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Mehdi R.,Ecole de Technologie Superieure of Montreal | Nidhal R.,French Institute for Research in Computer Science and Automation | Anis C.,Cerep
Computers and Industrial Engineering | Year: 2010

In this paper, we develop a joint quality control and preventive maintenance policy for a production system producing conforming and non-conforming units. The considered system consists of one machine which must supply another production line operating on a just-in-time basis. According to the proportion l of non-conforming units observed on each lot and compared to a threshold value lm, one decides to undertake or not maintenance actions on the system. In order to palliate perturbations caused by the stopping of the machine to undergo preventive maintenance or an overhaul, a buffer stock h is built up from the instant when the rejection rate reaches a threshold level lA in order to ensure the continuous supply of the subsequent production line. Our objective is to determine simultaneously the optimal rates lm* and lA*, and the optimal size h* which minimize the expected total cost per time unit including the average costs related to maintenance, quality and inventory. © 2009 Elsevier Ltd. All rights reserved. Source


Souheil A.,Cerep | Sadok T.,University of Lorraine | Zied H.,University of Lorraine
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2015

This paper deals with a manufacturing system M1 which has to satisfy a random demand during a finite horizon given a required service level. To help meet this demand, subcontracting is used through another production system M2 which has a random service level β. The aim of this study is to determine the production plan of the manufacturing system M1 for each period of the horizon taking into account the machine M1 degradation according its production rate. Baring in mind that realistically the subcontractor is not always available to satisfy each demand variation, we assume that we can only order a minimum fixed quantity - defined a prioriduring the entire horizon. The optimal production plan then will correspond to the minimum sum of production (M1 and M2), inventory, lost sales cost and degradation cost. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Source


Horvat S.,Ruder Boskovic Institute | Hamersak Z.,Ruder Boskovic Institute | Stipetic I.,Ruder Boskovic Institute | Jolas T.,Cerep
European Journal of Medicinal Chemistry | Year: 2010

A series of novel pregabalin derivatives were synthesized starting from N-protected pregabalin, different amino sugars, adamantylamine, serotonin and tryptamine. New compounds were spectroscopically characterized and in vitro tested on gabapentin receptor binding assay. The serotonin-pregabalin adduct showed significant binding effect and its IC50 value was determined. © 2009 Elsevier Masson SAS. All rights reserved. Source


Yedes Y.,CEREP LGIPM | Chelbi A.,Cerep | Rezg N.,French Institute for Research in Computer Science and Automation
Journal of Intelligent Manufacturing | Year: 2012

In this paper we deal with the integrated supply chain management problem in the context of a single vendor-single buyer system for which the production unit is assumed to randomly shift from an in-control to an out-of-control state. At the end of each production cycle, a corrective or preventive maintenance action is performed, depending on the state of the production unit, and a new setup is carried out. Two different integrated production, shipment and maintenance strategies are proposed to satisfy the buyer's demand at minimum total cost. The first one suggests that the buyer orders batches of size nQ and the vendor produces nQ and makes equal shipments of size Q. The second policy proposes that to satisfy the same ordered quantity, the vendor produces separately smaller batches of size Q, n times. The total integrated average cost per time unit corresponding to each strategy is considered as the performance criterion allowing choosing the best policy for any given situation. © 2010 Springer Science+Business Media, LLC. Source


Berge C.,Hoffmann-La Roche | Froloff N.,Cerep | Kalathur R.K.R.,LBGI IGBMC | Maumy M.,Institute Of Recherche Mathematique Avancee Irma | And 3 more authors.
Journal of Computational Biology | Year: 2010

Large multidimensional data matrices are frequent in biology. However, statistical methods often have difficulties dealing with such matrices because they contain very complex data sets. Consequently variable selection and dimensionality reduction methods are often used to reduce matrix complexity, although at the expense of information conservation. A new method derived from multidimensional scaling (MDS) is presented for the case where two matrices are available to describe the same population. The presented method transforms one of the matrices, called the target matrix, with some constraints to make it fit with the second matrix, referred to as the reference matrix. The fitting to the reference matrix is performed on the distances computed for the two matrices, and the transformation depends on the problem at hand. A special feature of this method is that a variable can be only partially modified. The method is applied on the exclusive-or (XOR) problem and then on a biological application with large-scale gene expression data. © Copyright 2010, Mary Ann Liebert, Inc. Source

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