An Optimal Deadlock Prevention Policy for Flexible Manufacturing Systems Using Petri Net Models with Resources and the Theory of Regions

In this paper, an optimal deadlock prevention policy for flexible manufacturing systems (FMSs) is proposed. In an FMS, dead-locks can arise because of a limited number of shared resources, i.e. machines, robots, buffers, fixtures etc. Deadlock is a highly undesirable situation, where each of a set of two or more jobs keeps waiting indefinitely for the other jobs in the set to release resources. The proposed optimal deadlock prevention policy is based on the use of reachability graph analysis of a Petri net model (PNM) of a given FMS and the synthesis of a set of new net elements, namely places with initial marking and related arcs, to be added to the PNM, using the theory of regions, which is a formal synthesis technique toderive Petri nets from automaton-based models. The policy proposed is optimal in the sense that it allows the maximal use of resources in the system according to the production requirements. Two examples are provided for illustration. RID=" ID=" <E5>Correspondence and offprint requests to</E5>: M. Uzam, Ni&gbreve;de &Uuml;niversitesi, M&uuml;hendislik-Mimarlik Fak&uuml;ltesi, Elektrik-Elektronik M&uuml;hendisli&gbreve;i B&ouml;l&uuml;m&uuml;, Kamp&uuml;s, 51100, Ni&gbreve;de, Turkey. E-mail: murat_uzam&commat;hotmail.com     

Computation of a turbulent natural convection in a rectangular cavity with the low-reynolds-number differential stress and flux model

A numerical study of a natural convection in a rectangular cavity with the low-Reynoldsnumber differential stress and flux model is presented. The primary emphasis of the study is placed on the investigation of the accuracy and numerical stability of the low-Reynolds-number differential stress and flux model for a natural convection problem. The turbulence model considered in the study is that developed by Peeters and Henkes (1992) and further refined by Dol and Hanjalic (2001), and this model is applied to the prediction of a natural convection in a rectangular cavity together with the two-layer model, the shear stress transport model and the time-scale bound model, all with an algebraic heat flux model. The computed results are compared with the experimental data commonly used for the validation of the turbulence models. It is shown that the low-Reynolds-number differential stress and flux model predicts well the mean velocity and temperature, the vertical velocity fluctuation, the Reynolds shear stress, the horizontal turbulent heat flux, the local Nusselt number and the wall shear stress, but slightly under-predicts the vertical turbulent heat flux. The performance of the model is comparable to that of the low-Reynolds-number differential stress and flux model except for the over-prediction of the horizontal turbulent heat flux. The two-layer model predicts poorly the mean vertical velocity component and under-predicts the wall shear stress and the local Nusselt number. The shear stress transport model predicts well the mean velocity, but the general performance of the shear stress transport model is nearly the same as that of the two-layer model, under-predicting the local Nusselt number and the turbulent quantities.     

Measurement and simultaneous compression of multidimensional -ray histograms using address randomizing transforms

In the paper we present efficient algorithm for measurement and simultaneous compression of multidimensional symmetrical γ-ray histograms from event data streams. The compression of data volume is achieved due to both the symmetry of the γ-ray spectra and compression capabilities of the employed randomizing transform. The algorithm of compression is very fast. Acquired compressed data can be later processed in an interactive way.