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Mohamed Ali Kammoun
UFR-MIM, LGIPM, University of Lorraine, F-57000 Metz, France

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Journal article
Published: 05 May 2021 in Applied Sciences
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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.

ACS Style

Zied Hajej; Aime Nyoungue; Aminu Abubakar; Kammoun Mohamed Ali. An Integrated Model of Production, Maintenance, and Quality Control with Statistical Process Control Chart of a Supply Chain. Applied Sciences 2021, 11, 4192 .

AMA Style

Zied Hajej, Aime Nyoungue, Aminu Abubakar, Kammoun Mohamed Ali. An Integrated Model of Production, Maintenance, and Quality Control with Statistical Process Control Chart of a Supply Chain. Applied Sciences. 2021; 11 (9):4192.

Chicago/Turabian Style

Zied Hajej; Aime Nyoungue; Aminu Abubakar; Kammoun Mohamed Ali. 2021. "An Integrated Model of Production, Maintenance, and Quality Control with Statistical Process Control Chart of a Supply Chain." Applied Sciences 11, no. 9: 4192.

Journal article
Published: 10 July 2020 in Sustainability
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The flight rescheduling problem is one of the major challenges of air traffic issue. Unforeseen bad weather conditions stimulate air traffic congestion and make the initial scheduling infeasible, resulting in significant economic losses for passengers and airlines. Furthermore, due to rigorous environmental legislations, flight rescheduling becomes a more complicated problem, as it has to deal with flight delays on the one hand, and carbon emissions on the other hand. In this paper, we address the flight rescheduling problem with an environmental requirement subject to the air capacity limitation due to bad weather conditions. A new strategy is proposed to minimize the disruption effects on planned flights, which adopted ground delay, longer route change, flight cancellation, as well speed adjustment to arrive at a scheduled time. Firstly, the objective of this study is to determine the economical flights plan in line with the new available air capacity. Secondly, by considering the environmental impact of the kerosene consumption, we illustrate the contribution of an economical decision to aircraft emissions. Experiment results are provided to show the efficiency of the proposed strategies and genetic algorithm as the used optimization method. Furthermore, the impacts of carbon tax and cost of arrival delay on the flights carbon emissions are studied.

ACS Style

Mohamed Ali Kammoun; Sadok Turki; Nidhal Rezg. Optimization of Flight Rescheduling Problem under Carbon Tax. Sustainability 2020, 12, 5576 .

AMA Style

Mohamed Ali Kammoun, Sadok Turki, Nidhal Rezg. Optimization of Flight Rescheduling Problem under Carbon Tax. Sustainability. 2020; 12 (14):5576.

Chicago/Turabian Style

Mohamed Ali Kammoun; Sadok Turki; Nidhal Rezg. 2020. "Optimization of Flight Rescheduling Problem under Carbon Tax." Sustainability 12, no. 14: 5576.

Journal article
Published: 01 August 2018 in Journal of Air Transport Management
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In this paper, we address the aircraft routing and rescheduling problem under airspace capacities uncertainty due to unplanned weather conditions, which occurs before the take-off of scheduled flights. For this problem, we propose a hybrid approach that is based on Time Petri Net (TPNTPN) tool. Furthermore, as a second step, a genetic algorithm is introduced in which a possible solution for ARRPARRP is represented by a new encoding. Additionally, we integrate a post-step, which verifies the feasibility of the flight plans based on an improved Time Reduced Ordered Binary Decision Diagrams (TROBDDsTROBDDs). The conducted experiments on a collection of instances show that the TROBDDsTROBDDs can represent a large number of rescheduling flights locations with compact structure and reduce computation time. In addition, the genetic algorithm illustrates a good compromise between the obtained solutions and computation times.

ACS Style

Mohamed Ali Kammoun; Nidhal Rezg. An efficient hybrid approach for resolving the aircraft routing and rescheduling problem. Journal of Air Transport Management 2018, 71, 73 -87.

AMA Style

Mohamed Ali Kammoun, Nidhal Rezg. An efficient hybrid approach for resolving the aircraft routing and rescheduling problem. Journal of Air Transport Management. 2018; 71 ():73-87.

Chicago/Turabian Style

Mohamed Ali Kammoun; Nidhal Rezg. 2018. "An efficient hybrid approach for resolving the aircraft routing and rescheduling problem." Journal of Air Transport Management 71, no. : 73-87.

Original article
Published: 06 February 2018 in The International Journal of Advanced Manufacturing Technology
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Several industrial systems are required to carry out a sequence of missions in which the maintenance activity is allowed only between two consecutive missions. In such case, the selective maintenance strategy is widely adopted, which aims to select the best components to be maintained, taking into account the constrained maintenance resources. The suggested maintenance selective resolution methods in the literature are based essentially on theoretical analyses and estimated parameters, which does not necessarily reflect the reality. In this study, we propose to combine techniques based on data mining approach to the selective maintenance of a multi-component system, using the maintenance data collection. For this purpose, the similar components are clustered, as a first step, and the age degradation coefficient of similar components is computed by using the K-means clustering algorithm. Next, we propose a mixed integer programming model that uses as input data the components degradation coefficients of the first step, in order to decide which components need to be replaced first. After, using the Apriori algorithm, the frequent sequences of maintained component are extracted, which provides us additional knowledge to predict the next maintenance activity. Finally, the proposed approach is assessed through a real-world case study of maintenance data of a flexible manufacturing system.

ACS Style

Mohamed Ali Kammoun; Nidhal Rezg. Toward the optimal selective maintenance for multi-component systems using observed failure: applied to the FMS study case. The International Journal of Advanced Manufacturing Technology 2018, 96, 1093 -1107.

AMA Style

Mohamed Ali Kammoun, Nidhal Rezg. Toward the optimal selective maintenance for multi-component systems using observed failure: applied to the FMS study case. The International Journal of Advanced Manufacturing Technology. 2018; 96 (1-4):1093-1107.

Chicago/Turabian Style

Mohamed Ali Kammoun; Nidhal Rezg. 2018. "Toward the optimal selective maintenance for multi-component systems using observed failure: applied to the FMS study case." The International Journal of Advanced Manufacturing Technology 96, no. 1-4: 1093-1107.

Journal article
Published: 15 April 2017 in Applied Sciences
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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.

ACS Style

Mohamed Ali Kammoun; Wajih Ezzeddine; Nidhal Rezg; Zied Achour. FMS Scheduling under Availability Constraint with Supervisor Based on Timed Petri Nets. Applied Sciences 2017, 7, 399 .

AMA Style

Mohamed Ali Kammoun, Wajih Ezzeddine, Nidhal Rezg, Zied Achour. FMS Scheduling under Availability Constraint with Supervisor Based on Timed Petri Nets. Applied Sciences. 2017; 7 (4):399.

Chicago/Turabian Style

Mohamed Ali Kammoun; Wajih Ezzeddine; Nidhal Rezg; Zied Achour. 2017. "FMS Scheduling under Availability Constraint with Supervisor Based on Timed Petri Nets." Applied Sciences 7, no. 4: 399.

Journal article
Published: 20 August 2015 in International Journal of Systems Science
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ACS Style

Sadok Rezig; Zied Achour; Nidhal Rezg; Mohamed-Ali Kammoun. Supervisory control based on minimal cuts and Petri net sub-controllers coordination. International Journal of Systems Science 2015, 47, 1 -11.

AMA Style

Sadok Rezig, Zied Achour, Nidhal Rezg, Mohamed-Ali Kammoun. Supervisory control based on minimal cuts and Petri net sub-controllers coordination. International Journal of Systems Science. 2015; 47 (14):1-11.

Chicago/Turabian Style

Sadok Rezig; Zied Achour; Nidhal Rezg; Mohamed-Ali Kammoun. 2015. "Supervisory control based on minimal cuts and Petri net sub-controllers coordination." International Journal of Systems Science 47, no. 14: 1-11.

Articles
Published: 28 August 2013 in International Journal of Production Research
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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.

ACS Style

Mohamed Ali Kammoun; Nidhal Rezg; Zied Achour. New approach for air traffic management based on control theory. International Journal of Production Research 2013, 52, 1711 -1727.

AMA Style

Mohamed Ali Kammoun, Nidhal Rezg, Zied Achour. New approach for air traffic management based on control theory. International Journal of Production Research. 2013; 52 (6):1711-1727.

Chicago/Turabian Style

Mohamed Ali Kammoun; Nidhal Rezg; Zied Achour. 2013. "New approach for air traffic management based on control theory." International Journal of Production Research 52, no. 6: 1711-1727.