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The maintenance strategies commonly employed in industrial settings primarily rely on theoretical models that often overlook the actual operating conditions. To address this limitation, the present paper introduces a novel selective predictive maintenance approach based on a machine learning model for a multi-parallel series system, which involves executing multiple missions with breaks between them. For this purpose, the proposed selective maintenance approach consists of finding, at each breakdown, the optimal structure of maintenance activities that provide the desired reliability level of the system for each mission. This decision is based on a component's actual age, as determined by the prediction model. In addition, an optimization model with the Extended Great Deluge (EGD) algorithm uses these predictions as input data to identify the best maintenance level for each component considering the constrained maintenance resources. Finally, the numerical results of the proposed idea applied to the Flexible Manufacturing System (FMS) data are presented to show the robustness of the model. [ABSTRACT FROM AUTHOR]

This article investigates integrated maintenance, production, and product quality control policy for a supply chain consisting of a single machine producing only one type of product, a main storage warehouse, and multi-purchases warehouses. The variation of the production rate and its use over time impact the manufacturing system’s degradation degree. Hence, the machine is subject to a random failure that directly affects the quality of the products. The goal of this study is to establish an optimal production and delivery planning with inventory management considering the production, holding, and delivery costs, and then an appropriate maintenance strategy, considering the influence of the production rate on the system degradation. Also, we provide a quality control policy to reduce the proportion of non-compliant products by using the statistical process control chart to forecast production. Forecasting the production aims to satisfy the varying demands during a finite horizon under service and quality levels. Numerical examples are presented to justify the effectiveness of the suggested strategy.

In this paper, we present a novel statistical approach to corpus-based speech synthesis. Classically, phonetic information is defined and considered as acoustic reference to be respected. In this way, many studies were elaborated for acoustical unit classification. This type of classification allows separating units according to their symbolic characteristics. Indeed, target cost and concatenation cost were classically defined for unit selection. In Corpus-Based Speech Synthesis System, when using large text corpora, cost functions were limited to a juxtaposition of symbolic criteria and the acoustic information of units is not exploited in the definition of the target cost. In this manuscript, we token in our consideration the unit phonetic information corresponding to acoustic information. This would be realized by defining a probabilistic linguistic Bi-grams model basically used for unit selection. The selected units would be extracted from the English TIMIT corpora. Keywords--Unit selection, Corpus-based Speech Synthesis, Bi-gram model, I. INTRODUCTION CONCATENATIVE Text-To-Speech synthesizers join prerecorded segments of speech data in order to produce high quality output speech [1,2]. The synthesizer has to find the best unit to concatenate [...]

Air traffic management aims to provide solutions to congestion problems in air traffic networks (ATNs) which in turn are mainly generated by the variation in the capacity of air sectors or airports due to adverse weather conditions. Most of the existing approaches to dealing with these problems are based on mathematical programming techniques and inherit its computational difficulty. In this paper, we introduce a control scientist point of view to this topic by proposing an approach to solve the ground-holding problem based on discrete event systems control theory. An ATN can effectively be considered as a timed discrete event system and can be efficiently modelled based on a Time Petri net tool. The main advantage is an explicit representation of the position of each aircraft in the ATN at each time instant. The state space is modelled by a Discrete Time Reachability Graph and the capacity constraints on the air sectors are modelled by time floating general mutual exclusion constraints. Feasible flight plans can be constructed based on control synthesis techniques, while an algorithm to compute the optimal flight plan is proposed assuming a realistic cost function. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal solution to large-scale Flexible Manufacturing System (FMS) scheduling problems under availability constraints based on Timed Petri Nets (TPNs). First a decomposition method of TPNs is proposed, then a mathematical model is derived based on their properties. The mathematical model is built to determine the optimal firing sequence of TPN transitions to minimize the total manufacturing time. The resulting firing sequence of TPN transitions is used to generate the manufacturing system supervisor operated by TPN and digital controllers. Several numerical examples and comparative studies are provided in this paper in order to prove the new approach's efficiency. [ABSTRACT FROM AUTHOR]

This paper addresses the synthesis of Petri net (PN) controller for the forbidden state transition problem with a new utilisation of the theory of regions. Moreover, as any method of control synthesis based on a reachability graph, the theory of regions suffers from the combinatorial explosion problem. The proposed work minimises the number of equations in the linear system of theory of regions and therefore one can reduce the computation time. In this paper, two different approaches are proposed to select minimal cuts in the reachability graph in order to synthesise a PN controller. Thanks to a switch from one cut to another, one can activate and deactivate the corresponding PNcontroller. An application is implemented in a flexible manufacturing system to illustrate the present method. Finally, comparison with previous works with experimental results in obtaining a maximally permissive controller is presented. [ABSTRACT FROM AUTHOR]