A model management systems approach to manufacturing systems design

Manufacturing systems design involves the solution of a complex series of interrelated problems. This complexity will increase in the future as manufacturing practices change to meet increased global competition. Research within manufacturing systems design has mainly been focused on finding improved models for solving particular problems, or extending existing modeling techniques. This has resulted in numerous modeling tools being available to support manufacturing systems design. However, little research work has been carried out into consolidating the existing theories and models. As a result, a large body of this work has not been applied in industry.Model management has evolved as a research area which investigates methods for storing, modifying, and manipulating models. This article describes a prototype model management system for manufacturing systems design. The objective here is not to develop another decision support system for manufacturing design, but to illustrate, through the development of a prototype system, a number of key ideas of how concepts from the area of model management systems can be used to support manufacturing systems design. The prototype model management system utilizes the structured modeling framework and uses an extended version of the structured modeling language. An important aspect of the prototype model management system is the incorporation of the model development task, thus allowing the system to be easily updated and adapted. The prototype system was evaluated using a range of queueing network models for manufacturing systems design.     

Characterisation of chickpea flour‐based gluten‐free batters and muffins with added biopolymers: rheological,physical and sensory properties

Chickpea flour (CF)‐based muffin formulations were made with CF alone and with added biopolymers [whey protein (WP), xanthan gum (XG) and inulin (INL)] to evaluate their suitability to be a wheat flour (WF) substitute in muffins. Structural characteristics of the batters and muffins were studied by means of rheometry, microscopy, physicochemical properties, and texture and sensory analysis. Partial replacement of CF with XG, alone (at 0.5 and 1%) or blended with either WP or INL, significantly increased the batter viscoelasticity as denser matrices developed; moreover, the muffins with XG added at 1% had similar hardness to wheat gluten muffins. The replacement of WF decreased the springiness, cohesiveness, chewiness, resilience and specific volume of the muffin. However, baked muffins with added XG also showed higher sensory sponginess and moisture associated with numerous air bubbles in the batter and were perceived to be easier to swallow and to have better general appearance.     

Cooperative games with nontransferable utility on antimatroids

This paper introduces a new family of nontransferable utility (NTU) games with partial cooperation. Games with transferable utility (TU) restricted by antimatroids were studied since 2004. Antimatroids are known combinatorial structures which are interpreted in games as dependency situations among a group of agents, and they generalize several other hierarchical structures studied in the literature. Now we define projected NTU games over antimatroids following the same idea. We have needed to build a new theory about projections between two coalitions. In this case, an outcome is feasible for a coalition if and only if its projection is feasible in the NTU game. This paper studies several properties of the projected games and the relations between these games and the original game for some interesting cases: TU games, hyperplane games and bargaining problems.     

Morphological contrast index based on the Weber's law

In this article, a morphological contrast index based on the Weber's law is proposed to quantify the contrast in a processed image. This measure involves the contours of the image along with its background. The proposal made here is applied to detect the image with higher contrast, and also identify the enhanced image most similar to the original. Moreover, the contrast index is compared with other four indexes reported in the current literature. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 137–144, 2012     

Ultraviolet Lamp Output Measurement: A Concise Derivation of the Keitz Equation

An equation relating the measured irradiance and the output power of a fluorescent lamp was derived by Keitz. The equation forms the basis for a new protocol that has been proposed for quantifying the total flux from an ultraviolet lamp. There has been confusion in the literature regarding the spatial distribution of flux from lamp emitters, which has led to emission models that are similar to the Keitz model but are incorrect. The Keitz equation is derived here from first principles in an effort to eliminate the confusion and present a correct method of calculating total flux.     

Incorporation of polyfluorenes into poly(lactic acid) films for sensor and optoelectronics applications

Films of neat and plasticized biodegradable poly(lactic acid) (PLA) matrices containing anionic conjugated polyelectrolytes, poly[9,9‐bis(4‐phenoxybutylsulfonate)]fluorene‐2,7‐diyl‐alt‐arylenes, with 1,4‐phenylene and 4,4″‐p‐terphenylene, respectively, as arylene groups or a neutral poly(9,9‐dialkylfluorene) for comparison were prepared by solution casting. These films were characterized using differential scanning calorimetry, thermogravimetry, scanning electron microscopy and fluorescence spectroscopy. In addition, the effects of plasticizer on the thermal properties and the oxygen permeability of the PLA films were measured through the oxygen transmission rate. Results show that it is possible to obtain thin, optically transparent and luminescent films with potential in oxygen sensing, exhibiting good thermal and photochemical stability. At high polyelectrolyte content, evidence is found for phase separation and aggregate formation and it is no longer possible to obtain completely homogeneous films. The possibility of incorporating the cationic metal complex tris(2,2′‐bipyridyl)ruthenium(II) into plasticized PLA films containing conjugated polyelectrolytes for dual‐wavelength ratiometric luminescence sensing is also discussed. Copyright © 2012 Society of Chemical Industry     

Optimal performance assessment for a photo‐Fenton degradation pilot plant driven by solar energy using artificial neural networks

Artificial neural networks (ANN) were proposed as a multivariate experimental design tool for monitoring a photo‐Fenton treatment of wastewaters containing a synthetic mixture of pesticides. ANN and Nelder‐Mead simplex methods were used to find out the optimum operating parameters of a photo‐Fenton pilot plant. ANN was developed to predict the most important operating parameters (e.g., the total organic carbon and the initial mineralization kinetic rate constants of the reactions), which determine the photo‐catalytic degradation efficiency in photo‐Fenton processes. Experimental measurements of temperature, pH, hydrogen peroxide (H₂O₂) consumption, initial concentration of Fe²⁺, and the AE were used as input data for the ANN learning. A feed‐forward with one hidden layer, a Levenberg–Marquardt learning algorithm, a hyperbolic tangent sigmoidal transfer function and a linear transfer function were used to develop the ANN model. The best fitting of the training database was obtained with an ANN architecture constituted by seven neurons in the hidden layer. The simulated results were validated with experimental measurements, showing an acceptable agreement (R² > 0.99). The ANN was subsequently coupled with a Nelder–Mead simplex method to obtain the optimum operating parameters of the photo‐Fenton pilot plant. The H₂O₂ consumption was used as key variable for evaluating the optimization procedure. Errors less than 1% between simulated and experimental data were found. The obtained results showed that the use of ANN provides an excellent predictive performance tool with the additional capability to assess the influence of each operating parameter on the removal process of water pollutants. Copyright © 2011 John Wiley & Sons, Ltd.     

A Dynamic Harmonic Regression Approach to Power System Modal Identification and Prediction

Abstract—Time series models provide a powerful tool to extract nonstationary features from measured data. In this article, a statistical framework based upon a dynamic harmonic regression model for examining modal behavior is provided. In this model, temporal patterns in measured data are modeled within a stochastic state space setting. Estimates of the states or time-varying parameters are then obtained using an optimal estimation method based on the Kalman filter. Techniques to estimate future values of the unobserved signal are also analyzed. The widely applicable technique is illustrated on both simulated and measured data. Factors that affect the performance of the method are discussed, including the effects of non-linear trends, data quality, and sampling design. Connections with other modal identification methods are also investigated.