Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System

During the recent years, development of information technology caused to develop a new industrial system which is called e-Manufacturing system. Thanks to the webenabled manufacturing technologies, the lead times are being minimized to their extreme level, and the minimum amount of inventory is kept, though the products are being made-to order. Under these circumstances, achieving near-zero downtime of the plant floor’s equipments is a crucial factor which mitigates the risk of facing unmet demands. Many researches carried out to schedule maintenance actions in short term, but none of them have utilized all of planning horizon to spread maintenance actions along available time. In this research a method of enhanced maintenance scheduling of multi-component e-Manufacturing systems has been developed. In this multi-component system, importance of all machines is considered and the benefit of the entire system in term of produced parts is taken into account (versus benefits of single machine). In proposed system, the predicted machines degradation information, online information about work in process (WIP) inventory (at inventory buffer of each work station) as well as production line’s dynamism are taken into account. All of makespans of planning horizon have been utilized to improve scheduling efficiency and operational productivity by maximizing the system throughputs. A state-of-the-art method which is called simulation optimization has been utilized to implement the proposed scheduling method. The production system is simulated by ProModel software. It plays the role of objective function of the maintenance scheduling optimization problem. Using a production related heuristic method which is called system value method, the value of each workstation is determined. These values are used to define the objective function’s parameters. Then, using genetic algorithm-based software which is called SimRunner and has been embedded by ProModel, the scheduling optimization procedure is run to find optimum maintenance schedule. This process is carried out for nine generated scenarios. At the end, the results are benchmarked by two commonly used maintenance scheduling methods to magnify the importance of proposed intelligent maintenance scheduling in the multi-component e-Manufacturing systems. The results demonstrate that the proposed optimal maintenance scheduling method yields much better system value rather than sequencing methods. Furthermore, it indicates that when the mean time to repairs are longer, this method is more efficient. The results in the simulated testbed indicate that the developed scheduling method using simulation optimization functions properly and can be applied in other cases

Experimental Characterization And Neural Network Prediction Of Dynamic Behavior Of Zta With Srco3 And Mgo

Ceramics materials are extensively used in armor applications for their attractive properties such as high hardness, low density and high compressive strength. However for designing and selection for appropriate ceramic armor material, a deep knowledge about the dynamic behavior of ceramic is necessary. A number of research has been done on dynamic behavior of ceramic, unfortunately most of work focused on the conventional and limited ceramics (such as Al2O3 , B4C, SiC). For this reason prediction of the dynamic behavior of the new composition of ceramics is difficult and some time is impossible. In this work, mechanical properties and dynamic behavior of ZTA are being investigated. For studying the dynamic behavior of the ZTA, SHPB apparatus is modified (using pulse shaper and sandwich the sample with WC platen) and used. Effect of different amount of YSZ (10-40wt.%) on their properties of ZTA is also investigated dynamically using SHPB. ZTA with 20 wt.% YSZ shows the optimum properties and also their dynamic behavior. Effect of SrCO3 (1-5wt.% ) added to the ZTA with 20 wt.% YSZ and the formation of new phase (SrAl12O19) on porosity and fracture toughness is of interest. The formation of this phase increases the porosity and hence decreases the dynamic performance of the composite. An addition of MgO (0.2-0.9wt.%) to ZTA with 20 wt.% YSZ resulted a reduction in grain size and consequently increase the hardness. Further investigation on different dynamic loading condition on ZTA with 20 wt.% YSZ and 0.2wt.% MgO were also conducted. The dynamic behavior of representative ZTA is predicted by three different machine learning methods (Multilayer Perceptron (MLP), Time Series and Supporting Vector Regression (SVR)). The predictions are compared to each other and the time series neural networks shows the best agreement with the experimental data

Hierarchical spatio-temporal models for environmental processes

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file (viewed on November 21, 2007)Vita.Thesis (Ph. D.) University of Missouri-Columbia 2007.The processes governing environmental systems are often complex, involving different interacting scales of variability in space and time. The complexities and often high dimensionality of such spatio-temporal processes can be effectively addressed using a hierarchical modeling framework where a complex problem is decomposed into a series of simpler problems that are linked through rules of probability. In this dissertation, hierarchical spatio-temporal models are developed and utilized for environmental processes. The methods discussed in this dissertation include a wide scope of problems related to the modeling of spatio-temporal environmental processes. Specifically, methods are described for efficient modeling of spatio-temporal environmental processes using both discrete- and continuous valued data.Includes bibliographical reference

Reclaiming Impact in the Age of Awareness-raising for Human Rights

In the last decade, the practice of awareness-raising for human rights has appeared as notably common across the board. Nevertheless, widespread awareness-raising has not necessarily always resulted in meaningful and sustainable impact. Accepting that awareness raising is not a panacea, we challenge the global collective fascination with big impact, while considering the power of small strategic impact that invests in education, and building alliances, and has the potential to last and to expand by way of gradual encroachment through contextually-defined grassroots means natural to its course. Empowered through social media, advocates are increasingly enthusiastic about reaching massive audiences by way of campaigns which if effectively designed and executed, travel far and wide. Acknowledging the potential power of awareness-raising, this practice should not be mistaken as an end in and of itself. In fact, if viewed as an end, such campaigns can arguably bear detrimental unintended consequences: While giving an impression of activism they may fail to channel the collective energy of the public into strategic and sustainable action focused on appropriately-scoped and scalable change. In this context, we explore the original aim(s) of awareness-raising as a concept, as well as its limitations and capacities. Moreover, we will revisit the parameters of structural, foundational and sustainable impact. In doing so, we will examine successful strategies for translating awareness-raising into behavioral change and measurable impact in other contexts (e.g., environmental movement, or public health). Finally, we will challenge the notion of global as it stands today, rejecting the notion that the west always seem to have lessons learned on human rights to offer to the Global South. As western societies struggle with backlash and hostility towards progress, there are valuable opportunities to learn from experiences of the Global South on grassroots activism, and the importance of patience in seeking impact

Proposed Model for Stress-strain Behavior of Fly Ash Concrete Under the Freezing and Thawing Cycles

Fly ash is a supplementary cement material using instead of Portland cement in concrete. Using this material concludes to less emission of greenhouse gas and less water demand of concrete. In this paper, an experimental investigation was carried out on compressive stress–strain behavior of three groups of concrete specimens with different water/cement ratios (0.45, 0.5 and 0.55), containing 0, 10, 20, 30 and 40 percent of fly ash (by weight), after subjecting to freezing and thawing cycles. 0, 45, 100 and 150 cycles of freezing and thawing were applied on these specimens according to ASTM C666 and the results presented. Numerical models for the stress–strain behavior of these frozen-thawed concrete were developed and compared with the available experimental data. Results show that the maximum compressive strength of these concrete specimens exposing cycles of freezing and thawing is gained by using about 10 % of fly ash. Moreover, there is a good agreement between the proposed models and test results and the difference is less than 5 %

Fast Approximation To Gaussian Obstacle Sampling For Randomized Motion Planning

International audienc

Existence of solutions for some classes of integro-differential equations via measure of noncompactness

In this present paper, we introduce a new measure of noncompactness on the space consisting of all real functions which are $n$ times bounded and continuously differentiable on $\mathbb{R}_+$. As an application, we investigate the problem of the existence of solutions for some classes of the functional integral-differential equations which enables us to study the existence of solutions of nonlinear integro-differential equations. In our considerations we apply the technique of measures of noncompactness in conjunction with Darbo's fixed point theorem. Finally, we give some illustrative examples to verify the effectiveness and applicability of our results

Responses of different panicum miliaceum l. Genotypes to saline and water stress in a marginal mediterranean environment

The aims of this study were to evaluate: (1) the effect of sodium chloride (NaCl) and mannitol at different osmotic pressures on the germination of three proso millet (Panicum miliaceum L.) genotypes (VIR 9181, Unikum, and Kinelskoje) under controlled laboratory conditions; and (2) the effects of irrigation water salinity, maximum crop evapotranspiration (ETm) restitution regimes, and arbuscular mycorrhizal fungi (AMF) inoculation on forage production in a marginal Mediterranean soil for the genotypes that showed the highest and lowest seed germination. In the laboratory experiment, the Unikum genotype showed the highest seed germination (95.1%), whereas the lowest was found for Kinelskoje (80.4%). Regardless of the osmoticum type, germination was significantly reduced by osmotic pressure increases. Unikum showed a higher fresh biomass yield (FBY) (620.4 ± 126.3 g m−2) than Kinelskoje (340.0 ± 73.5 g m−2). AMF inoculation did not influence FBY under salt conditions, while in the absence of salt conditions it significantly increased the Unikum FBY (+50.7%) as compared to the uninoculated treatment (552.5 ± 269 g m−2). The 25% ETm significantly reduced FBY in both genotypes (−86.2% and −84.1% for Unikum and Kinelskoje, respectively) sd compared to the 100% ETm treatments (1090.3 ± 49.7 g m−2 in Unikum and 587 ± 72.2 g m−2 in Kinelskoje). The obtained results give novel information about proso millet forage production in low-input agriculture in marginal semi-arid Mediterranean land