975 resultados para Stage efficiency


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This industrial based research project was undertaken for British Leyland and arose as a result of poor system efficiency on the Maxi and Marina vehicle body build lines. The major factors in the deterioration of system efficiency were identified as: a) The introduction of a 'Gateline' system of vehicle body build. b) The degeneration of a newly introduced measured daywork payment scheme. By relating the conclusions of past work on payment systems to the situation at Cowley, it was concluded that a combination of poor industrial relations and a lack of managerial control had caused the measured daywork scheme to degenerate into a straightforward payment for time at work. This ellminated the monetary incentive to achieve schedule with the consequence that both inefficiency and operating costs increased. To analyse further the cause of inefficiency, a study of Marina gateline stoppage logs was carried out. This revealed that poor system efficiency on the gateline was caused more by the nature of its design than poor reliability on individual items of' plant. The consideration given to system efficiency at the design stage was found to be negligible, the main obstacles being: a) A lack of understanding pertaining to the influence of certain design factors on the efficiency of a production line. b) The absence of data and techniques to predict system efficiency at the design stage. To remedy this situation, a computer simulation study of' the design factors was carried out from which relationships with system efficiency were established and empirical efficiency equations developed. Sets of tables were compiled from the equations and efficiency data relevant to vehicle body building established from the gateline stoppage logs. Computer simulation, the equations and the tables,when used in conjunction. with good efficiency data, are shown to be accurate methods of predicting production line system.efficiency.

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The EU intends to increase the fraction of fuels from biogenic energy sources from 2% in 2005 to 8% in 2020. This means a minimum of 30 million TOE/a of fuels from biomass. This makes technical-scale generation of syngas from high-grade biomass, e.g. straw, hay, bark, or paper/cardboard waste, and the production of synthetic fuels by Fischer-Tropsch (FT) synthesis highly attractive. The BTL concept (Biomass to Liquids) of the Karlsruhe Research Center, labeled bioliq, focuses on this challenge by locally concentrating the biomass energy content by fast pyrolysis in a coke/oil slurry followed by slurry conversion to syngas in a central entrained flow gasifier at 1200C and pressures above 4MPa. FT synthesis generates intermediate products for synthetic fuels. To prevent the sensitive catalysts from being poisoned the syngas must be free of tar and particulates. Trace concentrations of H2S, COS, CS2, HCl, NH3, and HCN must be on the order of a few ppb. Moreover, maximum conversion efficiency will be achieved by cleaning the gas above the synthesis conditions. (T>350C, P>4MPa). The concept of an innovative dry HTHP syngas cleaning process is presented. Based on HT particle filtration and suitable sorption and catalysis processes for the relevant contaminants, an overall concept will be derived, which leads to a syngas quality required for FT synthesis in only two combined stages. Results of filtration experiments on a pilot scale are presented. The influence of temperature on the separation and conversion, respectively, of particulates and gaseous contaminants is discussed on the basis of experimental results obtained on a laboratory and pilot scale. Extensive studies of this concept are performed in a scientific network comprising the Karlsruhe Research Center and five universities; funding is provided by the Helmholtz Association of National Research Centers in Germany.

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Financial institutes are an integral part of any modern economy. In the 1970s and 1980s, Gulf Cooperation Council (GCC) countries made significant progress in financial deepening and in building a modern financial infrastructure. This study aims to evaluate the performance (efficiency) of financial institutes (banking sector) in GCC countries. Since, the selected variables include negative data for some banks and positive for others, and the available evaluation methods are not helpful in this case, so we developed a Semi Oriented Radial Model to perform this evaluation. Furthermore, since the SORM evaluation result provides a limited information for any decision maker (bankers, investors, etc...), we proposed a second stage analysis using classification and regression (C&R) method to get further results combining SORM results with other environmental data (Financial, economical and political) to set rules for the efficient banks, hence, the results will be useful for bankers in order to improve their bank performance and to the investors, maximize their returns. Mainly there are two approaches to evaluate the performance of Decision Making Units (DMUs), under each of them there are different methods with different assumptions. Parametric approach is based on the econometric regression theory and nonparametric approach is based on a mathematical linear programming theory. Under the nonparametric approaches, there are two methods: Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). While there are three methods under the parametric approach: Stochastic Frontier Analysis (SFA); Thick Frontier Analysis (TFA) and Distribution-Free Analysis (DFA). The result shows that DEA and SFA are the most applicable methods in banking sector, but DEA is seem to be most popular between researchers. However DEA as SFA still facing many challenges, one of these challenges is how to deal with negative data, since it requires the assumption that all the input and output values are non-negative, while in many applications negative outputs could appear e.g. losses in contrast with profit. Although there are few developed Models under DEA to deal with negative data but we believe that each of them has it is own limitations, therefore we developed a Semi-Oriented-Radial-Model (SORM) that could handle the negativity issue in DEA. The application result using SORM shows that the overall performance of GCC banking is relatively high (85.6%). Although, the efficiency score is fluctuated over the study period (1998-2007) due to the second Gulf War and to the international financial crisis, but still higher than the efficiency score of their counterpart in other countries. Banks operating in Saudi Arabia seem to be the highest efficient banks followed by UAE, Omani and Bahraini banks, while banks operating in Qatar and Kuwait seem to be the lowest efficient banks; this is because these two countries are the most affected country in the second Gulf War. Also, the result shows that there is no statistical relationship between the operating style (Islamic or Conventional) and bank efficiency. Even though there is no statistical differences due to the operational style, but Islamic bank seem to be more efficient than the Conventional bank, since on average their efficiency score is 86.33% compare to 85.38% for Conventional banks. Furthermore, the Islamic banks seem to be more affected by the political crisis (second Gulf War), whereas Conventional banks seem to be more affected by the financial crisis.

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This paper examines the efficiency of public sector expenditures and foreign aid at achieving social sector outcomes in Small Island Developing States (SIDS). Efficiency is estimated using a Stochastic Production Function (SPF) approach and panel data since 1990. A second stage of the analysis examines the determinants of efficiency. Results indicate that the efficiency of aid and public sectors at improving life expectancy has deteriorated during the 1990s but efficiency at improving school enrolments has increased. Higher levels of governance are associated with higher efficiency. There is also evidence to suggest that efficiency is lower in SIDS, as well as in Sub-Saharan Africa.

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Grape is one of the world's largest fruit crops with approximately 67.5 million tonnes produced each year and energy is an important element in modern grape productions as it heavily depends on fossil and other energy resources. Efficient use of these energies is a necessary step toward reducing environmental hazards, preventing destruction of natural resources and ensuring agricultural sustainability. Hence, identifying excessive use of energy as well as reducing energy resources is the main focus of this paper to optimize energy consumption in grape production.In this study we use a two-stage methodology to find the association of energy efficiency and performance explained by farmers' specific characteristics. In the first stage a non-parametric Data Envelopment Analysis is used to model efficiencies as an explicit function of human labor, machinery, chemicals, FYM (farmyard manure), diesel fuel, electricity and water for irrigation energies. In the second step, farm specific variables such as farmers' age, gender, level of education and agricultural experience are used in a Tobit regression framework to explain how these factors influence efficiency of grape farming.The result of the first stage shows substantial inefficiency between the grape producers in the studied area while the second stage shows that the main difference between efficient and inefficient farmers was in the use of chemicals, diesel fuel and water for irrigation. The use of chemicals such as insecticides, herbicides and fungicides were considerably less than inefficient ones. The results revealed that the more educated farmers are more energy efficient in comparison with their less educated counterparts. © 2013.

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The influence of IT investment on hospital efficiency and quality are of great interest to healthcare executives as well as insurers. Few studies have examined how IT investments influence both efficiency and quality or whether there is an optimal IT investment level that influences both in the desired direction. Decision makers in healthcare wonder if there are tradeoffs between their pursuit of hospital operational efficiency and quality. Our study involving a 2-stage double bootstrap DEA analysis of 187 US hospitals over 2. years found direct effects of IT investment upon service quality and a moderating effect of quality upon operational efficiency. Further, our findings indicate a U-shaped relationship between IT investments and operational efficiency suggesting that IT investments have diminishing returns beyond a certain point.

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Microfinance has been developed as alternative solution for global poverty alleviation effort in the last 30 years. Microfinance institution (MFI) has unique characteristic wherein they face double bottom line objectives of outreach to the poor and financial sustainability. This study proposes a two-stage analysis to measure Islamic Microfinance institutions (IMFIs) performance by comparing them to conventional MFIs. First, we develop a Data Envelopment Analysis (DEA) framework to measure MFIs' efficiency in its double bottom line objectives, i.e. in terms of social and financial efficiency. In the second stage non-parametric tests are used to compare the performance and identify factors that contribute to the efficiency of IMFIs and MFIs.

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Radio frequency identification (RFID) technology has gained increasing popularity in businesses to improve operational efficiency and maximise costs saving. However, there is a gap in the literature exploring the enhanced use of RFID to substantially add values to the supply chain operations, especially beyond what the RFID vendors could offer. This paper presents a multi-agent system, incorporating RFID technology, aimed at fulfilling the gap. The system is developed to model supply chain activities (in particular, logistics operations) and is comprised of autonomous and intelligent agents representing the key entities in the supply chain. With the advanced characteristics of RFID incorporated, the agent system examines ways logistics operations (i.e. distribution network) particular) can be efficiently reconfigured and optimised in response to dynamic changes in the market, production and at any stage in the supply chain. © 2012 IEEE.

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Two-stage data envelopment analysis (DEA) efficiency models identify the efficient frontier of a two-stage production process. In some two-stage processes, the inputs to the first stage are shared by the second stage, known as shared inputs. This paper proposes a new relational linear DEA model for dealing with measuring the efficiency score of two-stage processes with shared inputs under constant returns-to-scale assumption. Two case studies of banking industry and university operations are taken as two examples to illustrate the potential applications of the proposed approach.

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The objective of this project is to design a new desalination system with energy efficiency approaching the theoretical thermodynamic limit—even at high recovery ratio. The system uses reverse osmosis (RO) and a batch principle of operation to overcome the problem of concentration factor which prevents continuous-flow RO systems from ever reaching this limit and thus achieving the minimum possible specific energy consumption, SEC. Batch operation comprises a cycle in three phases: pressurisation, purge, and refill. Energy recovery is inherent to the design. Unlike in closed-circuit desalination (CCD), no feedwater is added to the pressure circuit during the pressurisation phase. The batch configuration is compared to standard configurations such as continuous single-stage RO (with energy recovery) and CCD. Theoretical analysis has shown that the new system is able to use 33% less energy than CCD at a recovery ratio of 80%. A prototype has been constructed using readily available parts and tested with feedwater salinities and recovery ratios ranging from 2,000 to 5,000 ppm and 17.2–70.6%, respectively. Results compare very well against the standard configurations. For example, with feedwater containing 5,000 ppm NaCl and recovery ratio of 69%, a hydraulic SEC of 0.31 kWh/m3 was obtained—better than the minimum theoretically possible with a single-stage continuous flow system with energy recovery device.

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This dissertation analyzes hospital efficiency using various econometric techniques. The first essay provides additional and recent evidence to the presence of contract management behavior in the U.S. hospital industry. Unlike previous studies, which focus on either an input-demand equation or the cost function of the firm, this paper estimates the two jointly using a system of nonlinear equations. Moreover, it addresses the longitudinal problem of institutions adopting contract management in different years, by creating a matched control group of non-adopters with the same longitudinal distribution as the group under study. The estimation procedure then finds that labor, and not capital, is the preferred input in U.S. hospitals regardless of managerial contract status. With institutions that adopt contract management benefiting from lower labor inefficiencies than the simulated non-contract adopters. These results suggest that while there is a propensity for expense preference behavior towards the labor input, contract managed firms are able to introduce efficiencies over conventional, owner controlled, firms. Using data for the years 1998 through 2007, the second essay investigates the production technology and cost efficiency faced by Florida hospitals. A stochastic frontier multiproduct cost function is estimated in order to test for economies of scale, economies of scope, and relative cost efficiencies. The results suggest that small-sized hospitals experience economies of scale, while large and medium sized institutions do not. The empirical findings show that Florida hospitals enjoy significant scope economies, regardless of size. Lastly, the evidence suggests that there is a link between hospital size and relative cost efficiency. The results of the study imply that state policy makers should be focused on increasing hospital scale for smaller institutions while facilitating the expansion of multiproduct production for larger hospitals. The third and final essay employs a two staged approach in analyzing the efficiency of hospitals in the state of Florida. In the first stage, the Banker, Charnes, and Cooper model of Data Envelopment Analysis is employed in order to derive overall technical efficiency scores for each non-specialty hospital in the state. Additionally, input slacks are calculated and reported in order to identify the factors of production that each hospital may be over utilizing. In the second stage, we employ a Tobit regression model in order to analyze the effects a number of structural, managerial, and environmental factors may have on a hospital’s efficiency. The results indicated that most non-specialty hospitals in the state are operating away from the efficient production frontier. The results also indicate that the structural make up, managerial choices, and level of competition Florida hospitals face have an impact on their overall technical efficiency.

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Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies.^ The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task.^ This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation. ^

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Because of high efficacy, long lifespan, and environment-friendly operation, LED lighting devices become more and more popular in every part of our life, such as ornament/interior lighting, outdoor lightings and flood lighting. The LED driver is the most critical part of the LED lighting fixture. It heavily affects the purchasing cost, operation cost as well as the light quality. Design a high efficiency, low component cost and flicker-free LED driver is the goal. The conventional single-stage LED driver can achieve low cost and high efficiency. However, it inevitably produces significant twice-line-frequency lighting flicker, which adversely affects our health. The conventional two-stage LED driver can achieve flicker-free LED driving at the expenses of significantly adding component cost, design complexity and low the efficiency. The basic ripple cancellation LED driving method has been proposed in chapter three. It achieves a high efficiency and a low component cost as the single-stage LED driver while also obtaining flicker-free LED driving performance. The basic ripple cancellation LED driver is the foundation of the entire thesis. As the research evolving, another two ripple cancellation LED drivers has been developed to improve different aspects of the basic ripple cancellation LED driver design. The primary side controlled ripple cancellation LED driver has been proposed in chapter four to further reduce cost on the control circuit. It eliminates secondary side compensation circuit and an opto-coupler in design while at the same time maintaining flicker-free LED driving. A potential integrated primary side controller can be designed based on the proposed LED driving method. The energy channeling ripple cancellation LED driver has been proposed in chapter five to further reduce cost on the power stage circuit. In previous two ripple cancellation LED drivers, an additional DC-DC converter is needed to achieve ripple cancellation. A power transistor has been used in the energy channeling ripple cancellation LED driving design to successfully replace a separate DC-DC converter and therefore achieved lower cost. The detailed analysis supports the theory of the proposed ripple cancellation LED drivers. Simulation and experiment have also been included to verify the proposed ripple cancellation LED drivers.

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This experiment used a modified go/no-go paradigm to investigate the processes by which response inhibition becomes more efficient during mid-childhood. The novel task, which measured trials on which a response was initiated but not completed, was sensitive to developmental changes in response inhibition. The effect of inducing time pressure by narrowing allowable response time was also examined. While increasing time pressure did not reduce the inhibitory demands of the task for either age group, older children (aged 9-to-11 years) were able to inhibit their responses at an earlier stage of movement than younger children (aged 5-to-7 years). This shows that as children get older they become more efficient at controlling their behaviour which drives developmental improvements in response inhibition.