaluate the risk level of failures, to rank failures, and to prioritize actions. This approach is simple but it suffers from several weaknesses. In an attempt to overcome the weaknesses associated with the traditional RPN ranking system, several fuzzy inference techniques for RPN determination are investigated in this paper. A generic Fuzzy RPN approach is described, and its performance is evaluated using a case study relating to a semiconductor manufacturing process. In addition, enhancements for the fuzzy RPN approach are proposed by refining the weights of the fuzzy production rules.

Uma metodologia para adaptação e melhoria de produtos a partir da engenharia reversa

O tema desta dissertação de mestrado é o estudo da Engenharia Reversa como ferramenta de suporte à melhoria e adaptação de produtos. A partir de conceitos teóricos sobre desenvolvimento de produtos e melhoria de processos, propõe-se uma metodologia para adaptação de produtos destinados à exportação. A metodologia proposta consiste de oito passos, contemplando etapas de identificação e priorização das demandas de adaptação de produtos e elencando ferramentas auxiliares no atingimento dos objetivos desejados. A etapa inicial deste trabalho consiste de uma revisão bibliográfica dividida em duas partes: (i) adaptação de produtos através da utilização da Engenharia Reversa e seus habilitadores, e (ii) ferramentas para melhoria de processos. Os tópicos contemplados em (ii) incluem ferramentas para o mapeamento de processos de manufatura e para a sua melhoria. Destaque especial é dado ao Desdobramento da Função Qualidade – QFD (Quality Function Deployment), a Análise de Modos e Efeitos de Falhas (FMEA – Failure Mode and Effect Analysis) e às Cartas de Processos. Na seqüência, apresentam-se os passos da metodologia proposta para a adaptação de produtos às demandas de mercado utilizando a Engenharia Reversa e seus habilitadores. Finalmente, os passos metodológicos são aplicados a um caso prático, cujo objetivo é a adaptação de um pincel, produzido por uma empresa gaúcha, às demandas de um distribuidor alemão de ferramentas manuais.

Avaliação da prevenção de falhas em processos utilizando métodos de tomada de decisão

Este trabalho apresenta uma investigação sobre o emprego de FMEA (Failure Mode and Effect Analysis) de Processo com a exposição de irregularidades na sua utilização. O método AHP (Analytic Hierarchy Process) e os Conjuntos Fuzzy são aplicados no estudo das práticas atuais de utilização de FMEA. O AHP é aplicado para a priorização das irregularidades quanto à gravidade de sua ocorrência. Os Conjuntos Fuzzy são aplicados para avaliação do desempenho da utilização de FMEA em algumas empresas do ramo automotivo. Como resultado, tem-se a aceitação de oito e a não aceitação de três dos onze formulários de FMEA averiguados.

Avaliação de sistemas de prevenção de falhas em processos de manufatura na indústria automotiva com metodologia de auxílio à decisão

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação dos conceitos de RCM e a ferramenta FMEA no aumento de confiabilidade em equipamentos de uma indústria química

The growing demand for quality at competitive prices and fast production process put to the test function in the industrial Maintenance. The need for equipment with high availability to fit this fierce competitiveness makes maintenance becomes essentially reliable. Despite this current context, many companies still have an old view of maintenance, focused only on corrective services, and proposals for change are often neglected due to the sense of urgency day to day. Thus, this study aims to demonstrate through theoretical applicability of simple tool, but of great value in increasing reliability within the maintenance sector of an industry, applying the concepts of Reliability Centered Maintenance – RCM and Analysis tool Failure Modes and Effects – FMEA in equipment of a chemical company directly involved in the manufacturing process of the brake fluid, which this product is used in vehicles around the country. That way, you can identify the types, occurrence and criticality of each failure and evaluate assertively decision making for each device, avoiding unnecessary downtime and potential failures of the same