Wafik Hachicha

Abstract: Healthcare waste management is one of the most important environmental problems in the world and particularly in Tunisia, because of the potential environmental hazards and public health risks. The collection of infectious healthcare waste is a highly visible and important service that involves large expenditures. This study discusses the off-site transport problem of infectious healthcare waste from the 12 hospitals in the governorate of Sfax (Tunisia) to a planned steam sterilization disposal centre. This problem of transportation is modelled as capacitated vehicle routing problem (CVRP). Experimental results are reported for the proposed real-life case study from using the solver CPLEX 9.0 software as an interactive optimizer tool. The robust proposed solution method can be considered to be important for a licensed company or for the Sfax municipality for healthcare-wastes transportation system and for CVRP practitioners.

Abstract: The objective of this paper is to develop a framework that integrates two important concepts: Statistical process control (SPC) and engineering process control (EPC). Most of the literature researches on integrated SPC/EPC systems are focused into continuous process mainly with Algorithmic SPC. The integrated SPC/EPC systems in batch process control have not received the same degree of attention. In particular, there is an only Run-to-Run (RTR) control methodology application which is mostly focused in semiconductor industry. This paper is a first of its kind in integrated SPC/EPC systems that applied in batch process and based on data-driven quality improvement tools. The proposed SPC/EPC integration is performed continually in two successive phases: (1) Active SPC for the batch making advance, and (2) RTR control action between batches. Control limits for critical variables are developed using information from the historical reference distribution of past successful batches. EPC application is based on the development of progressive knowledge-based rules. For a validation purpose, the proposed approach is applied to data collected from an industrial batch alkyd polymerization reactor which evolution is monitored by measuring the overflow water weight, the acidity index and the viscosity of samples withdrawn from the reactor. This industrial process is poorly automated, subject to several disturbances, and the batches have uneven lengths. The synthesis is stopped at the maximum yield allowed by the gelation point of the cold product. Through this case study application, process engineers at the company are now able to use a valuable decision making tool when the production process is affected by certain disruptions, with obvious consequences on product quality, productivity and competitiveness.

Abstract: The first step in the design of a cellular manufacturing (CM) system is the cell formation (CF) problem, which involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. A large number of CF techniques have been developed through the years. Unfortunately, theses techniques consider only a single objective in identifying cells which could make the final configuration unsuitable for implementation since factors such as the possible existence of exceptional elements (EE) in the final solution and the possible availability of multiple units of each type of machines. The objective of this paper is to valorize previous CF techniques. In other words, the proposed approach is designed to be used after the CF process is completed, regardless of the method taken from literature to create an initial CF solution. It carried out in two phases. In the first phase, a simulation-based methodology is applied for sizing each manufacturing cell machines. In the second phase, the same simulation model is used to deal with each EE in order to create better cell configurations. The objective is to analyze and to compare the cost associated with alternative actions for the removal of the EE: an exceptional machine can be duplicated, or a part may be subcontracted. All simulation studies which take into account the stochastic aspect in the CM system are realized by the software Arena. The process is demonstrated with a numerical example.

Abstract: Simulation project requires highly qualified multidisciplinary staff rarely available in a Small and medium-sized enterprise (SME). The aim of this paper is to develop a computerassisted performance analysis and optimization (CPAO) to help a SME manager which is considered in this paper as an inexperienced user in applying a simulation project without using explicitly the ARENA® software. After the design of the suitable simulation model with ARENA® software by an expert simulation modeler, the inexperienced user of CPAO can operate the process of simulation and optimization easily and simply. Major manipulations include the following. (1) The setting of possible configurations. (2) The statistical analysis and graphical analysis of simulation results. (3) The improvement and the optimization of some criteria. The developed CPAO application is carried out in two steps. Firstly, the Unified Modeling Language (UML) is employed for the CPAO phase. Secondly, Visual Basic Administration (VBA) language is exploited to develop various User Forms dialogues with the inexperienced user, ARENA software, Ms Excel and Ms Access. Finally, for the simulation optimization technique, the simulated annealing (SA) algorithm is adopted. To demonstrate and validate CPAO results, an illustrative example which is considered a manufacturing lines system with buffer stocks design problem is fully detailed.

Abstract: Control Chart Pattern Recognition (CCPR) is a critical task in Statistical Process Control (SPC). Abnormal patterns exhibited in control charts can be associated with certain assignable causes adversely affecting the process stability. Abundant literature treats the detection of different Control Chart Patterns (CCPs). In fact, numerous CCPR studies have been developed according to various objectives and hypotheses. Despite the widespread literature on this topic, efforts to review and analyze research on CCPR are very limited. For this reason, this survey paper proposes a new conceptual classification scheme, based on content analysis method, to classify past and current developments in CCPR research. More than 120 papers published on CCPR studies within 1991-2010 were classified and analyzed. Major findings of this survey include the following. (1) The most popular CCPR studies deal with independently and identically distributed process data. (2) Some recent studies on identification of mean shifts or/and variance shifts of a multivariate process are based on innovative techniques. (3) The percentage of studies that address concurrent pattern identification is increasing. (4) The majority of the reviewed articles use Artificial Neural Network (ANN) approach. Feature-based techniques, in particular wavelet-denoise, are investigated for improving the recognition performance of ANN. For the same reason, there is a general trend followed by many authors who propose hybrid, modular and integrated ANN recognizer designs combined with decision tree learning, particle swarm optimization, etc. (5) There are two main categories of performance criteria used to evaluate CCPR approaches: statistical criteria that are related to two conventional Average Run Length (ARL) measures, and recognition-accuracy criteria, which are not based on these ARL measures. The most applied criteria are recognition-accuracy criteria, mainly for ANN-based approaches. Performance criteria which are related to ARL measures are insufficient and inappropriate in the case of concurrent pattern identification. Finally, this paper briefly discusses some future research directions and our perspectives.

Abstract: Simulation is essentially a trial-and-error approach, and is therefore, time-consuming and does not provide a method for optimization. Metamodelling techniques have been recently pursued in order to tackle these drawbacks. The main objective has been to provide robust, fast decision support aids to enhance the overall effectiveness of decision-making processes. This paper proposes an application of simulation metamodelling through artificial neural networks (ANNs). The building of the appropriate ANN model over second-order linear regression model and the reverse simulation metamodelling as simulation-optimization are assisted by the Neuro® Software. To validate the proposed approach, a case study which is adopted from literature, deals with a lot sizing problem in make-to-order supply chain. The optimal solution is to determine the fixed lot size for each manufacturing product type that will ensure order mean flow time target. The comparative results with others metamodels techniques; illustrate the efficiency and effectiveness of the proposed approach.

Abstract: Simulation Optimization (SO) provides a structured approach to the system of design and configuration when analytical expressions for input/output relationships are unavailable. SO has attracted considerable research attention in the recent past. Despite the growing body of literature on this topic, precious little effort has been devoted to synthesizing the overall state of art of research on SO. In this paper, an attempt is made to review the status of literature on SO. A new literature review scheme is presented. Also the literature affectation is presented since 1995 up to now. We have classified techniques for SO into four groups: (i) Statistical Selection Methods, (ii) Metamodel Methods, (iii) Stochastic Gradient Estimation, and (iv) Global Search Methods. Therefore, a literature affectation is presented since 1995. It is concluded that during the period since 2004, there are a shift trend towards of global search methods.

Abstract: This paper develops a simulation optimisation approach for solving the Lot-Sizing Problem (LSP) in Make-to-Order (MTO) supply chain. For this purpose, a discrete event simulation model was firstly implemented as a tool in estimating Order Mean Flow Time (OMFT) performance. Secondly, a multiple-objective optimisation was achieved by applying Response Surface Methodology (RSM). A comprehensive case study is detailed which involves a multi-product, multi-stage, multi-location production planning with capacity-constrained and stochastic parameters such as lot arrivals order, transit time, set-up time, processing time, etc. The objective of the proposed approach is to determine the fixed optimal lot size for each manufacturing product type that will ensure OMFT target value for each finished product type. The study results illustrate that the LSP in MTO sector is viable and provide a prototype for further research on simulation optimisation approaches.

Abstract: La formation des cellules (FC) de production se traduit par le groupement des produits en familles et le partage des machines en sous groupes. Le traitement de ce problème devient plus complexe en présence de gammes alternatives. Dans ce contexte, nous proposons une nouvelle approche qui traite ce problème en deux niveaux. Le premier niveau porte sur l�application de la méthode des plans d�expériences. L�objectif étant de choisir, pour chaque produit, la gamme préférentielle permettant l�optimisation des indicateurs de performance de FC. En plus, ce niveau de traitement permet une analyse de la sensibilité de la solution finale ignorée par les techniques antérieures de la FC. Nous avons proposé et justifié un nouvel indice de la FC défini par le pourcentage de conservation des données de la matrice d�incidence initiale. Le second niveau de traitement consiste à appliquer la méthode de la FC basée sur l�analyse des corrélations statistiques entre les différents produits et machines. Pour expliquer l�approche proposée, nous avons détaillé deux exemples numériques. Les résultats d�une analyse comparative appliquée à des problèmes reconnus en littérature, ont permis de valider l�approche proposée. Cell formation (CF) problem involves grouping parts into families and machines into cells. The CF problem becomes extra complicated if parts are assigned with alternative routings. In this context, we propose a new two-phase approach. The first phase is based on Designed of Experiments. The objective is to realize the best alternative routing for each part in term of CF performance criteria. In addition, the result goes across and beyond the previous CF procedures by providing a sensitivity analysis aspect. A new performance criterion which is based on the percentage of conservation of incidence matrix data is proposed and validated. The second phase consists in applying CF based on correlation analysis to cluster the machines and parts. In order to illustrate the two phases of the proposed approach, two numerical examples are provided. Furthermore, the results of a comparative study based on multiple performance criteria show that the present approach is valid.

Abstract: Cellular manufacturing (CM) is an important application of group technology (GT) that can be used to enhance both flexibility and efficiency in today�s small-to-medium lot production environment. The crucial step in the design of a CM system is the cell formation (CF) problem which involves grouping parts into families and machines into cells. The CF problem are increasingly complicated if parts are assigned with alternative routings (known as generalized Group Technology problem). In most of the previous works, the route selection problem and CF problem were formulated in a single model which is not practical for solving large-scale problems. We suggest that better solution could be obtained by formulating and solving them separately in two different problems. The aim of this case study is to apply Taguchi method for the route selection problem as an optimization technique to get back to the simple CF problem which can be solved by any of the numerous CF procedures. In addition the main effect of each part and analysis of variance (ANOVA) are introduced as a sensitivity analysis aspect that is completely ignored in previous research. The case study results provided a better CF solution compared with Kusiak�s solution.

Abstract: The important step in the design of a cellular manufacturing (CM) system is to identify the part families and machine groups and consequently to form manufacturing cells. The scope of this article is to formulate a multivariate approach based on a correlation analysis for solving cell formation problem. The proposed approach is carried out in three phases. In the first phase, the correlation matrix is used as similarity coefficient matrix. In the second phase, Principal Component Analysis (PCA) is applied to find the eigenvalues and eigenvectors on the correlation similarity matrix. A scatter plot analysis as a cluster analysis is applied to make simultaneously machine groups and part families while maximizing correlation between elements. In the third stage, an algorithm is improved to assign exceptional machines and exceptional parts using respectively angle measure and Euclidian distance. The proposed approach is also applied to the general Group Technology (GT) problem in which exceptional machines and part are considered. Furthermore, the proposed approach has the flexibility to consider the number of cells as a dependent or independent variable. Two numerical examples for the design of cell structures are provided in order to illustrate the three phases of proposed approach. The results of a comparative study based on multiple performance criteria show that the present approach is very effective, efficient and practical.

Abstract: Cellular Manufacturing (CM) system has been recognized as an efficient and effective way to improve productivity in a factory. In recent years, there have been continuous research efforts to study different facet of CM system. They are developed to satisfy only one or limited functional requirements of the CM system design. The literature does not contain much published research on CM design which includes all design aspects. In this paper we provide a framework for the complete CM system design. It combines Axiomatic Design (AD) and Experimental Design (ED) to generate several feasible and potentially profitable designs. The AD approach is used as the basis for establishing a systematic CM systems design structure. ED has been a very useful tool to design and analyze complicated industrial design problems. AD helps secure valid input-factors to the ED. An element of the proposed framework is desmontrate through a numerical example for a cell formation problem with alternative process.

Abstract: This paper presents a cost estimation model of weld assemblages. It is based on the product decomposition into parts and then into assemblages. The study is about a proposition of an original definition of welding and preparing features attributed to each assemblages. It is based on knowledge modelling at the level of process and product perception. The decomposition of the product into features and the identification of cost features remain manual. The proposed model consists in combining two cost estimating model applied to the products and to the processes. First, we have used an analytic model for the formalizing of the welding time, of the electrode consumption and of gas consumption according to the different parameters of the preparing and the welding features. Second, we have used the parameter method for the cost structuring caused by the different feature-cost (cost entity) preparing and by the feature-cost welding.

Abstract: This article presents a system of computer aided costs of weld operations by welding for mechanical assemblages. We propose a system based on the combination of two cost estimation methods: on one hand we use the analytic method to formulate the time for weld and for gas and filling metal consumption according to the different parameters of preparing and welding features. The estimating is based upon an evaluation of the filling metal mass used in the welding process. On the other hand, we use the parametric method for the structuring of costs generated by the different features costs which compose the welding process: preparing, pointing and welding. In this case, the estimating is based on the structure of inductors suitable for the scale of each feature. The system we have developed has been implemented with Microsoft Access which permits us to rapidly and efficiently define important and strong data base. The latter constitutes in majority a library of expertise for the enterprise such as the used processes, the preparations, the metals, etc. At last, and to show the developed methods interest and the efficiency of the model, we have treated an industrial project proposed by a collaborating enterprise. The results obtained compared to real time made by welding staff prove the rapidity and the accuracy of the model we have developed.

Abstract: Cell Formation (CF) problem involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. Many researches have suggested methods for CF. Few of these methods; have addressed the possible existence of exceptional elements (EE) in the solution and the effect of correspondent intercellular movement, which cause lack of segregation among the cells. This paper presents a simulation-based methodology, which takes into consideration the stochastic aspect in the cellular manufacturing (CM) system, to create better cell configurations. An initial solution is developed using any of the numerous CF procedures. The objective of the proposed method which provides performances ratings and cost-effective consist in determine how best to deal with the remaining EE. It considers and compares two strategies (1) permitting intercellular transfer and (2) exceptional machine duplication. The process is demonstrated with a numerical example.

Abstract: The crucial step in the design of a Cellular Manufacturing (CM) system is the Cell Formation (CF) problem. This problem consists of identifying the part families and the machine groups and, consequently, forming manufacturing cells. The aim of this paper is to formulate a new multivariate approach based on a correlation analysis for solving CF problem. The proposed approach is carried out in two phases. In the first phase, the correlation matrix is used as similarity coefficient matrix. In the second phase, Principal Component Analysis (PCA) is applied as a cluster analysis to make simultaneously machine groups and part families. This approach integrates significant production data such as processing time and part type production volume in the early stages of grouping decisions for CM. The objective is to minimise the total processing time outside the cells. Two illustrative examples and numerical results are provided.

Abstract: This paper deals with the lot sizing problem in Make To Order (MTO) supply chain solved by simulation optimization (SO) approach. A comprehensive case study is detailed which involves a multi-stage, multi-product, multi-location, multi-resource with setup, capacity constraints and stochastic demand. The case study objective is to determine a fixed optimal lot size for each manufacturing product type that will ensure Order Mean Flow Time (OMFT) target value for each finished product type. For a comparison purpose, three SO methods are used: (1) A metamodel method based on Response Surface Methodology (RSM), (2) A metamodel method based on Design of Experiment, and (3) Global Search method based simultaneously on Tabu Search, Neural Networks, and Scatter Search. Methods (1) and (2) have been treated in the literature with a manual based approach, while the method (3) that will be more addressed in this paper, using the OptQuest Software. The results of the comparative study between the three methods show that the first one which is based on RSM is very effective while the third method is very practical and gives a good satisfactory solution.

Abstract: Simulation is a widely accepted tool in complex systems design and analysis. However, it is essentially a trial-and-error approach, and is therefore, time-consuming and does not provide a method for optimization. Metamodeling techniques have been recently pursued in order to tackle these drawbacks. The main objective has been to provide robust, fast decision support aids to enhance the overall effectiveness of decision-making processes. This paper proposes an application of simulation metamodeling through artificial neural networks (ANNs). The proposed approach is composed of two main steps assisted successively by the ©Neuro Software. The first one consists of building the appropriate ANN model over second-order linear regression model. Based on this model, the second step is a reverse simulation metamodeling that will be used as an optimization tool. To validate the proposed approach, a real case study is adopted from literature (Yang and Tseng [1]). It concerns an anonymous integrated-circuit (IC) packaging company in Taiwan. The case study problem is to maximize throughput performance. The comparative results with Response Surface Methodology (RSM) based metamodel results; illustrate the efficiency and effectiveness of the proposed approach.

Abstract: Le problème de la conception des lignes de production (CLP) fait l�objet de plusieurs recherches dans la littérature. Ces différentes recherches ont étudié seulement quelques points relatifs à la CLP. Il est rare de proposer une méthodologie complète pour la CLP. C�est dans ce cadre que s�inscrit ce travail. Il s�agit d�appliquer, successivement, la technique SADT (Systematic Analysis and Design Technique) et la méthode de la Conception Axiomatique (CA) pour proposer un modèle conceptuel pour la CLP et plus particulièrement, d�une ligne d�assemblage semi-automatique à produits multiples. Enfin, nous avons mené une étude pratique dans une société industrielle, ceci pour montrer l�intérêt de la démarche proposée. Ainsi, nous avons remarqué sa simplicité de mise en �uvre et son efficacité. In recent years, there have been continuous research efforts to study different facets of the problems of production line design (PLD). The literature does not contain much published research on PLD which includes all design aspects. In this paper we provide a conceptual design framework for PLD which is based on the SADT (Systematic Analysis and Design Technique) technique and the Axiomatic Design (AD) method. The conceptual design framework is valid for any production line in particular for a semiautomatic assembly line that produces the various products. Finally, for a confirmation purpose, the proposed conceptual design framework

Abstract: Nowadays, many companies have been shifting its production strategy from the make-to-stock (MTS) to the make-to-order (MTO) sector. However, most of literature research on production planning concentrates on MTS systems. The MTO area has not received the same degree of attention. There are only some research papers which are based on queueing network models that explicitly talk about the Lot Sizing Problem (LSP) in MTO sector. This paper presents a case study in MTO sector for which analytical model is still extremely complex up to now (multi-stage, multi-product, multi-location, multi-resource with setup, capacity constraints and stochastic demand). The objective is to determine a fixed optimal lot size for each manufacturing product type that will ensure Order Mean Flow Time (OMFT) target value for each finished product type. The adopted approach is carried out in three steps. A Discrete Event Simulation (DES) model was firstly implemented as a tool in estimating (OMFT) performance. Secondly, Design of Experiment is applied to conduct simulation experiments. Finally, a multiple-objective optimization is achieved by applying desirability optimization methodology. The study results illustrate that the LSP in MTO sector is viable and provides a prototype for further research in supply chain coordination

Abstract: Simulation Optimization (SO) provides a structured approach to the system design and configuration when analytical expressions for input/output relationships are unavailable. Several excellent surveys have been written on this topic. Each survey concentrates on only few classification criteria. This paper presents a literature survey with all classification criteria on techniques for SO according to the problem of characteristics such as shape of the response surface (global as compared to local optimization), objective functions (single or multiple objectives) and parameter spaces (discrete or continuous parameters). The survey focuses specifically on the SO problem that involves single per-formance measure.

Abstract: Cellular manufacturing (CM) is an important application of group technology (GT) that can be used to enhance both flexibility and efficiency in today�s small-to-medium lot production environment. The crucial step in the design of a CM system is the cell formation (CF) problem which involves grouping parts into families and machines into cells. The CF problem are increasingly complicated if parts are assigned with alternative routings (known as generalized Group Technology problem). In most of the previous works, the route selection problem and CF problem were formulated in a single model which is not practical for solving large-scale problems. We suggest that better solution could be obtained by formulating and solving them separately in two different problems. The aim of this case study is to apply Taguchi method for the route selection problem as an optimization technique to get back to the simple CF problem which can be solved by any of the numerous CF procedures. In addition the main effect of each part and analysis of variance (ANOVA) are introduced as a sensitivity analysis aspect that is completely ignored in previous research. The case study results provided a better CF solution compared with Kusiak�s solution.

Abstract: Cellular Manufacturing (CM) system has been recognized as an efficient and effective way to improve productivity in a factory. In recent years, there have been continuous research efforts to study different facet of CM system. The literature does not contain much published research on CM design which includes all design aspects. In this paper we provide a framework for the complete CM system design. It combines Axiomatic Design (AD) and Experimental Design (ED) to generate several feasible and potentially profitable designs. The AD approach is used as the basis for establishing a systematic CM systems design structure. ED has been a very useful tool to design and analyze complicated industrial design problems. AD helps secure valid input-factors to the ED. An element of the proposed framework is desmontrate through a numerical example for cell formation with alternative process.

Abstract: R�SUM�. La Maîtrise Statistique des Procédés (MSP) et le Contrôle Automatique des Procédés (CAP) poursuivent un même objectif : réduire la variabilité du procédé et le garder sur la cible. Ce travail porte sur la proposition d�un modèle d�intégration du CAP dans la MSP qui se base sur la discrétisation des fonctions de transfert relatives à chaque composante du procédé. Nous avons proposé d�une part, une nouvelle règle de contrôle qui se base sur un système de premier ordre. D�autre part, nous avons montré comment établir des cartes de contrôle à un procédé de type AR (1). A l�aide d�expériences de simulation, nous avons montré que la règle que nous avons proposée a réduit la variabilité en la comparant à celle proposée en littérature. ABSTRACT. The Statistical Process Control (SPC) and the Automated Process Control (APC) have a common goal: achieve optimal product quality by controlling variations in the process. The work in this paper will present a developed integration methodology of the APC in the SPC which is based on discretization of the transfer functions relating to each component of the process. We proposed on the one hand, a new control rule which is based on a system of first order. In the other hand, we showed how to establish control charts to a process of the type AR (1). Using simulation experiments, we showed that the proposed control rule reduced variability by comparing it with that proposed in literature.

Abstract: The important step in Cellular Manufacturing (CM) system design is the cell formation (CF) problem which involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. Many researches have suggested methods for CF. Few of these methods; have addressed the possible existence of exceptional elements (EE) in the solution and the effect of correspondent intercellular movement, which cause lack of segregation among the cells. This paper presents a simulation-based methodology, which takes into consideration the stochastic aspect in the CM system, to create better cell configurations. An initial solution is developed using any of the numerous CF procedures. The proposed method which provides performances ratings and cost-effective consist in determine how best to deal with the remaining EE. It considers and compares exceptional machines duplication with permitting intercellular transfer cost. The process is demonstrated with a numerical example.

Abstract: En technologie de groupe, plusieurs travaux de recherche ont proposé des méthodes pour la formation des cellules de production. Généralement, ces méthodes négligent l�effet en-gendré par la présence de machines ou de produits exceptionnels dans leurs solutions. Partant d�une solution initiale de réparti-tion des machines en cellules comportant des éléments excep-tionnels, ce travail présente une approche par simulation permet-tant d�évaluer puis d�améliorer la performance des cellules de production. Deux stratégies, basées sur l�optimisation des coûts de transfert et d�investissement, ont été étudiée : la première consiste à admettre les machines exceptionnelles et la deuxième traite le cas de dupliquer ces machines pour éliminer les trans-ferts entre cellules.

Abstract: In this paper, we consider the problem of forming machine cell in cellular manufacturing (CM). The major problem in the design of a CM system is to identify the part families and machine groups and consequently to form manufacturing cells. The aim of this article is to formulate a multivariate approach based on a correlation analysis for solving cell formation problem. The proposed approach is carried out in two phases. In the first phase, the correlation matrix is used as an original similarity coefficient matrix. In the second phase, Principal Component Analysis (PCA) is applied to find the eigenvalues and eigenvectors on the correlation similarity matrix. A scatter plot analysis as a cluster analysis is applied to make machine groups while maximizing correlation between elements. A numerical example for the design of cell structures is provided in order to illustrate the proposed approach. The results of a comparative study based on multiple performance criteria show that the present approach is very effective, efficient and practical

Abstract: Cet article présente un modèle d�estimation des coûts des assemblages par soudage. Il est basé sur la décomposition du produit en pièces et par la suite en assemblages. L�étude porte sur une proposition d�une définition originale des entités de préparation et de soudage attribuées pour chaque assemblage. Il consiste en premier lieu à utiliser une méthode analytique pour modéliser les temps de soudage et cela nous permet dans un second lieu à développer par la méthode paramétrique la structuration des coûts engendrés par les différentes Entité Coût Préparation et Entités Coût Soudage. This paper presents a cost estimation model of weld assemblages. It is based on the product decomposition into parts and then into assemblages. The study is about a proposition of an original definition of welding and preparing features attributed to each assemblages. The proposed model consists in combining two cost estimating model applied to the products and to the processes un one hand, we have use an analytic model for the formalizing of the welding time, of the electrode consumption and of gas consumption according to the different parameters of the preparing and the welding features. The decomposition into features allows to formalize the time estimating expertise related to the welding.

Abstract: On a entamé ce rapport par une modélisation d�un assemblage soudé qui a permis d�introduire la notion entité de soudage et entité de préparation. Le modèle d�estimation des temps des assemblages soudés est basé sur la définition d�une matrice d�assemblage et la décomposition du produit en entités. Le modèle proposé consiste à combiner deux méthodes d�estimation des coûts appliquées au produit et au processus : d�une part, on a utilisé la méthode analytique pour la formalisation du temps de soudage, de consommation d�électrode et de gaz en fonction des différents paramètres des entités de soudage et de préparation. L�estimation est basée sur une évaluation de la masse du métal d�apport. D�autre part, on a utilisé la méthode paramétrique pour la structuration des coûts engendrés par les différentes Entités Coût qui composent le processus de soudage : préparation, pointage et soudage. Dans ce cas, l�estimation est fondée sur la structuration d�inducteur convenable à l�échelle de chaque Entité Coût. Enfin, on a développé une base de données qui repose sur le modèle développé. La maquette logicielle qui a été mise en �uvre avec Microsoft Access, est susceptible d�apporter une estimation des temps et des coûts. Enfin, pour montrer l�efficacité du modèle, on a traité d�une part, un projet industriel proposé par l�entreprise MDI et d�autre part, on a mené une étude comparative avec l�application DEVISOUD conçu par le CETIM Senlis, France.

Abstract: The aim of this work is to propose new approaches for the design of cellular manufacturing (CM) and principally for the cell formation (CF) which is consist in identifying the part families and machine groups. The scope of the first approach is to formulate a multivariate approach based on a correlation analysis for solving CF problem. The correlation matrix is used as similarity coefficient matrix. A scatter plot analysis is applied as a cluster analysis to make simultaneously machine groups and part families. Finally, an algorithm is improved to assign exceptional machines and exceptional parts. The CF problem are increasingly complicated if parts are assigned with alternative routings. The second proposed approach is a first of its kind in CM literature that based on Taguchi method as an optimization technique for the route selection problem which consist in determining a unique route for each part. The obtained result goes across and beyond the previous researches by providing the main effect of each part as a sensitivity analysis aspect. In the third proposed approach, we provide a framework for the complete CM system design which combines Axiomatic Design and Experimental Design to generate several feasible and potentially profitable designs. T

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