7,735 research outputs found

    A fuzzy-QFD approach for the enhancement of work equipment safety: a case study in the agriculture sector

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    The paper proposes a design for safety methodology based on the use of the Quality Function Deployment (QFD) method, focusing on the need to identify and analyse risks related to a working task in an effective manner, i.e. considering the specific work activities related to such a task. To reduce the drawbacks of subjectivity while augmenting the consistency of judgements, the QFD was augmented by both the Delphi method and the fuzzy logic approach. To verify such an approach, it was implemented through a case study in the agricultural sector. While the proposed approach needs to be validated through further studies in different contexts, its positive results in performing hazard analysis and risk assessment in a comprehensive and thorough manner can contribute practically to the scientific knowledge on the application of QFD in design for safety activities

    Tractor Lifetime Assessment Analysis

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    In this paper, two different approaches in analyzing the tractor lifetime assessment are presented. The first one is based on reliability theory and the other one is based on the relevant experience that was implemented in the ASABE standards. In this way, the dependence of tractor reliability and lifetime on working conditions is presented through two models verified in the paper. Tractors from two different producers were analyzed. Experimental data were collected during the tractor working engagement at the fields of Agricultural Corporation Belgrade (ACB). Analyzing the obtained data it is possible to find the mismanagement in the tractor usage. Removing them it is possible to extend the period of tractor utilization. In this way the overall organization of tractor- machinery system on a farm can significantly be improved

    A Modelling Approach for Evaluating Agri-Environmental Policies at Sector Level

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    This paper presents a new approach to evaluate the cost effectiveness of agri-environmental policies at sector level. Policy uptake, cumulative environmental effects and public expenditure are identified as the main determinants of cost-effectiveness. On the basis of the sector-consistent, comparative-static, farm group model FARMIS, the determinants of policy cost-effectiveness at sector level are addressed. Firstly, intensity levels for the FARMIS activities are defined in order to model uptake of agri-environmental policies with FARMIS, secondly, life-cycle assessment data is attached to these intensity levels to determine environmental effects of the policies and thirdly, public expenditure is calculated under consideration of transaction costs. This paper concludes delineating the strengths and limitations of the approach

    Hybrid linear programming to estimate CAP impacts of flatter rates and environmental top-ups

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    This paper examines evolutions of the Common Agricultural Policy (CAP) decoupling regime and their impacts on Greek arable agriculture. Policy analysis is performed by using mathematical programming tools. Taking into account increasing uncertainty, we assume that farmers perceive gross margin in intervals rather than as expected crisp values. A bottom-up hybrid model accommodates both profit maximizing and risk prudent attitudes in order to accurately assess farmers’ response. Marginal changes to crop plans are expected so that flatter single payment rates cause significant changes in incomes and subsidies. Nitrogen reduction incentives result in moderate changes putting their effectiveness in question.Interval Linear Programming, Min-Max Regret, Common Agricultural Policy, Arable cropping, Greece

    Maintenance management of tractors and agricultural machinery: Preventive maintenance systems

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    Agricultural machinery maintenance has a crucial role for successful agricultural production.  It aims at guaranteeing the safety of operations and availability of machines and related equipment for cultivation operation.  Moreover, it is one major cost for agriculture operations.  Thus, the increased competition in agricultural production demands maintenance improvement, aiming at the reduction of maintenance expenditures while keeping the safety of operations.  This issue is addressed by the methodology presented in this paper.  So, the aim of this paper was to give brief introduction to various preventive maintenance systems specially condition-based maintenance (CBM) techniques, selection of condition monitoring techniques and understanding of condition monitoring (CM) intervals, advancement in CBM, standardization of CBM system, CBM approach on agricultural machinery, advantages and disadvantages of CBM.  The first step of the methodology consists of concept condition monitoring approach for the equipment preventive maintenance; its purpose is the identification of state-of-the-art in the CM of agricultural machinery, describing the different maintenance strategies, CM techniques and methods.  The second step builds the signal processing procedure for extracting information relevant to targeted failure modes.   Keywords: agricultural machinery, fault detection, fault diagnosis, signal processing, maintenance managemen

    Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

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    As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability

    Data-Driven Simulator: Redesign of Chickpea Harvester Reels

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    Conventional redesign methodologies applied on the grain harvester headers for the mechanical harvesting of chickpeas cause its progress to not be as rapid and technological. This paper presents a hybrid modeling-optimization methodology to design harvester reels for efficient chickpea harvesting. The five fabricated headers were tested in both real and virtual modeling environments to optimize the operational parameters of the reel for minimum losses. Harvesting losses data gathered from chickpea fields over ten years of trials were fed into a fuzzy logic model, which in turn was merged with simulated annealing to develop a simulator. To this end, simulated annealing was used to produce combinations of reel diameter and number of bats, to be fed into the fuzzy model until achieving a minimum harvesting loss. The proposed model predicts the reel structure measured in-field evaluation, which fits well with the previously established mathematical model. A significant improvement in harvesting performance, 71% pod harvesting, validates the benefits of the proposed fuzzy-simulated annealing approach to optimize the design of grain harvester headers

    Application Of Intuitionistic Fuzzy Topsis Model For Troubleshooting An Offshore Patrol Boat Engine

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    In this paper, an Intuitionistic Fuzzy TOPSIS model which is based on a score function is proposed for detecting the root cause of failure in an Offshore Boat engine, using groups of expert’s opinions. The study which has provided an alternative approach for failure mode identification and analysis in machines, addresses the machine component interaction failures which is a limitation in existing methods. The results from the study show that although early detection of failures in engines is quite difficult to identify due to the dependency of their systems from each other. However, with the Intuitionistic Fuzzy TOPSIS model which is based on an improved score function such faults/failures are easily detected using expert’s based opinions

    Biodiesel and social inclusion: a fuzzy set and regression analysis in the north of Brazil

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    After the launch of Brazilian Biodiesel use and production Program (PNPB) in 2004, the oil seed production became an economic alternative for family farmers since they might have the chance to improve their income and supply biodiesel enterprises with raw material. Theoretically speaking this picture is easy to draw, but few recent little scientific research was carried out aiming at identifying the socio-economic profile of farmers that are being included in the Brazilian biodiesel chain. Thus, this study aims to assess the links between the family farmers’ living standards and the adoption of oil seed activity. Thus, an analysis of Jatropha curcas and Ricinus communis small-scale seed production was done in the Tocantins state, located in the north of Brazil. A fuzzy set theory was applied to construct deprivation indicators based on living standard criteria and a nonlinear probit model was formulated to analyze the inclusion of poor families in the biodiesel chain. The preliminary results point towards a positive relationship between degree of deprivation and adoption of oil seed activity in the case of Ricinus communis system production and a negative relationship in the case of Jatropha curcas system
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