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.

Short communication.Wood identification based on their common name and their transversal surface anatomy. Application to the batch from the expedition of Ruiz and Pavon

Aim of study: To identify species of wood samples based on common names and anatomical analyses of their transversal surfaces (without microscopic preparations). Area of study: Spain and South America Material and methods: The test was carried out on a batch of 15 lumber samples deposited in the Royal Botanical Garden in Madrid, from the expedition by Ruiz and Pavon (1777-1811). The first stage of the methodology is to search and to make a critical analysis of the databases which list common nomenclature along with scientific nomenclature. A geographic filter was then applied to the information resulting from the samples with a more restricted distribution. Finally an anatomical verification was carried out with a pocket microscope with a magnification of x40, equipped with a 50 micrometers resolution scale. Main results: The identification of the wood based exclusively on the common name is not useful due to the high number of alternative possibilities (14 for “naranjo”, 10 for “ébano”, etc.). The common name of one of the samples (“huachapelí mulato”) enabled the geographic origin of the samples to be accurately located to the shipyard area in Guayaquil (Ecuador). Given that Ruiz y Pavon did not travel to Ecuador, the specimens must have been obtained by Tafalla. It was possible to determine correctly 67% of the lumber samples from the batch. In 17% of the cases the methodology did not provide a reliable identification. Research highlights: It was possible to determine correctly 67% of the lumber samples from the batch and their geographic provenance. The identification of the wood based exclusively on the common name is not useful.