961 resultados para M OPERATION


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An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

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post-deadline paper

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Mathematical models of straight-grate pellet induration processes have been developed and carefully validated by a number of workers over the past two decades. However, the subsequent exploitation of these models in process optimization is less clear, but obviously requires a sound understanding of how the key factors control the operation. In this article, we show how a thermokinetic model of pellet induration, validated against operating data from one of the Iron Ore Company of Canada (IOCC) lines in Canada, can be exploited in process optimization from the perspective of fuel efficiency, production rate, and product quality. Most existing processes are restricted in the options available for process optimization. Here, we review the role of each of the drying (D), preheating (PH), firing (F), after-firing (AF), and cooling (C) phases of the induration process. We then use the induration process model to evaluate whether the first drying zone is best to use on the up- or down-draft gas-flow stream, and we optimize the on-gas temperature profile in the hood of the PH, F, and AF zones, to reduce the burner fuel by at least 10 pct over the long term. Finally, we consider how efficient and flexible the process could be if some of the structural constraints were removed (i.e., addressed at the design stage). The analysis suggests it should be possible to reduce the burner fuel lead by 35 pct, easily increase production by 5+ pct, and improve pellet quality.

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This paper considers a variant of the classical problem of minimizing makespan in a two-machine flow shop. In this variant, each job has three operations, where the first operation must be performed on the first machine, the second operation can be performed on either machine but cannot be preempted, and the third operation must be performed on the second machine. The NP-hard nature of the problem motivates the design and analysis of approximation algorithms. It is shown that a schedule in which the operations are sequenced arbitrarily, but without inserted machine idle time, has a worst-case performance ratio of 2. Also, an algorithm that constructs four schedules and selects the best is shown to have a worst-case performance ratio of 3/2. A polynomial time approximation scheme (PTAS) is also presented.

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Purpose: To study the impact of powder flow properties on dosator filling systems, with particular focus on improvements in dose weight accuracy and repeatability. Method: This study evaluates a range of critical powder flow properties such as: flow function, cohesion, wall friction, adhesion to wall surfaces, density/compressibility data, stress ratio “K” and gas permeability. The characterisations of the powders considered in this study were undertaken using an annular shear cell using a sample size of 0.5 litres. This tester also incorporated the facility to measure bed expansion during shear in addition to contraction under consolidation forces. A modified Jenike type linear wall friction tester was used to develop the failure loci for the powder sample in conjunction with multiple wall samples (representing a variety of material types and surface finishes). Measurements of the ratio of applied normal stress versus lateral stress were determined using a piece of test equipment specifically designed for the purpose. Results: The correct characterisation of powders and the incorporation of this data into the design of process equipment are recognised as critical for reliable and accurate operation. An example of one aspect of this work is the stress ratio “K”. This characteristic is not well understood or correctly interpreted in many cases – despite its importance. Fig 1 [Omitted] (illustrates a sample of test data. The slope of the line gives the stress ratio in a uniaxial compaction system – indicating the behaviour of the material under compaction during dosing processes. Conclusions: A correct assessment of the bulk powder properties for a given formulation can allow prediction of: cavity filling behaviour (and hence dosage), efficiency of release from dosator, and strength and stability of extruded dose en route to capsule filling Influences over the effectiveness of dosator systems have been shown to be impacted upon by: bed pre-compaction history, gas permeability in the bed (with respect to local density effects), and friction effects for materials of construction for dosators

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Purpose: To develop an improved mathematical model for the prediction of dose accuracy of Dosators - based upon the geometry of the machine in conjunction with measured flow properties of the powder. Methods: A mathematical model has been created, based on a analytical method of differential slices - incorporating measured flow properties. The key flow properties of interest in this investigation were: flow function, effective angle of wall friction, wall adhesion, bulk density, stress ratio K and permeability. To simulate the real process and (very importantly) validate the model, a Dosator test-rig has been used to measure the forces acting on the Dosator during the filling stage, the force required to eject the dose and the dose weight. Results: Preliminary results were obtained from the Dosator test-rig. Figure 1 [Omitted] shows the dose weight for different depths to the bottom of the powder bed at the end of the stroke and different levels of pre-compaction of the powder bed. A strong influence over dose weight arising from the proximity between the Dosator and the bottom of the powder bed at the end of the stroke and the conditions of the powder bed has been established. Conclusions: The model will provide a useful tool to predict dosing accuracy and, thus, optimise the future design of Dosator based equipment technology – based on measured bulk properties of the powder to be handled. Another important factor (with a significant influence) on Dosator processes, is the condition of the powder bed and the clearance between the Dosator and the bottom of the powder bed.

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Presented is a study that expands the body of knowledge on the effect of in-cycle speed fluctuations on performance of small engines. It uses the engine and drivetrain models developed previously by Callahan, et al. (1) to examine a variety of engines. The predicted performance changes due to drivetrain effects are shown in each case, and conclusions are drawn from those results. The single-cylinder, high performance four-stroke engine showed significant changes in predicted performance compared to the prediction with zero speed fluctuation in the model. Measured speed fluctuations from a firing Yamaha YZ426 engine were applied to the simulation in addition to data from a simple free mass model. Both methods predicted similar changes in performance. The multiple-cylinder, high performance two-stroke engine also showed significant changes in performance depending on the firing configuration. With both engines, the change in performance diminished with increasing mean engine speed. The low output, single-cylinder two-stroke engine simulation showed only a negligible change in performance, even with high amplitude speed fluctuations. Because the torque versus engine speed characteristic for the engine was so flat, this was expected. The cross-charged, multi-cylinder two-stroke engine also showed only a negligible change in performance. In this case, the combination of a relatively high inertia rotating assembly and the multiple cylinder firing events within the revolution smoothing the torque pulsations reduced the speed fluctuation amplitude itself.

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Cross-border (North/South) co-operation between the Republic of Ireland and Northern Ireland was an indelible feature of the form of governance provided by the Belfast Good Friday Agreement (1998). Previous efforts to establish North/South co-operation had all foundered but the establishment and initial operation of the Agreement's cross-border institutions proved to be uncontroversial. However, during its implementation, other areas of the Agreement gave Ulster unionists more pressing cause for concern. These areas of concern included the release of paramilitary prisoners, police reform, the 'decommissioning' of Irish Republican Army (IRA) weaponry, and the unionist perception that the 'Britishness of Northern Ireland' was being actively eroded. These concerns served to emphasise and strengthen political and cultural borders between communities at a regional and local level within Northern Ireland. They also threatened the pro-Agreement unionists' contestation of unionist ideological orthodoxy, a contestation that was undertaken in an attempt to adapt the Ulster unionist identity to the shifting thresholds of the state.

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Received for publication October 31, 2002. Design and operation of Fe0 permeable reactive barriers (PRBs) can be improved by understanding the long-term mineralogical transformations that occur within PRBs. Changes in mineral precipitates, cementation, and corrosion of Fe0 filings within an in situ pilot-scale PRB were examined after the first 30 months of operation and compared with results of a previous study of the PRB conducted 15 months earlier using X-ray diffraction and scanning electron microscopy employing energy dispersive X-ray and backscatter electron analyses. Iron (oxy)hydroxides, aragonite, and maghemite and/or magnetite occurred throughout the cores collected 30 mo after installation. Goethite, lepidocrocite, mackinawite, aragonite, calcite, and siderite were associated with oxidized and cemented areas, while green rusts were detected in more reduced zones. Basic differences from our last detailed investigation include (i) mackinawite crystallized from amorphous FeS, (ii) aragonite transformed into calcite, (iii) akaganeite transformed to goethite and lepidocrocite, (iv) iron (oxy)hydroxides and calcium and iron carbonate minerals increased, (v) cementation was greater in the more recent study, and (vi) oxidation, corrosion, and disintegration of Fe0 filings were greater, especially in cemented areas, in the more recent study. If the degree of corrosion and cementation that was observed from 15 to 30 mo after installation continues, certain portions of the PRB (i.e., up-gradient entrance of the ground water to the Fe0 section of the PRB) may last less than five more years, thus reducing the effectiveness of the PRB to mitigate contaminants. Abbreviations: EDX, energy dispersive X-ray • Fe0, zerovalent iron • PRB, permeable reactive barrier • SEM, scanning electron microscopy • XRD, X-ray diffraction