Publications by Year: 2013

2013

Mohamed, Bouznita. 2013. “Développement d’un Système Expert Connexionniste à Base des Méthodes de Sûreté de Fonctionnement: Application au Diagnostic d’un Bioréacteur, ISBN : 978-9931-9117-0-8”. CPI’2013 The 8th International Conference on Integrated Design and Production.

Hanane, Zermane. 2013. “Automation and fuzzy control of a manufacturing system, ISBN: 978-1-4244-9796-6. IEEE Xplore ”. (CoDIT 2013), International Conference on Control, Decision and Information Technologies. Publisher's Version

Nafissa, Rezki. 2013. “Design of multi-agent system for quality control and machine maintenance, ISBN: 978-1-4244-9796-6. IEEE Xplore ”. (CoDIT 2013), International Conference on Control, Decision and Information Technologies. Publisher's Version

Sonia, Benaicha. 2013. “Development of an Industrial Application with Neuro-Fuzzy Systems, ISBN: 978-1-4244-9796-6. IEEE Xplore ”. (CoDIT 2013), International Conference on Control, Decision and Information Technologies. Publisher's Version

Eddine, Bellal Salah. 2013. “Recognition of objetcts in an image for triage, ISBN: 978-1-4244-9796-6. IEEE Xplore ”. (CoDIT 2013), International Conference on Control, Decision and Information Technologies. Publisher's Version

Fateh, Bencherif. 2013. “Fuzzy Alpha-cuts to capture customer requirements in improving product development.”. (ISPS'13 IEEE) Thee‎ 11th International Symposium on Programming and Systems. Publisher's Version

Fateh, Bencherif. 2013. “ Fuzzy relative importance ‎of ‎customer ‎requirements in Improving Product Development”. (ICMSAO IEEE) ‎International ‎Conference on ‎Modelling, Simulation and Applied Optimization. Publisher's Version

Fateh, Bencherif, and Mouss Leila Hayet. 2013. 168 pages Amélioration du processus de développement de produit – Cas d’une entreprise Algérienne, ISSN / ISBN 978-613-1547 27-0 / 6131547270. Editions universitaires Européennes – Germany. Publisher's Version Abstract

Nous nous situons dans un environnement fortement concurrent et dynamique lié à la mondialisation des économies, cette dynamique pousse l’entreprise à innover et à explorer son future et proposer à ses clients la meilleure offre. Les entreprises à travers une transformation réflexive, transforment des entrées en produits et doit prendre des décisions au sujet de la façon de réagir aux besoins du marché et du client et des ressources à allouer. Ces transformations doivent être qualitatives et performantes et le processus de développement, le meneur de cette transformation, soit le noyau de toutes les transformations. Ainsi le processus est incorporé dans tout organisme économique comme facteur de réussite et de mesure de l'internationalisation de l’entreprise. Les approche de développement existantes ne supportent pas de manière optimale les exigences de développement total et l’offre de la concurrence caractérisée par le court délai et le minimum budget et par la qualité de leur offre. Ce travail propose une amélioration par laquelle les entreprises peuvent atténuer les risques de développement et s'assurer que le produit final tend à être exactement ce que le client veut.

Adel, Abdelhadi, and Mouss Leila Hayet. 2013. Algorithms for the integration of Arabic Language in Mobile Phones, ISBN-13: 978-3-659-38488-2 / ISBN-10: 3659384887. Book, LAP Lambert Academic Publishing. Publisher's Version Abstract

This work presents a subject which deals with man machine interfaces. Its objective is to study the data-processing impact of the integration of the Arabic language in mobile phones, in order to make an Arabic man machine interface. The correct display of Arabic characters is essential in a graphic interface, and because Arabic characters change their forms according to the position occupied in a word, it is necessary to make a contextual analysis on each word, to find the correct form of each character. The transformation of two or several characters in only one form, also requires making a particular treatment, as in case of the Arabic ligature LAM-ALEF. The Arabic language has a different direction of writing compared to other languages embedded in mobile phones, which requires finding a bi-directional algorithm that ensures a correct display of SMS messages. These messages can contain characters of different direction, right-to-left, left-to-right or characters without direction. It allows making comprehensible the display of messages.

Benbrahim, Meriem, et al. 2013. “Adaptive type-2 fuzzy sliding mode controller for SISO nonlinear systems subject to actuator faults”. Springer Berlin Heidelberg, International Journal of Automation and Computing Vol. 10 ( issue 4) : pp335-342. Publisher's Version Abstract

In this paper, an adaptive type-2 fuzzy sliding mode control to tolerate actuator faults of unknown nonlinear systems with external disturbances is presented. Based on a redundant actuation structure, a novel type-2 adaptive fuzzy fault tolerant control scheme is proposed using sliding mode control. Two adaptive type-2 fuzzy logic systems are used to approximate the unknown functions, whose adaptation laws are deduced from the stability analysis. The proposed approach allows to ensure good tracking performance despite the presence of actuator failures and external disturbances, as illustrated through a simulation example

Hicham, Aoueg, and Mechenene Athmane. 2013. “Continuous Improvement of Production system in Algerian industry ISSN/ISBN 1694-08141694-0784”. IJCSI International Journal of Computer Science Issues Vol. 10 (Issue 4) : pp.337-344. Publisher's Version Abstract

This paper presents the methodology for process improvement of Algerian Company, which implements a new process by the following of business process reengineering approach. For this, we conducted a comprehensive study of the company activity through a study of the current manufacturing process followed by an evaluation of various performance indicators, this has allowed us to propose a new model production process and identify weaknesses of the activities and services that interact with the company machining process Keywords: Improvement continouus, Kaizen, performance, Réingeneering, Six sigma

Hicham, Aoueg, and Mechenene Athmane. 2013. “Implementation and adaptability of a continuous improvement tool in Algerian industry, ISSN/ISBN 2162-6359”. International Journal of Economics and Management Sciences Vol. 3 (No. 11) : pp. 41-49.

Hicham, Aoueg, and Mechennene Athmane. 2013. “Process Optimization by DMAIC Approach in Algerian Industry, Nov 2013”. IJMIT International Journal of Management, Information and Technology Vol. 7 (No. 2) : pp 1074-1083. Publisher's Version Abstract

The aim of this paper is to contribute to the improvement of the performance of the functioning of the SCIMAT company. For that purpose, we made a diagnosis of all workshops to identify the possible axes of improvement and to choose the solutions to be implemented.This diagnosis is made by implementation of DMAIC methodologyof Six sigma approach at SCIMAT company in Algeria, DMAIC is the five-step approach that makes up the Six Sigma tool kit, and its sole objective is to drive costly variation from manufacturing and business processes. The five steps in DMAIC are Define,Measure,Analyze,Improve, andControl.As the backbone of theSix Sigmamethodology, DMAIC delivers sustained defect-free performance and highly competitive quality costs over the long run.

Ouahab, Kadri, Mouss Leila Hayet, and Mouss Med Djamel. 2013. “Reconnaissance des Formes par SVM pour le Diagnostic du Système de Pasteurisation d’une Usine de Lait, janvier, ISSN 1112-9697”. RST, Revue des Sciences et Technologie Volume 4 (N°1). Publisher's Version Abstract

Dans cet article, nous présentons un nouvel algorithme pour la classification de différents états de fonctionnement et de dysfonctionnement d'un système industriel. Notre algorithme offre une bonne qualité de classification de données. Cet algorithme est basé sur Les Séparateurs à Vastes Marges (SVM). Il permet de classer des données non linéairement séparables. L'algorithme offre aussi la possibilité d'utiliser des bases de données de grandes tailles. Les expériences effectuées sur les bases de données issues d'un système de pasteurisation montrent que notre algorithme fournit de très bons résultats.

Meriem, Benbrahim, and Enounbouli Nadji. 2013. “Adaptive Type-2 Fuzzy Sliding Mode Controller for SISO Nonlinear Systems Subject to Actuator Faults, ISSN/ISBN 1476-8186/1751-8520”. IJAC International Journal of Automation and Computing Vol. 10 ( Issue 4) : pp.335-342. Publisher's Version Abstract

Ouahiba, Chouhal, Mouss Leila Hayet, and Mahdaoui Rafik. 2013. “A Web service Based Multi Agent System for the Diagnosis of industrial plants, May, ISSN/ISBN 1970 – 8734/1970-8742”. IREME International Review of Mechanical Engineering. Vol 5 (N° 6) : pp: 1156-1159. Publisher's Version Abstract

Fault diagnosis and maintenance are considered as vital aspects in industrial process, therefore, fault diagnosis systems should support decision-making tools, new diagnosis approaches and technique. In this paper, we discuss the cooperation of agents and Web Services in order to create highly flexible and dynamic framework for manufacturing systems fault diagnosis based on three-tier architectures that can support a distributed application. We depict also how Web Services can be located and the provided services can be invoked.

Ouahab, Kadri, Mouss Leila Hayet, and Mouss Med Djamel. 2013. “Reconnaissance des Formes par SVM pour le Diagnostic du Système de Pasteurisation d’une Usine de Lait, janvier, ISSN/ISBN 1112-9697”. RST, Revue des Sciences et Technologie Volume 4 (N°1) : p: 283. Publisher's Version Abstract

Eddine, Bellal Salah, and Mouss Leila Hayet. 2013. “Recognition of objects in an image for triage, December, ISSN/ISBN 2250-1355/ 2249-9555”. IJCSITS International Journal of Computer Science, Information Technology, & Security Vol 2 (Issue 6) : pp 1170-1176. Publisher's Version Abstract

In this paper, our aim is to present existing methods and techniques related to the artificial vision which is an active subject of research. In this work, we elaborate a recognition system of objects in an image for a sorting application. The corner stone of our work is based on the recognition and sorting of objects (geometrical shapes) in an image in artificial vision. The application of these images is achieved using a fixed camera having a regular and permanent field of vision with a consequent angle on a conveyer which holds the objects to be observed. The Objects' recognition process requires knowledge of our camera characteristics. In order to calibrate this camera, we propose to use a simple Web camera configured to get a photo of the conveyer's centre. The objective is to seek for objects in the images, which are considered as unitary and not sequences of images. In this case, the development of automatic methods is required to ensure the sorting rapidity but with additional complex processing to make it efficient. The analysis determines simultaneously both the recensement and arithmetic counting, then the detection of faults based mainly on the comparison of the object shape with the shape defined previously and using this operation the sorting is made. A complementary system equipped with sensors and programmable automata is used to eject each object into corresponding panel.

Adel, Abdelhadi, and Mouss Leila Hayet. 2013. “An efficient hybrid approach based on multi agent system and emergence method for the integration of systematic preventive maintenance policies in hybrid flow-shop scheduling to minimize makespan, September 2013, ISSN/ISBN: 2141-2383.”. Journal of Mechanical Engineering Research 05 (06) : 112-122 . Publisher's Version Abstract

This paper proposes a novel hybrid algorithm for the integration of systematic preventive maintenance policies in hybrid flow shop scheduling to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time and methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Quo Vadis Machine Learning-Based Systems Condition Prognosis?—A Perspective

Benbouzid, Mohamed, and Tarek Berghout. 2023. “Quo Vadis Machine Learning-Based Systems Condition Prognosis?—A Perspective”. Electronics 12 (3) : 527. Publisher's Version Abstract

Data-driven prognostics and health management (PHM) is key to increasing the productivity of industrial processes through accurate maintenance planning. The increasing complexity of the systems themselves, in addition to cyber-physical connectivity, has brought too many challenges for the discipline. As a result, data complexity challenges have been pushed back to include more decentralized learning challenges. In this context, this perspective paper describes these challenges and provides future directions based on a relevant state-of-the-art review.

Lithium-ion Battery State of Health Prediction with a Robust Collaborative Augmented Hidden Layer Feedforward Neural Network Approach

Berghout, Tarek, et al. 2023. “Lithium-ion Battery State of Health Prediction with a Robust Collaborative Augmented Hidden Layer Feedforward Neural Network Approach”. IEEE Transactions on Transportation Electrification. Publisher's Version Abstract

Lithium-ion (Li-ion) batteries play an important role in providing necessary energy when acting as a main or backup source of electricity. Indeed, the unavailability of battery aging discharge data in most real-world applications makes the State of Health (SoH) assessment very challenging. Alternatively, accelerated aging is therefore adopted to emulate the degradation process and to achieve an SoH estimate. However, accelerated aging generates limited deterioration patterns suffering from a higher level of complexity due to the non-linearity and non-stationarity imposed by harsh conditions. In this context, this paper aims to provide a predictive model capable of solving incomplete data problems by providing two main solutions for each of the problems of complexity and missing patterns, respectively. First, to overcome the problem of lack of patterns, a robust collaborative feature extractor (RCFE) is designed by collaborating between a set of improved restricted Boltzmann machines (I-RBMs) to be able to share learning knowledge among different locally trained I-RBMs to create a more generalized global extraction model. Second, a set of RCFEs is then evolved through a neural network with an augmented hidden layer (NAHL) to enhance the predictive ability by further exploring representation learning to overcome pattern complexity issues. The designed RCFE-NAHL is trained to predict SoH using constant current (CC) discharge characteristics by implying multiple characteristics recorded through the constant voltage (CV) charging process as indicators of health. The proposed SoH prediction approach performances are evaluated on a set of battery life cycles from the well-known NASA database. In this context, the achieved results clearly highlight the higher accuracy and robustness of the proposed learning model.

2DF-IDS: Decentralized and differentially private federated learning-based intrusion detection system for industrial IoT

Othmane, Friha, et al. 2023. “2DF-IDS: Decentralized and differentially private federated learning-based intrusion detection system for industrial IoT”. Computers & Security 127. Publisher's Version Abstract

Advanced technologies, such as the Internet of Things (IoT) and Artificial Intelligence (AI), underpin many of the innovations in Industry 4.0. However, the interconnectivity and open nature of such systems in smart industrial facilities can also be targeted and abused by malicious actors, which reinforces the importance of cyber security. In this paper, we present a secure, decentralized, and Differentially Private (DP) Federated Learning (FL)-based IDS (2DF-IDS), for securing smart industrial facilities. The proposed 2DF-IDS comprises three building blocks, namely: a key exchange protocol (for securing the communicated weights among all peers in the system), a differentially private gradient exchange scheme (achieve improved privacy of the FL approach), and a decentralized FL approach (that mitigates the single point of failure/attack risk associated with the aggregation server in the conventional FL approach). We evaluate our proposed system through detailed experiments using a real-world IoT/IIoT dataset, and the results show that the proposed 2DF-IDS system can identify different types of cyber attacks in an Industrial IoT system with high performance. For instance, the proposed system achieves comparable performance (94.37%) with the centralized learning approach (94.37%) and outperforms the FL-based approach (93.91%) in terms of accuracy. The proposed system is also shown to improve the overall performance by 12%, 13%, and 9% in terms of F1-score, recall, and precision, respectively, under strict privacy settings when compared to other competing FL-based IDS solutions.

Faulty Detection System Based on SPC and Machine Learning Techniques

Benrabah, Mohamed-Elamine, Ouahab Kadri, and Nadia-Kenza Mouss. 2023. “Faulty Detection System Based on SPC and Machine Learning Techniques”. Revue de l’Intelligence Artificielle : 969-977. Publisher's Version Abstract

Starting from a worrying observation, that companies have difficulties controlling the anomalies of their manufacturing processes, in order to have a better control over them, we have realized a case study on the practical data of the Fertial Complex to analyze the main parameters of the ammonia neutralization by nitric acid process. This article proposes a precise diagnostic of this process to detect dysfunction problems affecting the final product. We start with a general diagnosis of the process using the SPC method, this approach is considered an excellent way to monitor and improve the product quality and provides very useful observations that allowed us to detect the parameters that suffer from problems affecting the quality. After the discovery of the parameters incapable to produce the quality required by the standards, we applies two machine learning technologies dedicated to the type of data of these parameters for detected the anomaly, the first technique called The kernel connectivity-based outlier factor (COF) algorithm consists in recording for each object the degree of being an outlier, the second technique called the Isolation Forest, its principle is to establish a forest to facilitate the calculation and description. The results obtained were compared in order to choose which is the best algorithm to monitor and detect the problems of these parameters, we find that the COF method is more efficient than the isolation forest which leads us to rely on this technology in this kind of process in order to avoid passing a bad quality to the customer in future.

IoT-based food traceability system: Architecture, technologies, applications, and future trends

Mehannaoui, Raouf, Kinza-Nadia Mouss, and Karima Aksa. 2023. “IoT-based food traceability system: Architecture, technologies, applications, and future trends”. Food Control 145. Publisher's Version Abstract

An effective Food Traceability System (FTS) in a Food Supply Chain (FSC) should adequately provide all necessary information to the consumer(s), meet the requirements of the relevant agencies, and improve food safety as well as consumer confidence. New information and communication technologies are rapidly advancing, especially after the emergence of the Internet of Things (IoT). Consequently, new food traceability systems have become mainly based on IoT. Many studies have been conducted on food traceability. They mainly focused on the practical implementation and theoretical concepts. Accordingly, various definitions, technologies, and principles have been proposed. The “traceability” concept has been defined in several ways and each new definition has tried to generalize its previous ones. Nevertheless, no standard definition has been reached. Furthermore, the architecture of IoT-based food traceability systems has not yet been standardized. Similarly, used technologies in this field have not been yet well classified. This article presents an analysis of the existing definitions of food traceability, and thus proposes a new one that aims to be simpler, general, and encompassing than the previous ones. We also propose, through this article, a new architecture for IoT-based food traceability systems as well as a new classification of technologies used in this context. We do not miss discussing the applications of different technologies and future trends in the field of IoT-based food traceability systems. Mainly, an FTS can make use of three types of technologies: Identification and Monitoring Technologies (IMT), Communication Technologies (CT), and Data Management Technologies (DMT). Improving a food traceability system requires the use of the best new technologies. There is a variety of promising technologies today to enhance FTS, such as fifth-generation (5G) mobile communication systems and distributed ledger technology (DLT).

Laboratoire D'automatique et Productique