947 resultados para Fuzzy analytic hierarchy process
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This thesis examined solar thermal collectors for use in alternative hybrid solar-biomass power plant applications in Gujarat, India. Following a preliminary review, the cost-effective selection and design of the solar thermal field were identified as critical factors underlying the success of hybrid plants. Consequently, the existing solar thermal technologies were reviewed and ranked for use in India by means of a multi-criteria decision-making method, the Analytical Hierarchy Process (AHP). Informed by the outcome of the AHP, the thesis went on to pursue the Linear Fresnel Reflector (LFR), the design of which was optimised with the help of ray-tracing. To further enhance collector performance, LFR concepts incorporating novel mirror spacing and drive mechanisms were evaluated. Subsequently, a new variant, termed the Elevation Linear Fresnel Reflector (ELFR) was designed, constructed and tested at Aston University, UK, therefore allowing theoretical models for the performance of a solar thermal field to be verified. Based on the resulting characteristics of the LFR, and data gathered for the other hybrid system components, models of hybrid LFR- and ELFR-biomass power plants were developed and analysed in TRNSYS®. The techno-economic and environmental consequences of varying the size of the solar field in relation to the total plant capacity were modelled for a series of case studies to evaluate different applications: tri-generation (electricity, ice and heat), electricity-only generation, and process heat. The case studies also encompassed varying site locations, capacities, operational conditions and financial situations. In the case of a hybrid tri-generation plant in Gujarat, it was recommended to use an LFR solar thermal field of 14,000 m2 aperture with a 3 tonne 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 increased saving of biomass (100 t/a) and land (9 ha/a). For solar thermal applications in areas with high land cost, the ELFR reduced levelised energy costs. It was determined that off-grid hybrid plants for tri-generation were the most feasible application in India. Whereas biomass-only plants were found to be more economically viable, it was concluded that hybrid systems will soon become cost competitive and can considerably improve current energy security and biomass supply chain issues in India.
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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.
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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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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.
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The enormous potential of cloud computing for improved and cost-effective service has generated unprecedented interest in its adoption. However, a potential cloud user faces numerous risks regarding service requirements, cost implications of failure and uncertainty about cloud providers' ability to meet service level agreements. These risks hinder the adoption of cloud. We extend the work on goal-oriented requirements engineering (GORE) and obstacles for informing the adoption process. We argue that obstacles prioritisation and their resolution is core to mitigating risks in the adoption process. We propose a novel systematic method for prioritising obstacles and their resolution tactics using Analytical Hierarchy Process (AHP). We provide an example to demonstrate the applicability and effectiveness of the approach. To assess the AHP choice of the resolution tactics we support the method by stability and sensitivity analysis. Copyright 2014 ACM.
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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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Egyes alternatívák, forgatókönyvek, technológiák stb. fenntarthatóságának értékelése – definíciószerűen többdimenziós probléma. A megfelelő alternatíva kiválasztásánál ugyanis a döntéshozóknak egyszerre kell figyelembe venniük környezetvédelmi, gazdasági és társadalmi szempontokat. Az ilyen döntéseket támogathatják többszempontú döntéshozatali modellek. A tanulmány hét többszempontú döntési módszertan (MAU, AHP, ELECTRE, PROMETHEE, REGIME, NAIADE és ideális-referencia pont) alkalmazhatóságát vizsgálja részvételi körülmények között. Az utóbbi évek e témában publikált esettanulmányait áttekintve megállapítható, hogy egyik módszer sem dominálja a többit, azok különböző feltételek mellett eltérő sikerrel használhatók. Ennek ellenére a különböző technikák kombinációjával előállíthatunk olyan eljárásokat, melyekkel az egyes módszerek előnyeit még jobban kiaknázhatjuk. ________ Measuring and comparing the sustainability of certain actions, scenarios, technologies, etc. – by definition – is a multidimensional problem. Decision makers must consider environmental, economic and social aspects when choosing an alternative course of action. Such decisions can be aided by multi-criteria decision analysis (MCDA). In this paper participatory seven different MCDA methodologies are investigated (MAU, the Analytic Hierarchic Process (AHP), the ELECTRE, PROMETHEE, REGIME, and NAIADE methods and the “Ideal and reference point” approaches). It is based on a series of reports, in which more than 30 real world case studies focusing on participatory MCDA were reviewed. It is emphasized that there is no “best” choice from the list of MCDA techniques, but some methods fit certain decision problems more than others. However, with the combination of these methodologies some complementary benefits of the different techniques can be exploited.
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A fenntarthatóság értékelése definíciószerűen többdimenziós probléma. A megfelelő alternatíva, forgatókönyv, eljárás stb. kiválasztásakor ugyanis a döntéshozóknak egyszerre kell figyelembe venniük környezetvédelmi, gazdasági és társadalmi szempontokat. Az ilyen döntéseket alátámaszthatják a több szempontú döntéshozatali modellek. A tanulmány a több szempontú döntési eljárások közül a legfontosabb hétnek az alkalmazhatóságát vizsgálja részvételi körülmények között. Az utóbbi évek e témában publikált esettanulmányainak áttekintésével megállapítható, hogy egyik módszer sem uralja a többit, azok különböző feltételek mellett eltérő sikerrel használhatók. Ennek ellenére a különböző módszerek kombinációjával végrehajthatunk olyan eljárásokat, amelyekkel az egyes módszerek előnyeit még jobban kiaknázhatjuk. ________ Measuring and comparing the sustainability of certain actions, scenarios, technologies, etc. is by definition a multidimensional problem. Decision-makers must consider environmental, economic and social aspects when choosing an alternative course of action. Such decisions can be aided by multi-criteria decision analysis (MCDA). This paper investigates seven different MCDA methodologies: MAU, the Analytic Hierarchic Process (AHP), the ELECTRE, PROMETHEE, REGIME, and NAIADE methods, and "Ideal and reference point" approaches). It is based on a series of reports in which over 30 real-world case studies focusing on participatory MCDA were reviewed. It is stressed, however, that there is no "best" choice in the list of MCDA techniques. Some methods fit certain decision problems better than others. Nonetheless, some complementary benefits of the different techniques can be exploited by combining these methodologies.
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One of the global phenomena with threats to environmental health and safety is artisanal mining. There are ambiguities in the manner in which an ore-processing facility operates which hinders the mining capacity of these miners in Ghana. These problems are reviewed on the basis of current socio-economic, health and safety, environmental, and use of rudimentary technologies which limits fair-trade deals to miners. This research sought to use an established data-driven, geographic information (GIS)-based system employing the spatial analysis approach for locating a centralized processing facility within the Wassa Amenfi-Prestea Mining Area (WAPMA) in the Western region of Ghana. A spatial analysis technique that utilizes ModelBuilder within the ArcGIS geoprocessing environment through suitability modeling will systematically and simultaneously analyze a geographical dataset of selected criteria. The spatial overlay analysis methodology and the multi-criteria decision analysis approach were selected to identify the most preferred locations to site a processing facility. For an optimal site selection, seven major criteria including proximity to settlements, water resources, artisanal mining sites, roads, railways, tectonic zones, and slopes were considered to establish a suitable location for a processing facility. Site characterizations and environmental considerations, incorporating identified constraints such as proximity to large scale mines, forest reserves and state lands to site an appropriate position were selected. The analysis was limited to criteria that were selected and relevant to the area under investigation. Saaty’s analytical hierarchy process was utilized to derive relative importance weights of the criteria and then a weighted linear combination technique was applied to combine the factors for determination of the degree of potential site suitability. The final map output indicates estimated potential sites identified for the establishment of a facility centre. The results obtained provide intuitive areas suitable for consideration
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Il presente elaborato si propone di analizzare la tematica della sostenibilità nella gestione della Supply Chain, con particolare attenzione alla misurazione delle performance attraverso indicatori KPI e modelli multidimensionali. Nella prima sezione, dopo un’introduzione sul tema dello sviluppo sostenibile, si offre una descrizione dello scenario attuale e degli approcci alla sostenibilità, evidenziandone i principi guida e le sfide future, mentre in seguito vengono analizzate le pressioni esercitate dagli stakeholder per l’implementazione di pratiche sostenibili. La seconda porzione dell’elaborato è incentrata sull’introduzione della sostenibilità nel Supply Chain Management, caratterizzandone l’evoluzione dalla tradizionale gestione della catena di fornitura e mettendone in luce opportunità e barriere. Successivamente, la terza parte si propone di entrare nel dettaglio in merito alle pratiche adottabili nella filiera finalizzate all’implementazione di un management sostenibile, proponendo un modello concettuale per l’analisi delle varie attività, dalla progettazione di prodotto fino alla logistica inversa. Un’ulteriore tematica approfondita è rappresentata dall’impatto di queste pratiche sostenibili sulle performance economiche aziendali, proponendo diversi approcci. Nell’ultima sezione dell’elaborato il focus è incentrato sulla misurazione delle performance di sostenibilità, dove ne vengono indagate opportunità e difficoltà, proponendo in seguito un modello teorico. Contestualmente vengono quindi esposti diversi KPI e modelli multidimensionali, i quali, con modalità e prospettive diverse, contribuiscono alla misurazione delle prestazioni di sostenibilità: in particolare viene fatto riferimento agli indici caratteristici del GRI e all’utilizzo combinato della balanced scorecard e dell’analytic hierarchy process.
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The study of Quality of Life (Qol) has been conducted on various scales throughout the years with focus on assessing overall quality of living amongst citizens. The main focus in these studies have been on economic factors, with the purpose of creating a Quality of Life Index (QLI).When it comes down to narrowing the focus to the environment and factors like Urban Green Spaces (UGS) and air quality the topic gets more focused on pointing out how each alternative meets this certain criteria. With the benefits of UGS and a healthy environment in focus a new Environmental Quality of Life Index (EQLI) will be proposed by incorporating Multi Criteria Analysis (MCA) and Geographical Information Systems (GIS). Working with MCA on complex environmental problems and incorporating it with GIS is a challenging but rewarding task, and has proven to be an efficient approach among environmental scientists. Background information on three MCA methods will be shown: Analytical Hierarchy Process (AHP), Regime Analysis and PROMETHEE. A survey based on a previous study conducted on the status of UGS within European cities was sent to 18 municipalities in the study area. The survey consists of evaluating the current status of UGS as well as planning and management of UGS with in municipalities for the purpose of getting criteria material for the selected MCA method. The current situation of UGS is assessed with use of GIS software and change detection is done on a 10 year period using NDVI index for comparison purposes to one of the criteria in the MCA. To add to the criteria, interpolation of nitrogen dioxide levels was performed with ordinary kriging and the results transformed into indicator values. The final outcome is an EQLI map with indicators of environmentally attractive municipalities with ranking based on predefinedMCA criteria using PROMETHEE I pairwise comparison and PROMETHEE II complete ranking of alternatives. The proposed methodology is applied to Lisbon’s Metropolitan Area, Portugal.
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Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.
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Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.
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The present study—employing psychometric meta-analysis of 92 independent studies with sample sizes ranging from 26 to 322 leaders—examined the relationship between EI and leadership effectiveness. Overall, the results supported a linkage between leader EI and effectiveness that was moderate in nature (ρ = .25). In addition, the positive manifold of the effect sizes presented in this study, ranging from .10 to .44, indicate that emotional intelligence has meaningful relations with myriad leadership outcomes including effectiveness, transformational leadership, LMX, follower job satisfaction, and others. Furthermore, this paper examined potential process mechanisms that may account for the EI-leadership effectiveness relationship and showed that both transformational leadership and LMX partially mediate this relationship. However, while the predictive validities of EI were moderate in nature, path analysis and hierarchical regression suggests that EI contributes less than or equal to 1% of explained variance in leadership effectiveness once personality and intelligence are accounted for. ^