Unité de recherche de Mécanique, Modélisation et Production (U2MP), Tunisia Département de génie mécanique, Ecole Nationale d’ingénieurs de Sfax, Tunisia
faouzi.masmoudi@enis.rnu.tn
Faouzi Masmoudi has obtained PhD in Computer-Integrated Manufacturing (1988) from ENSAM Paris – France. He is a Professor at the National School of Engineers of Sfax in Tunisia, and a Researcher at the Mechanics Modelling and Production Research Unit (U2MP). The activities of research are: modelling and simulation of manufacturing systems; design and layout of the cellular systems of production; and simulation of manufacturing cells with unreliable machines.
Abstract: Assessing customer trust in suppliers with regards to its influencing factors is an important open issue in supply chain management literature. In this paper, a customer trust index is designed as the trust level arising from the information sharing degree and quality, related to the information shared by a supplier with his customer. The customer trust level is evaluated using a fuzzy decision support system integrating information sharing dimensions. The core is a rule-based system designed using the results of questionnaires and interviews with supply chain experts. Several tests were generated in order to analyze the impact of the different information sharing attributes on the customer trust index. The developed approach is then applied to a real supply chain from the textile industry. Results show large differences of weight and impact between the different information-related factors that build the customer trust index. It is also shown that the proposed system has an important role in ensuring the objectivity of the trust assessment process and in helping decision makers evaluate their business partners.
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: This paper describes the development of a process simulation model and integration of the Genetic Algorithms (GA) with the model as optimisation techniques using a case study of Lot Sizing Problem (LSP) in Make To Order (MTO) supply chain solved by a combined simulation and Genetic Algorithm (GA) optimization model. The simulation model is performed using ARENA software. GA model is implemented using Visual Basic for Application (VBA) language, because it ensures exchanges between ARENA software and Ms Excel. The case studyâs objective is to determine 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 OptQuest software, which is used a global search method, to illustrate the efficiency and effectiveness of the proposed approach.
Notes: This article is a revised and extended version presented at International Conference on Advanced Logistics and Transportation (ICALT) 2013, Sousse, Tunisia, 29-31 May 2013
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: This paper studies the flexible flow shop (FFS) NPâhard scheduling problem with the availability constraints to minimise the makespan. We used implicitly Branch and Bound through developing three different new mixed integer linear programming (MILP) to model the problem based on different definitions of the decision variables. We studied the efficiency of the model proposed in terms of a computational resolution and of the quality of the linear lower bound by using ILOGâCplex solver. The experimentations which are carried out show that we can optimally solve the problems up to ten jobs and within four stages using three parallel machines per stage within several minutes of process time (CPU). We find that two proposed MILP show good results in terms of the quality of the linear lower bound obtained by the relaxation of the integrity constraints of this model.
Abstract: This paper focuses on the two dimensional rectangular non-oriented guillotine cutting stock problem (TDRCSP) in which many pieces with different dimensions need to be cut with different quantities in order to satisfy customers' orders. In order to maximise the use of raw materials, make-to-order 'MTO' and make-to-stock 'MTS' production strategies are combined; in addition to the (firm) orders that need to be fulfilled, other quantities of pieces are considered when designing cutting patterns in order to satisfy the forecast plan over a fixed time horizon. A new formulation of the optimisation problem is proposed in this paper considering multi-period demand planning as well as inventory management constraints. To solve this new problem, a hybrid heuristic, based on the combination of the Bottom Left and Shelf algorithms, is considered. It is shown that formulating the problem combining the original non-oriented guillotine TDRCSP with demand and inventory planning optimises the raw material use and yields good solutions in very short computational times. Results show that integrating forecast and inventory constraints are much more of an additional way to improve the raw material use than a real constraint. Finally, a discussion on the hybrid heuristic sensitivity and robustness is reported.
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: In this paper, the authors present a hybrid genetic approach for the two-dimensional rectangular guillotine oriented cutting-stock problem. In this method, the genetic algorithm is used to select a set of cutting patterns while the linear programming model permits one to create the lengths to produce with each cutting pattern to fulfil the customer orders with minimal production cost. The effectiveness of the hybrid genetic approach has been evaluated through a set of instances which are both randomly generated and collected from the literature.
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: 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: 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) is an important application of group technology (GT) that can be used to enhance both flexibility and efficiency in todayâs 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 Kusiakâs solution.
Notes: Wafik Hachicha, Faouzi Masmoudi, Mohamed Haddar (2008) Taguchi Method application for the part routing se
Abstract: The aim of this paper is to illustrate a solution that can be used to reduce the severity of breakdowns and improve performances in the cellular manufacturing (CM) system with unreliable machines.
The performance of CM system is conditioned by disruptive events, such as the failure of machines, which randomly occurs and penalizes the performance of the cells, seriously disturbing the smooth working of the factory. To overcome the problem caused by the breakdowns, the authors develop a solution, based on the principle of virtual cell and the notion of intercellular transfer that can improve the availability of the system. In this context, the use an analytical method based on Markov chains to model the availability of the cell. The results are validated using simulation.
The proposed solution in this paper confirmed that it is possible to reduce the severity of breakdowns in the CM system and improve the availability of the cells through an intercellular transfer created at the time of a breakdown. Simulation allowed a validation of the analytical model and showed the contribution of the suggested solution.
The developed approach studies the performance of the production cells formed by unreliable machines. It uses the notion of the intercellular transfer to improve the availability of the cells.
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.
Notes: Masmoudi, F.; Bouaziz, Z.; Hachicha, W. (2007). Computer-aided cost estimation of weld
operations, International Journal of Advanced Manufacturing Technology, Vol. 33, 3-4, 298-307
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: In this work, we present a model of a three-dimensional manufacturing tolerancement by the
use of a tensorial approach. We are interested in the study of the influence of the fixture
errors of a workpiece on a machined surface. The orientation variation of a workpiece is
caused by the fixture errors. Consequently three-dimensional geometric defaults are
generated when the workpiece is machined. Using a tensorial approach, these defaults are
modelled by the positional variations of a set of surface points.
By a numerical simulation, we validate the developed model and show the influence of the
fixture errors on the geometric orientation specifications. We also show that the choice of the
fixture location can be verified by the 3D influence of the geometric fixture errors on the
generated defaults of machined surfaces.
Abstract: Cellular manufacturing is an application of a group technology used to improve the
performance of manufacturing systems. A number of factors, including vulnerability to
machine breakdown, under utilization of resources and eventual unbalanced workload
distribution in a multi-cell plan disturb the smooth working of the factory when using the
group technology concept.
This paper focuses on a manufacturing cell composed of unreliable machines. We are
interested in the problem of cell production availability facing unexpected circumstances due
to an internal perturbation caused by machine breakdown. We consider a policy of
intercellular transfer in the event of breakdown to improve the availability of the cells. We
examine through simulation the performance of the system and evaluate the intercellular
transfer policy in terms of some selected criteria. The results indicate, under the assumed
conditions, that the developed policy improves the performance of the production cells.
Abstract: This paper describes the development of a simulation study to
reduce the effect of failure in cellular manufacturing with the use of a
maintenance policy. It analyses the effects of corrective, preventive and
opportunistic maintenance policies on the performance of a manufacturing cell.
We consider the productivity of the cell as performance criteria, and we study
the cell performance under different times between failure distributions and
different operational conditions. A simulation model was established in Arena
simulation software. The results are compared to determine the best policy for a
given system.
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 simulation of the process planning is a decisive stage in the manufacturing process of a
set of parts. This simulation is generally carried out by the calculation of the working
dimensions (WD) according to the blueprint dimensions (BPD), to the means of production
and to the machining process. The calculation and the generating of the working dimensions
can be done by using different methods such as the transfer method, the dispersion method
and the tolerance chart method.
This article presents a system of automatic generating of the working dimensions (WD)
through the tolerance chart method. From the blueprint dimensions and from the process
planning proposed, the system allows the automatic generating of three graphs: the blueprint
dimensions graph, the blueprint dimensions and the stock removal graph, as well as the
working dimensions graph. After the drawing of the two last graphs, the dimensional chains
appear in the matrix from: Y=PX.
At last, the calculation of the tolerance intervals for each dimension is done from the
resolution of an equation system according to the minimum economic tolerances imposed by
the manufacturing process and to the weight assigned to the tolerances.
(Received in July 2005, accepted in October 2005. This paper was with the authors 1 month for 1 revision.)
Abstract: This article developed a new method of the manufacturing cell sizing according to an approach based on the simulation and expert system. This method takes into consideration the stochastic aspect which governs the production system, the production scales of the product family to be treated, the products arrival law, the adopted scheduling and the used optimization criteria.
This study starts with the modeling of a manufacturing cell and the simulation of its functioning using the software âARENAâ, which provides performance ratings. In a second stage, the expert system exploits these performance measures by a confrontation of the obtained results to the pre-defined objectives. This step permits to lead to a possible decision in order to size each of the machines to obtain a better manufacturing cell functioning. This process is repeated iteratively until the obtention of a cell having the performances which conform to the objectives already defined. The method represents a very useful and economical approach to predict the system size.
Finally, applications of the developed method for the sizing of manufacturing cell machines permitted to get satisfactory results.
Abstract: This article deals with simulation modelling of a flexible manufacturing cell. Our purpose is the optimization of a
robot cycle that transfers products in the cell. We consider the productivity as performance criterion. An analytical
survey is developed and validated by simulation results. These results permit to get an aided adequate decision and
a large reactivity facing the changes of products operated in a flexible manufacturing cell. A constraint of flow time of products on machines has been considered in the model, the results of the simulation allowed to eliminate invalid cycles with this constraint and to classify the remaining cycles according to their shortest cycle times.
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.
Notes: Wafik Hachicha, Faouzi Masmoudi, Mohamed Haddar (2008) Formation of machine groups and part families in cellular manufacturing systems using a correlation analysis approach International Journal Advanced Manufacturing Technology. DOI 10.1007/s00170-007-0928-9
Abstract: Consumer goods are mainly manufactured in multiple steps often done by separate, independent production nodes, related to each others to form manufacturing supply chains (MSC). Mostly, each member of a supply chain optimizes his own local objective and accordingly, plans his operations (e.g., production, inventory, capacity planning). The purpose of this work is to improve the efficiency of production networks as a whole by developing a multi-objective optimization model for cooperative planning which aims at minimizing simultaneously the total production cost and the average inventory levels in a multi-period, multi-item environment. To solve this problem, we adopt an elitist non-dominated Sorting Genetic Algorithm (NSGA-II) to find optimal solutions. Several tests are developed to show the performance of the model.
Abstract: This paper presents a Multi-Objective Genetic Algorithm (MOGA) for Assembly Line Resource Assignment and Balancing Problem of type2(ALRABP-2). This approach minimizes both the cycle time and cost per hour of the line for a fixed number of stations to satisfy precedence constrains between tasks and compatibility constrains between resources. A modified version of Weighted Pareto-based Multi-Objective Genetic Algorithm (WPMOGA) is used to solve this problem. The effectiveness of the genetic approach has been evaluated through a set of instances randomly generated.
Abstract: In this paper, the authors present a hybrid genetic approach for the two-dimensional rectangular guillotine oriented cutting-stock problem. In this method, the genetic algorithm is used to select a set of cutting patterns while the linear programming model permits one to create the lengths to produce with each cutting pattern to fulfill the customer orders with minimal production cost. The effectiveness of the hybrid genetic approach has been evaluated through a set of instances which are both randomly generated and collected from the literature.
Abstract: An important supply chain research problem is the bullwhip effect (BE), which its presence makes supply chain planning difficult. In fact, demand fluctuations increase as one move up the supply chain from retailer to manufacturer. In this paper, a single-stage supply chain for a single-item inventory system is considered. The aim is about how identify the critical parameters that affect BE phenomenon when the retailer employ a (s, S) policy. To investigate and measure this impact, a simulation model is developed using Arena 10 software. A simulation-optimization based-approach is adopted, which combines metamodel through the factorial design experiments and the desirability function approach. Our findings suggest that when we want to reduce the BE, this doesn't mean directly reduce costs. The BE must be introduced in the supply chain management such a constraint not such an objective function (BE must be lower to 1 to have not a bullwhip effect), and the effect of S is always more significant than the effect of s, and it is valid for all studied situations. Otherwise, in a (s, S) policy, the choice of S is more determinant that s, to reduce costs in the supply chains as well BE.
Abstract: In this paper, a combined simulation and Genetic Algorithm (GA) optimization model is developed to solve the Lot Sizing Problem (LSP) in a Make to Order (MTO) supply chain. The simulation model is performed using ARENA software. GA model is implemented using Visual Basic for Application (VBA) language, because it ensures exchanges between ARENA software and Ms Excel. The GA and simulation models operate in parallel over time with interactions. The case studyâs objective is to determine a fixed optimal lot size for each manufactured product type that will ensure order mean flow time target for each finished product. The comparative results with OptQuest software, which is used a global search method, illustrate the efficiency and effectiveness of the proposed approach.
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: 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
Notes: Lot-Sizing Problem; Make to Order; Discrete Event Simulation; desirability optimization
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.
Notes: Simulation Optimization, classification methods, literature survey
Abstract: This paper considers a two dimensional guillotine cutting stock problem as a bin packing problem. Many pieces with different dimensions have to be cut with different quantities in order to satisfy customers' orders. In addition to the firm orders, forecast plans are considered as new constraints to be taken into account. In this paper, a hybrid heuristic is developed, based on the combination of the bottom left and the shelf algorithms. Several experimental tests are reported to demonstrate the validity and the performance of the heuristic. In fact, the proposed heuristic reduces the waste rate for all the considered tests in very short computational time. Results show that integrating the forecast constraints is actually more an additional way to improve the trim loss than a real constraint.
Notes: Wafik Hachicha, Faouzi Masmoudi, Mohamed Haddar (2007) An improvement of a cellular manufacturing system design using simulation analysis International journal of simulation modeling 6: 4. 193-205 december
Abstract: Cellular manufacturing (CM) is an important application of group technology (GT) that can be used to enhance both flexibility and efficiency in todayâs 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 Kusiakâs 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: 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: 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
DOI 
