A Petri Nets-based Scheduling Methodology forMultipurpose Batch Plants.

This article presents an optimization methodology of batch production processes assembled by shared resources which rely on a mapping of state-events into time-events allowing in this way the straightforward use of a well consolidated scheduling policies developed for manufacturing systems. A technique to generate the timed Petri net representation from a continuous dynamic representation (Differential-Algebraic Equations systems (DAEs)) of the production system is presented together with the main characteristics of a Petri nets-based tool implemented for optimization purposes. This paper describes also how the implemented tool generates the coverability tree and how it can be pruned by a general purpose heuristic. An example of a distillation process with two shared batch resources is used to illustrate the optimization methodology proposed

Data Reconciliation as a Framework for Chemical Processes Optimization and Control

This thesis presents, discusses and compares a set of methodologies and several appropriate combinations of them, to provide accurate estimation of process variables, either for steady-state or dynamic systems. Firstly, the accuracy of estimated measurements is improved through the proposal of novel Data Reconciliation techniques. The proposal combines data-based and model-based filtering and also consider the presence of time-delays between sampled data.Secondly, measuring network design and its optimal use are addressed. Thus, the measuring device number, their type and their location for optimum reliability and accuracy of measurement at lowest possible cost are determined.The first part of this thesis provides procedures for accuracy estimation in dynamic evolving processes. These procedures rely on combining data-based filtering and model-based filtering. One technique combines a Moving Average filter and a steady-state Data Reconciliation technique sequentially. The resulting estimator presents the important statistic feature of being unbiased. Additionally, this estimator provides high accuracy estimation and good tracking for dramatic dynamic changes of process variables, when compared with other techniques. The other technique performs a wavelet analysis as a former step for reconciling dynamic systems. The wavelet technique catches or extracts the process measurement trends that are later made consistent with the dynamic process model. As a consequence of this technique high estimation accuracy is provided. Additional advantages of applying this technique over the current techniques are the easy handling of distinct sample times and evaluating the variance of dynamic variables. Furthermore, this thesis addresses an important aspect regarding dynamic Data Reconciliation: how to improve the accuracy estimation when the process is faced with the presence of time-delay. This problem was overcome in a simple and efficient way by proposing a time-delay estimation method that works in conjunction with the Measurement Model adopted within the Data Reconciliation technique.The presented time-delay estimation method determines the existing delay by maximizing the correlation of the process variables using genetic algorithms.The second part of this thesis addresses the design of sensor networks, the proposed strategy allows the optimal selection and placement of measuring devices. The proposal deal with different sensor placement aspects: variation in design, retrofit, hardware redundancy and available sensor type.The sensor placement procedure was extended to deal with dynamic systems by taking advantages of dynamic variable classification and dynamic Data Reconciliation.The procedure to locate sensors in dynamic systems aims at maximizing the performance of Kalman filtering using accuracy as its main performance index. To accomplish this, both the measurement noise and the observation matrices are manipulated. The solution strategy has been implemented in academic and in the Tennessee Eastman challenge problems showing promising results. The resulting optimization problem was solved satisfactorily either by exhaustive search or using genetic algorithms based optimization. The profile of the relative increase of the system performance along the sensor network and the associate investment cost gives the designer all the alternatives for making an adequate decision.Additionally, reliability is considered by combining quantitative process knowledge and fault tree analysis, providing an efficient way to improve its evaluation. It is important to state that the possibility to use inferential sensors based in an Artificial Neural Network model instead of physical sensors, and their incorporation within reliability and reconciliation procedures was a paramount consideration throughout this work.Finally, this thesis also provides two frameworks, one for sensor placement and the second for Data Reconciliation. Both proposed frameworks have been designed, specified and validated following the guidelines of the new standards and trends in developing component-based application (e.g. UMLTM, CAPE-OPEN). These frameworks can include the above mentioned algorithms and can be extended to include other existing or futures approaches efficiently

A Petri Nets–Based Scheduling Methodology for Multipurpose Batch Plants

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Valorisation des DEEE par l’extraction des terres rares, métaux précieux et matières plastiques

The approach proposed in this work present clean processes for the treatment and recycling of waste electrical and electronic equipment, under the protection of the environment paradigm, especially for computers and mobile phones which are classified in category 3: “it and telecommunication equipment” according to the European directive 2002/96/EC through the extraction of precious metals, rare earths and possibly plastic granulates. The proposed solution is adapted to the specificities of Morocco by implementing a scheme of appropriate ecological treatment consists of: 1) Processing of non-ferrous pyrometallurgical aggregates isolated, 2) Recovery of gold from gold coins by hydrometallurgical 3) Identification of rare earth from monitors 4) Manufacture of hydraulic plaster from residual waste (mixture of plastics, resins and ceramics). This work also focuses the possibility of rationalizing the consumption of natural resources by minimizing the need for raw material (e.g. Cu, Al, Au, Pd, plastics,) by the transformation of electrical and electronic waste (WEEE) in resources.L’approche proposée dans le présent travail a pour but d’élaborer des procédés propres pour le traitement et la valorisation des déchets d’équipements électriques et électroniques, en particulier les ordinateurs et les téléphones mobiles classés dans la catégorie 3 : « Equipements informatiques et de télécommunication » selon la directive européenne 2002/96/ce. La valorisation consiste en l’extraction des métaux précieux, des terres rares et éventuellement de granulats de plastiques. La solution proposée est adaptée aux spécificités du Maroc par la mise en œuvre d’un schéma de traitement écologique approprié qui consiste en : 1) Traitement pyrométallurgique de granulats non ferreux isolés, 2) Récupération de l’or à partir des pièces dorées par voie hydrométallurgique, 3) Identification des terres rares dans les écrans, 4) Fabrication d’enduit hydraulique à partir de déchets ultimes (mélange de plastiques, résines et céramiques). Le présent travail se focalise aussi sur la possibilité de rationaliser la consommation des ressources naturelles en minimisant les besoins en matière première (par exemple : Cu, Al, Au, Pd, plastiques,...) par la transformation des déchets électriques et électroniques (DEEE) en ressources