78 resultados para constrained fuzzy analytic hierarchy process (AHP)
Resumo:
The existing method of pipeline monitoring, which requires an entire pipeline to be inspected periodically, wastes time and is expensive. A risk-based model that reduces the amount of time spent on inspection has been developed. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction method and logical insurance plans.The risk-based model uses analytic hierarchy process, a multiple attribute decision-making technique, to identify factors that influence failure on specific segments and analyze their effects by determining the probabilities of risk factors. The severity of failure is determined through consequence analysis, which establishes the effect of a failure in terms of cost caused by each risk factor and determines the cumulative effect of failure through probability analysis.
Resumo:
Projects that are exposed to uncertain environments can be effectively controlled with the application of risk analysis during the planning stage. The Analytic Hierarchy Process, a multiattribute decision-making technique, can be used to analyse and assess project risks which are objective or subjective in nature. Among other advantages, the process logically integrates the various elements in the planning process. The results from risk analysis and activity analysis are then used to develop a logical contingency allowance for the project through the application of probability theory. The contingency allowance is created in two parts: (a) a technical contingency, and (b) a management contingency. This provides a basis for decision making in a changing project environment. Effective control of the project is made possible by the limitation of the changes within the monetary contingency allowance for the work package concerned, and the utilization of the contingency through proper appropriation. The whole methodology is applied to a pipeline-laying project in India, and its effectiveness in project control is demonstrated.
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The main aim of this research is to demonstrate strategic supplier performance evaluation of a UK-based manufacturing organisation using an integrated analytical framework. Developing long term relationship with strategic suppliers is common in today's industry. However, monitoring suppliers' performance all through the contractual period is important in order to ensure overall supply chain performance. Therefore, client organisations need to measure suppliers' performance dynamically and inform them on improvement measures. Although there are many studies introducing innovative supplier performance evaluation frameworks and empirical researches on identifying criteria for supplier evaluation, little has been reported on detailed application of strategic supplier performance evaluation and its implication on overall performance of organisation. Additionally, majority of the prior studies emphasise on lagging factors (quality, delivery schedule and value/cost) for supplier selection and evaluation. This research proposes both leading (organisational practices, risk management, environmental and social practices) and lagging factors for supplier evaluation and demonstrates a systematic method for identifying those factors with the involvement of relevant stakeholders and process mapping. The contribution of this article is a real-life case-based action research utilising an integrated analytical model that combines quality function deployment and the analytic hierarchy process method for suppliers' performance evaluation. The effectiveness of the method has been demonstrated through number of validations (e.g. focus group, business results, and statistical analysis). Additionally, the study reveals that enhanced supplier performance results positive impact on operational and business performance of client organisation.
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This article presents a potential method to assist developers of future bioenergy schemes when selecting from available suppliers of biomass materials. The method aims to allow tacit requirements made on biomass suppliers to be considered at the design stage of new developments. The method used is a combination of the Analytical Hierarchy Process and the Quality Function Deployment methods (AHP-QFD). The output of the method is a ranking and relative weighting of the available suppliers which could be used to improve optimization algorithms such as linear and goal programming. The paper is at a conceptual stage and no results have been obtained. The aim is to use the AHP-QFD method to bridge the gap between treatment of explicit and tacit requirements of bioenergy schemes; allowing decision makers to identify the most successful supply strategy available.
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Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.
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A Bayesian procedure for the retrieval of wind vectors over the ocean using satellite borne scatterometers requires realistic prior near-surface wind field models over the oceans. We have implemented carefully chosen vector Gaussian Process models; however in some cases these models are too smooth to reproduce real atmospheric features, such as fronts. At the scale of the scatterometer observations, fronts appear as discontinuities in wind direction. Due to the nature of the retrieval problem a simple discontinuity model is not feasible, and hence we have developed a constrained discontinuity vector Gaussian Process model which ensures realistic fronts. We describe the generative model and show how to compute the data likelihood given the model. We show the results of inference using the model with Markov Chain Monte Carlo methods on both synthetic and real data.
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This thesis deals with the integration of the manpower criterion with the strategic decision making processes of technological projects in developing countries. This integration is to be achieved by ensuring the involvement of the actors, who have relevant roles and responsibilities along the whole life cycle of the project, in the strategic decision making phases of the project. The relevance of the actors is ascertained by the use of a responsibility index which relates their responsibility to the project's constituent stages. In the context of a technological project in a typical centrally-planned developing environment, the actors are identified as Arbiters, Planners, Implementors and Operators and their roles, concerns and objectives are derived. In this context, the actors are usually government and non-government organisations. Hence, decision making will involve multiple agencies as well as multiple criteria. A methodology covering the whole decision-making process, from options generation to options selection, and adopting Saaty's Analytical Hierarchy Process as an operational tool is proposed to deal with such multiple-criteria, multipleagency decision situations. The methodology is intended to integrate the consideration of the relevant criteria, the prevailing environmental and policy factors, and the concerns and objectives of the relevant actors into a unifying decision-making process which strives to facilitate enlightened decision making and to enhance learning and interaction. An extensive assessment of the methodology's feasibility, based on a specific technological project within the Iraqi oil industry is included, and indicates that the methodology should be both useful and implementable.
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Purpose: Energy security is a major concern for India and many rural areas remain un-electrified. Thus, innovations in sustainable technologies to provide energy services are required. Biomass and solar energy in particular are resources that are widely available and underutilised in India. This paper aims to provide an overview of a methodology that was developed for designing and assessing the feasibility of a hybrid solar-biomass power plant in Gujarat. Design/methodology/approach: The methodology described is a combination of engineering and business management studies used to evaluate and design solar thermal collectors for specific applications and locations. For the scenario of a hybrid plant, the methodology involved: the analytical hierarchy process, for solar thermal technology selection; a cost-exergy approach, for design optimisation; quality function deployment, for designing and evaluating a novel collector - termed the elevation linear Fresnel reflector (ELFR); and case study simulations, for analysing alternative hybrid plant configurations. Findings: The paper recommended that for a hybrid plant in Gujarat, a linear Fresnel reflector of 14,000 m2 aperture is integrated with a 3 tonne per hour biomass boiler, generating 815 MWh per annum of electricity for nearby villages and 12,450 tonnes of ice per annum for local fisheries and food industries. However, at the expense of a 0.3 ¢/kWh increase in levelised energy costs, the ELFR can increase savings of biomass (100 t/a) and land (9 ha/a). Research limitations/implications: The research reviewed in this paper is primarily theoretical and further work will need to be undertaken to specify plant details such as piping layout, pump sizing and structure, and assess plant performance during real operational conditions. Originality/value: The paper considers the methodology adopted proved to be a powerful tool for integrating technology selection, optimisation, design and evaluation and promotes interdisciplinary methods for improving sustainable engineering design and energy management. © Emerald Group Publishing Limited.
Resumo:
Presents information on a study which proposed a decision support system (DSS) for a petroleum pipeline route selection with the application of analytical hierarchy process. Factors governing route-selection for cross-country petroleum pipelines; Application of the DSS from an Indian perspective; Cost benefit comparison of the shortest route and the optimal route; Results and findings.
Resumo:
Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.
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Dynamical systems that involve impacts frequently arise in engineering. This Letter reports a study of such a system at microscale that consists of a nonlinear resonator operating with an unilateral impact. The microresonators were fabricated on silicon-on-insulator wafers by using a one-mask process and then characterised by using the capacitively driving and sensing method. Numerical results concerning the dynamics of this vibro-impact system were verified by the experiments. Bifurcation analysis was used to provide a qualitative scenario of the system steady-state solutions as a function of both the amplitude and the frequency of the external driving sinusoidal voltage. The results show that the amplitude of resonant peak is levelled off owing to the impact effect and that the bandwidth of impacting is dependent upon the nonlinearity and the operating conditions.
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In order to survive in the increasingly customer-oriented marketplace, continuous quality improvement marks the fastest growing quality organization’s success. In recent years, attention has been focused on intelligent systems which have shown great promise in supporting quality control. However, only a small number of the currently used systems are reported to be operating effectively because they are designed to maintain a quality level within the specified process, rather than to focus on cooperation within the production workflow. This paper proposes an intelligent system with a newly designed algorithm and the universal process data exchange standard to overcome the challenges of demanding customers who seek high-quality and low-cost products. The intelligent quality management system is equipped with the ‘‘distributed process mining” feature to provide all levels of employees with the ability to understand the relationships between processes, especially when any aspect of the process is going to degrade or fail. An example of generalized fuzzy association rules are applied in manufacturing sector to demonstrate how the proposed iterative process mining algorithm finds the relationships between distributed process parameters and the presence of quality problems.
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The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.
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Motivated by policy goals to develop international research capability and our experiences of collaborative research, we wanted to learn more about the factors that influence success in collaborative research. This article presents a review of the academic literature on collaborative research, focusing on multinational teams doing international comparative research. We address the question ‘what accounts for variation in process and performance of collaborative research projects?’, through 11 themes: context; vision; reward and commitment; leadership; structure; contract; task capability; sociability; communication; finance; rhythm and pace. We then propose an agenda for future research with an analytic framework and, finally, our conclusions.
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This research describes a computerized model of human classification which has been constructed to represent the process by which assessments are made for psychodynamic psychotherapy. The model assigns membership grades (MGs) to clients so that the most suitable ones have high values in the therapy category. Categories consist of a hierarchy of components, one of which, ego strength, is analysed in detail to demonstrate the way it has captured the psychotherapist's knowledge. The bottom of the hierarchy represents the measurable factors being assessed during an interview. A questionnaire was created to gather the identified information and was completed by the psychotherapist after each assessment. The results were fed into the computerized model, demonstrating a high correlation between the model MGs and the suitability ratings of the psychotherapist (r = .825 for 24 clients). The model has successfully identified the relevant data involved in assessment and simulated the decision-making process of the expert. Its cognitive validity enables decisions to be explained, which means that it has potential for therapist training and also for enhancing the referral process, with benefits in cost effectiveness as well as in the reduction of trauma to clients. An adapted version measuring client improvement would give quantitative evidence for the benefit of therapy, thereby supporting auditing and accountability. © 1997 The British Psychological Society.