Coordinated scheduling of production and delivery from multiple plants

This paper deals with the scheduling of orders and vehicle assignment for production and distribution planning in a scenario of no-wait, immediate delivery to the customer site. We first describe the problem and then present an integer programming model that maximizes the weighted value of the orders served. We consider a special case of the problem which can be solved in polinomial time by a minimum cost flow algorithm. Based on this approach we develop a heuristic procedure for the general case. Comparisons with an exact graph-based method attest that our heuristic produces good-quality solutions in short running times.     

Fracture mechanisms and failure processes at stiffener run-outs in polymer matrix composite stiffened elements

This paper describes the fractographic analyses of three stringer run-out designs which had been loaded to failure in tension. The main aims of the investigation were to deduce the failure processes in the elements, and to characterise the effect of local geometry of the stringer run-out on the failure process. The analysis showed that the critical failure mechanism in the elements was the development of +45° ply splitting at the skin surface, initially under mode I dominated intralaminar fracture. However, as these splits grew beneath the stringer foot, the mode II component increased. This led to mixed-mode delamination growth, extending parallel to the +45° ply, at the skin/adhesive interface. Subsequently, the delamination migrated through the skin via ply splits, ultimately reaching the interface between the second and third (−45°/0°) plies, in which it remained until catastrophic failure.

Extending and tapering the stringer foot led to shifting of the site of the +45° ply splitting; this was attributed to in-plane tensile stresses in the skin being inhibited in the modified designs. The reduced out-of-plane support on the stiffener foot in the modified designs led to an increase in the mode I component at the delamination from the stringer tip. It also led to an increase in the degree of multi-plane delamination growth. Based on the fractographic observations, recommendations for modelling the elements were suggested.     

Using computer animated graphics with science instruction with children.

The effects of animated presentations and practice were studied in a computer-based science lesson involving fourth- and fifth-grade students. Three levels of visual elaboration (static graphics, animated graphics, and no graphics) were crossed with three levels of practice (behavioral, cognitive, and no practice). Behavioral practice consisted of traditional questioning and cognitive practice consisted of a structural simulation. Animated graphics were superior to static graphics and no graphics so long as practice was provided. Behavioral practice was effective only when paired with lessons containing animated graphics. Cognitive practice was generally superior to the other practice conditions and did not appear dependent on visual elaboration. These results suggest that animated presentations can promote learning under certain conditions, and they also demonstrate a successful application of interactive graphics in the design of cognitively based practice activities. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effect of temperature on the absorption loss of chalcogenide glass fibers

The change in the absorption loss of IR-transmitting chalcogenide glass fibers in the temperature range of -90 degrees C /= 6 mum the change in loss was mainly due to multiphonon absorption. The change in loss for tellurium-based glass fibers increased significantly at T = 60 degrees C. The increase in the loss at short wavelengths (lambda /= 9 mum, multiphonon absorption dominated the loss spectrum.     

Development of an Active Thermoplastic Film with Oxygen Scavengers Made of Activated Carbon and Sodium Erythorbate

An active thermoplastic film made of low‐density polyethylene (LDPE) filled with oxygen scavengers made of powdered activated carbon (PAC) impregnated with sodium erythorbate (SE) was developed for packaging applications. Initial tests indicated that the impregnation of PAC with SE enhanced the heat resistance of SE, thereby allowing processing at temperatures typical of LDPE manufacturing. Subsequently, LDPE films with PAC/SE particles were manufactured in coupons that represented a typical juice package, and experiments indicated that these films absorbed 3.57 mg of oxygen in 11 days. This amount corresponded to 80% the concentration of oxygen in the headspace of the package. Furthermore, findings indicated that active particles alone have 10 times higher oxygen absorption capacity than the active LDPE film. Finally, the physical properties of the film were characterized by microscopy where oxygen scavengers showed a good dispersion within the matrix. However, 20 wt.% of these active particles decreased tensile strength of the film by 53%. Copyright © 2014 John Wiley & Sons, Ltd.     

The State‐of‐the‐Art in Predictive Visual Analytics

Predictive analytics embraces an extensive range of techniques including statistical modeling, machine learning, and data mining and is applied in business intelligence, public health, disaster management and response, and many other fields. To date, visualization has been broadly used to support tasks in the predictive analytics pipeline. Primary uses have been in data cleaning, exploratory analysis, and diagnostics. For example, scatterplots and bar charts are used to illustrate class distributions and responses. More recently, extensive visual analytics systems for feature selection, incremental learning, and various prediction tasks have been proposed to support the growing use of complex models, agent‐specific optimization, and comprehensive model comparison and result exploration. Such work is being driven by advances in interactive machine learning and the desire of end‐users to understand and engage with the modeling process. In this state‐of‐the‐art report, we catalogue recent advances in the visualization community for supporting predictive analytics. First, we define the scope of predictive analytics discussed in this article and describe how visual analytics can support predictive analytics tasks in a predictive visual analytics (PVA) pipeline. We then survey the literature and categorize the research with respect to the proposed PVA pipeline. Systems and techniques are evaluated in terms of their supported interactions, and interactions specific to predictive analytics are discussed. We end this report with a discussion of challenges and opportunities for future research in predictive visual analytics.     

THE USE OF PESTICIDES IN MALTINGS,BREWERIES AND DISTILLERIES APRIL 1974 - MARCH 1975

A survey of the use of pesticides in maltings, breweries and distilleries during the period April 1974 to March 1975 was made by the Pesticides Survey Group at the Ministry of Agriculture's Pest Infestation Control Laboratory at Slough in collaboration with the Department of Agriculture and Fisheries for Scotland. A breakdown of the insecticides and rodenticides used, including quantities and numbers of users, is given. The results show that in most cases, the official recommended measures to control pests are being followed.     

Ligand‐Free Synthesis of Aluminum‐Doped Zinc Oxide Nanocrystals and their Use as Optical Spacers in Color‐Tuned Highly Efficient Organic Solar Cells

The color of polymer solar cells using an opaque electrode is given by the reflected light, which depends on the composition and thickness of each layer of the device. Metal‐oxide‐based optical spacers are intensively studied in polymer solar cells aiming to optimize the light absorption. However, the low conductivity of materials such as ZnO and TiO₂ limits the thickness of such optical spacers to tenths of nanometers. A novel synthesis route of cluster‐free Al‐doped ZnO (AZO) nanocrystals (NCs) is presented for solution processing of highly conductive layers without the need of temperature annealing, including thick optical spacers on top of polymer blends. The processing of 80 nm thick optical spacers based on AZO nanocrystal solutions on top of 200 nm thick polymer blend layer is demonstrated leading to improved photocurrent density of 17% compared to solar cells using standard active layers of 90 nm in combination with thin ZnO‐based optical spacers. These AZO NCs also open new opportunities for the processing of high‐efficiency color tuned solar cells. For the first time, it is shown that applying solution‐processed thick optical spacer with polymer blends of different thicknesses can process solar cells of similar efficiency over 7% but of different colors.     

Localized Ligand Induced Electroless Plating (LIEP) Process for the Fabrication of Copper Patterns Onto Flexible Polymer Substrates

The “ligand induced electroless plating (LIEP) process” is a simple process to obtain localized metal plating onto flexible polymers such as poly(ethylene terephtalate) and polyvinylidene fluoride sheets. This generic and cost‐effective process, efficient on any common polymer surface, is based on the covalent grafting by the GraftFast process of a thin chelating polymer film, such as poly(acrylic acid), which can complex copper ions. The entrapped copper ions are then chemically reduced in situ and the resulting Cu⁰ species act as a seed layer for the electroless copper growth which, thus, starts inside the host polymer. The present work focuses on the application of the LIEP process to the patterning of localized metallic tracks via two simple lithographic methods. The first is based on a standard photolithography process using a positive photoresist masking to prevent the covalent grafting of PAA in designated areas of the polymer substrate. In the second, the patterning is performed by direct printing of the mask with a commercial laser printer. In both cases, the mask was lifted off before the copper electroless plating step, which provides ecological benefits, since only the amount of copper necessary for the metallic patterning is used.     

A diagnoser algorithm for anomaly detection in DEDS under partial and unreliable observations: characterization and inclusion in sensor configuration optimization

Complex engineering systems have to be carefully monitored to meet demanding performance requirements, including detecting anomalies in their operations. There are two major monitoring challenges for these systems. The first challenge is that information collected from the monitored system is often partial and/or unreliable, in the sense that some occurred events may not be reported and/or may be reported incorrectly (e.g., reported as another event). The second is that anomalies often consist of sequences of event patterns separated in space and time. This paper introduces and analyzes a diagnoser algorithm that meets these challenges for detecting and counting occurrences of anomalies in engineering systems. The proposed diagnoser algorithm assumes that models are available for characterizing plant operations (via stochastic automata) and sensors (via probabilistic mappings) used for reporting partial and unreliable information. Methods for analyzing the effects of model uncertainties on the diagnoser performance are also discussed. In order to select configurations that reduce sensor costs, while satisfying diagnoser performance requirements, a sensor configuration selection algorithm developed in previous work is then extended for the proposed diagnoser algorithm. The proposed algorithms and methods are then applied to a multi-unit-operation system, which is derived from an actual facility application. Results show that the proposed diagnoser algorithm is able to detect and count occurrences of anomalies accurately and that its performance is robust to model uncertainties. Furthermore, the sensor configuration selection algorithm is able to suggest optimal sensor configurations with significantly reduced costs, while still yielding acceptable performance for counting the occurrences of anomalies.