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دسترسی آزاد مقاله
1 - An integrated model of cellular manufacturing and supplier selection considering product quality
Habib Heydari Mohammad Mahdi Paydar Iraj MahdaviToday’s business environment has forced manufacturers and plants to produce high-quality products at low cost and the shortest possible delivery time. To cope with this challenge, manufacturing organizations need to optimize the manufacturing and other functions t چکیده کاملToday’s business environment has forced manufacturers and plants to produce high-quality products at low cost and the shortest possible delivery time. To cope with this challenge, manufacturing organizations need to optimize the manufacturing and other functions that are in logical association with each other. Therefore, manufacturing system design and supplier selection process are linked together as two major and interrelated decisions involved in viability of production firm. As a matter of fact, production and purchasing functions interact in the form of an organization’s overall operation and jointly determine corporate success. In this research, we tried to show the relationship between designing cellular manufacturing system (CMS) and supplier selection process by providing product quality considerations as well as the imprecise nature of some input parameters including parts demands and defects rates. A unified fuzzy mixed integer linear programming model is developed to make the interrelated cell formation and supplier selection decisions simultaneously and to obtain the advantages of this integrated approach with product quality and consequently reduction of total cost. Computational results also display the efficiency of proposed mathematical model for simultaneous consideration of cellular manufacturing design and supplier selection as compared to when these two decisions separately taken into account. پرونده مقاله -
دسترسی آزاد مقاله
2 - Cell forming and cell balancing of virtual cellular manufacturing systems with alternative processing routes using genetic algorithm
Adib Hosseini Mohammad Mahdi Paydar Iraj Mahdavi Javid JouzdaniCellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems and as a recently emerged field of study and practice, virtual cellular manufacturing (VCM) inherits the importance from CM. One type of VCM problems is VCM with al چکیده کاملCellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems and as a recently emerged field of study and practice, virtual cellular manufacturing (VCM) inherits the importance from CM. One type of VCM problems is VCM with alternative processing routes from which the route for processing each part should be selected. In this research, a bi-objective mathematical programming model is designed in order to obtain optimal routing of parts, the layout of machines and the assignment of cells to locations and to minimize the production costs and to balance the cell loads. The proposed mathematical model is solved by multi-choice goal programming (MCGP). Since CM models are NP-Hard, a genetic algorithm (GA) is utilized to solve the model for large-sized problem instances and the results obtained from both methods are compared. Finally, a conclusion is made and some visions for future works are offered.Cellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems and as a recently emerged field of study and practice, virtual cellular manufacturing (VCM) inherits the importance from CM. One type of VCM problems is VCM with alternative processing routes from which the route for processing each part should be selected. In this research, a bi-objective mathematical programming model is designed in order to obtain optimal routing of parts, the layout of machines and the assignment of cells to locations and to minimize the production costs and to balance the cell loads. The proposed mathematical model is solved by multi-choice goal programming (MCGP). Since CM models are NP-Hard, a genetic algorithm (GA) is utilized to solve the model for large-sized problem instances and the results obtained from both methods are compared. Finally, a conclusion is made and some visions for future works are offered. پرونده مقاله -
دسترسی آزاد مقاله
3 - A simulated annealing algorithm to determine a group layout and production plan in a dynamic cellular manufacturing system
Reza KiA Nikbakhsh Javadian Reza Tavakkoli-MoghaddamIn this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensiv چکیده کاملIn this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. There are also some features that make the presented model different from the previous studies. These include: 1) the variable number of cells, 2) machine depot keeping idle machines, and 3) integration of cell formation (CF), GL and PP decisions in a dynamic environment. The objective is to minimize the total costs (i.e., costs of intra-cell and inter-cell material handling, machine relocation, machine purchase, machine overhead, machine processing, forming cells, outsourcing and inventory holding). Two numerical examples are solved by the GAMS software to illustrate the results obtained by the incorporated features. Since the problem is NP-hard, an efficient simulated annealing (SA) algorithm is developed to solve the presented model. It is then tested using several test problems with different sizes and settings to verify the computational efficiency of the developed algorithm in compare to the GAMS software. The obtained results show that the quality of the solutions obtained by SA is entirely satisfactory in compare to GAMS software based on the objective value and computational time, especially for large-sized problems. پرونده مقاله -
دسترسی آزاد مقاله
4 - Developing a Multi-objective Mathematical Model for Dynamic Cellular Manufacturing Systems
Mohammad Saidi-Mehrabad Seyedeh Maryam Mirnezami-ziabariThis paper is in search of designing the cellular manufacturing systems (CMSs) under dynamic and flexible environment. CM is proper for small-to-medium lot production environment that helps the companies to produce variable kind of productions with at least scraps. The چکیده کاملThis paper is in search of designing the cellular manufacturing systems (CMSs) under dynamic and flexible environment. CM is proper for small-to-medium lot production environment that helps the companies to produce variable kind of productions with at least scraps. The most important benefits of CM are decline in material handling, reduction in work-in-process, reduction in set-up time, increment in flexibility, improved quality, and shorter lead time. In this research A multi-objective mixed integer model is presented that considers some real-world critical conditions same as costs of multi-period cell formation and production planning , human resource assignment to cells and balancing workload of cells. This model groups the parts and machines concurrently with labor assignment This study aims to 1) minimize various costs including reassignment cost of human resource, the batch inter-cell material handling cost, constant and variable cost of machines, relocation and purchase cost of machines, 2) minimize cell load variation and 3) maximize utilization rate of human resource. The model is complicate, so it is verified with Lingo 8. 0. Soft ware. Since particle swarm optimization approach less than many other metaheuristic approaches have been applied to solve multi-objective CMS problems so far, we utilize this method to solve our model. The results are presented at the last part. پرونده مقاله -
دسترسی آزاد مقاله
5 - Study and Implementation of Lean Manufacturing in a Garment Manufacturing Company: Bangladesh Perspective
Ripon Kumar Chakrabortty Sanjoy Kumar PaulLean manufacturing is a systematic approach to identifying and eliminating wastes (non-value added activities) through continuous improvement by conveying the product at the pull of the customer in pursuit of production. In a more basic term, more value with less work. چکیده کاملLean manufacturing is a systematic approach to identifying and eliminating wastes (non-value added activities) through continuous improvement by conveying the product at the pull of the customer in pursuit of production. In a more basic term, more value with less work. Since lean manufacturing eliminates many of the problems associated with poor production scheduling and line balancing, lean manufacturing is particularly appropriate for companies that do not have ERP systems in place or do not have strong material requirements planning (MRP), production scheduling, or production allocation systems in place. This is particularly significant in Bangladesh, where many private Bangladeshi garment manufacturing companies are operating significantly below their potential capacity, or experiencing a high level of late-deliveries, due to problems with their current production scheduling and production management systems. Considering all those facts this paper provides a roadmap as well as a framework to those manufacturing companies who are really operating significantly below their potential capacity. In this work, the existing layouts were studied and then layouts are proposed to enhance the production system and value stream mapping (VSM) is used as a basic lean manufacturing tool and some cellular manufacturing philosophies to find out the improved level of performance and productivity particularly in the garments section of Bangladesh. At the final stage, research work is reinforced by using a simulation software ARENA to judge the sustainability of proposal. پرونده مقاله -
دسترسی آزاد مقاله
6 - A Benders� Decomposition Approach for Dynamic Cellular Manufacturing System in the Presence of Unreliable Machines
Masoud Bagheri Saeed Sadeghi Mohammad Saidi-MehrabadIn order to implement the cellular manufacturing system in practice, some essential factors should be taken into account. In this paper, a new mathematical model for cellular manufacturing system considering different production factors including alternative process rou چکیده کاملIn order to implement the cellular manufacturing system in practice, some essential factors should be taken into account. In this paper, a new mathematical model for cellular manufacturing system considering different production factors including alternative process routings and machine reliability with stochastic arrival and service times in a dynamic environment is proposed. Also because of the complexity of the given problem, a Benders’ decomposition approach is applied to solve the problem efficiently. In order to verify the performance of proposed approach, some numerical examples are generated randomly in hypothetical limits and solved by the proposed solution approach. The comparison of the implemented solution algorithm with the conventional mixed integer linear and mixed integer non linear models verifies the efficiency of Benders’ decomposition approach especially in terms of computational time. پرونده مقاله -
دسترسی آزاد مقاله
7 - Layout of Cellular Manufacturing System in Dynamic Condition
amir hossein kamali dolatabadi seyed hamid reza pasandideh mehrzad abdi khalifeCellular manufacturing system (CMS) is highly important in modern manufacturing methods. Given the ever increasing market competition in terms of time and cost of manufacturing, we need models to decrease the cost and time of manufacturing. In this study, CMS is conside چکیده کاملCellular manufacturing system (CMS) is highly important in modern manufacturing methods. Given the ever increasing market competition in terms of time and cost of manufacturing, we need models to decrease the cost and time of manufacturing. In this study, CMS is considered in condition of dynamic demand in each period. The model is developed for facing dynamic demand that increases the cost of material flow. This model generates the cells and location facilities at the same time and it can move the machine(s) from one cell to another cell and can generate the new cells for each period. Cell formation is NP-Complete and when this problem is considered in dynamic condition, surly, it is strongly NP- Complete. In this study, genetic algorithm (GA) is used as a meta-heuristic algorithm for solving problems and evaluating the proposed algorithm, Branch and Bound (B & B) is used as a deterministic method for solving problems. Ultimately, the time and final solution of both algorithms are compared. پرونده مقاله -
دسترسی آزاد مقاله
8 - Scheduling Problem of Virtual Cellular Manufacturing Systems (VCMS); Using Simulated Annealing and Genetic Algorithm based Heuristics
Saeed Taouji Hassanpour Reza Bashirzadeh Abolfazl Adressi Behnam BahmankhahIn this paper, we present a simulated annealing (SA) and a genetic algorithm (GA) based on heuristics for scheduling problem of jobs in virtual cellular manufacturing systems. A virtual manufacturing cell (VMC) is a group of resources that is dedicated to the manufactur چکیده کاملIn this paper, we present a simulated annealing (SA) and a genetic algorithm (GA) based on heuristics for scheduling problem of jobs in virtual cellular manufacturing systems. A virtual manufacturing cell (VMC) is a group of resources that is dedicated to the manufacturing of a part family. Although this grouping is not reflected in the physical structure of the manufacturing system, but machines are spread on the shop floor physically. In this paper, there are multiple jobs with different manufacturing processing routes. First, we develop the mathematical model for the problem, and then we present the suggested algorithms. The scheduling objective is weighed tardiness and total travelling distance minimization. The problem is divided into two branches: small scale and large scale. For small scale, the results of GA and SA are compared to GAMS. For large scale problems, due to the time limitation of 3600 seconds, the results of GA and SA are compared to each other. Computational results show that both SA ad GA algorithms perform properly but SA is likely to turn out well in finding better solutions in shorter times especially in large scale problems. پرونده مقاله -
دسترسی آزاد مقاله
9 - A Comparison of Job-Shop and Group Technology Using Simulation by ARENA
Siyavash Khaledan Hadi ShirouyehzadProduction planning is performed through diverse methods according to the type of the system it is structured upon. One of the most important steps before production planning is to determine which system best fits the firm, and how the facilities should be designed. Bot چکیده کاملProduction planning is performed through diverse methods according to the type of the system it is structured upon. One of the most important steps before production planning is to determine which system best fits the firm, and how the facilities should be designed. Both job-shop and group-technology systems have their own pros and cons, each of which is suitable to a specific kind of factory. On the other hand, performance measurement is also important in terms of both productivity and queue factors. A good method to measure the performance is computer simulation by soft wares such as ARENA. This paper utilizes the software for separately simulating both the job-shop and group-technology systems for specific firm, and then compares the results. The results show that the group-technology system is better than the job-shop system in both productivity and queue factors, and it is highly recommended that the system should be changed. پرونده مقاله -
دسترسی آزاد مقاله
10 - Development of a cell formation heuristic by considering realistic data using principal component analysis and Taguchi’s method
Shailendra Kumar Rajiv Kumar SharmaOver the last four decades of research, numerous cell formation algorithms have been developed and tested, still this research remains of interest to this day. Appropriate manufacturing cells formation is the first step in designing a cellular manufacturing system. چکیده کاملOver the last four decades of research, numerous cell formation algorithms have been developed and tested, still this research remains of interest to this day. Appropriate manufacturing cells formation is the first step in designing a cellular manufacturing system. In cellular manufacturing, consideration to manufacturing flexibility and productionrelated data is vital for cell formation. The consideration to this realistic data makes cell formation problemvery complex and tedious. It leads to the invention and implementation of highly advanced and complex cell formation methods. In this paper an effort has been made to develop a simple and easy to understand/implement manufacturing cell formation heuristic procedure with considerations to the number of production and manufacturing flexibility-related parameters. The heuristic minimizes inter-cellular movement cost/time. Further, the proposed heuristic is modified for the application of principal component analysis and Taguchi’s method. Numerical example is explained to illustrate the approach. A refinement in the results is observed with adoption of principal component analysis and Taguchi’s method. پرونده مقاله -
دسترسی آزاد مقاله
11 - An archived multi-objective simulated annealing for a dynamic cellular manufacturing system
Hossein Shirazi Reza Kia Nikbakhsh Javadian Reza Tavakkoli-MoghaddamTo design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelate چکیده کاملTo design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelated decisions involved in the design of a CMS. This paper provides an extensive coverage of important manufacturing features used in the design of CMSs and enhances the flexibility of an existing model in handling the fluctuations of part demands more economically by adding machine depot and PP decisions. Two conflicting objectives to be minimized are the total costs and the imbalance of workload among cells. As the considered objectives in this model are in conflict with each other, an archived multi-objective simulated annealing (AMOSA) algorithm is designed to find Pareto-optimal solutions. Matrix-based solution representation, a heuristic procedure generating an initial and feasible solution and efficient mutation operators are the advantages of the designed AMOSA. To demonstrate the efficiency of the proposed algorithm, the performance of AMOSA is compared with an exact algorithm (i.e., [-constraint method) solved by the GAMS software and a well-known evolutionary algorithm, namely NSGAII for some randomly generated problems based on some comparison metrics. The obtained results show that the designed AMOSA can obtain satisfactory solutions for the multi-objective model. پرونده مقاله -
دسترسی آزاد مقاله
12 - A multi-objective model for designing a group layout of a dynamic cellular manufacturing system
Reza Kia Hossein Shirazi Nikbakhsh Javadian Reza Tavakkoli-MoghaddamThis paper presents a multi-objective mixed-integer nonlinear programming model to design a group layout of a cellular manufacturing system in a dynamic environment, in which the number of cells to be formed is variable. Cell formation (CF) and group layout (GL) are c چکیده کاملThis paper presents a multi-objective mixed-integer nonlinear programming model to design a group layout of a cellular manufacturing system in a dynamic environment, in which the number of cells to be formed is variable. Cell formation (CF) and group layout (GL) are concurrently made in a dynamic environment by the integrated model, which incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. Additionally, there are some features that make the presented model different from the previous studies. These features include the following: (1) the variable number of cells, (2) the integrated CF and GL decisions in a dynamic environment by a multi-objective mathematical model, and (3) two conflicting objectives that minimize the total costs (i.e., costs of intra and inter-cell material handling, machine relocation, purchasing new machines, machine overhead, machine processing, and forming cells) and minimize the imbalance of workload among cells. Furthermore, the presented model considers some limitations, such as machine capability, machine capacity, part demands satisfaction, cell size, material flow conservation, and location assignment. Four numerical examples are solved by the GAMS software to illustrate the promising results obtained by the incorporated features. پرونده مقاله -
دسترسی آزاد مقاله
13 - Stochastic extension of cellular manufacturing systems: a queuing-based analysis
Fatemeh Fardis Afagh Zandi Vahidreza GhezavatiClustering parts and machines into part families and machine cells is a major decision in the design of cellular manufacturing systems which is defined as cell formation. This paper presents a non-linear mixed integer programming model to design cellular manufacturing چکیده کاملClustering parts and machines into part families and machine cells is a major decision in the design of cellular manufacturing systems which is defined as cell formation. This paper presents a non-linear mixed integer programming model to design cellular manufacturing systems which assumes that the arrival rate of parts into cells and machine service rate are stochastic parameters and described by exponential distribution. Uncertain situations may create a queue behind each machine; therefore, we will consider the average waiting time of parts behind each machine in order to have an efficient system. The objective function will minimize summation of idleness cost of machines, sub-contracting cost for exceptional parts, non-utilizing machine cost, and holding cost of parts in the cells. Finally, the linearized model will be solved by the Cplex solver of GAMS, and sensitivity analysis will be performed to illustrate the effectiveness of the parameters. پرونده مقاله -
دسترسی آزاد مقاله
14 - Dynamic cellular manufacturing system considering machine failure and workload balance
Masoud Rabbani Hamed Farrokhi-Asl Mohammad RavanbakhshMachines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine چکیده کاملMachines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators’ assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics. پرونده مقاله
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