Papers by Keyword: Cell Formation

Abstract: A Combined Algorithm is proposed to form the machine cell and part family identification in the cellular manufacturing system. In the first phase, part families identification, by using Rank Order Clustering (ROC) and Modified Single Linkage Clustering (MOD-SLC). In second phase, Machine cell formation, by using Rank Order Clustering (ROC) and Modified Single Linkage Clustering (MOD-SLC), which is to assign machines into machine cells to produce part families. The above Proposed method is tested by using standard problems and compared with other method results for the same standard problems. Grouping efficiency is one of the most widely used measures of quality for Cellular Manufacturing Systems.

Abstract: Cellular manufacturing, one of the main tools of Lean Manufacturing, significantly improves material flow, which reduces the distance travelled by materials, inventory and cumulative lead times. In our study we focused on examination of the recent trends in cellular manufacturing research, and particularly the trends related to cell formation areas, objective criteria, performance measures, and development tools. The surveyed articles are organized by proposed classification scheme, and they are presented in synoptic graph diagrams. In the paper we also identify the best publication outlets for such research. Our survey on cell formation approaches identifies the major development features in cell manufacturing research area in leading journals between 2000 and 2011. Subsequently, the main findings are summarized and presented in the last part of the paper.

Abstract: A new algorithm is presented in order to search for the optimal solution of the manufacturing and fractional cell formation problem. In addition, this paper introduces a new toolkit, which is used to search for the various candidate solutions in a periodic and a waving (diversified) manner. The toolkit consists of 15 tools that play a major role in speeding up the obtainment of the final solution as well as in increasing its efficiency. The application of the binary digit grouping algorithm leads to the creation of manufacturing cells according to the concept of group technology. The nonzero entries, which remain outside the manufacturing cells, are called exceptional elements. When a lot of such elements is obtained, an additional cell called fractional (or remainder) cell may be formed; the aim of which is to reduce their number. This algorithm was tested by using illustrative examples taken from the literature and succeeded to give better or at least similar results when compared to those of other well-known algorithms.

Abstract: A decision support system based on scenario for multi-attribute selection of cell formation schemes is developed. The system combines fuzzy set theory and group decision with the AHP to decrease the influence of decision makers’ subjective preferences and control the uncertain and imprecise variations during evaluation process. The importance weights of different criteria and the ratings of various alternatives under different criteria are evaluated in linguistic terms represented by fuzzy numbers. The intangible criteria and criteria weights are determined by group decision which can integrate all decision makers’ subjective opinions based on different scenarios. Besides, fuzzy value of each of the alternatives is computed by making use of standard fuzzy arithmetic. The degree of confidence and risk index are also joined, so that decision makers can adjust them to match real context. Finally, a case of individual selection about cell formation is given, and the results demonstrate the proposed approach is both effective and robust.

Abstract: Cell formation（CF）and cellular layout design are the two main steps in designing a cellular manufacturing system (CMS). Efficient grouping is the prerequisite of a successful Cellular Manufacturing, and it is too hard to obtain a perfect consequence of CF and layout simultaneously. In this paper, a two-stage strategy is used to solve CF problem and layout sequentially. At the first stage, the cells are formed based on the part-machine clustering results obtained through the genetic algorithm, to get the initial inter-cell layout. At the second stage, the genetic algorithm is used to improve the solution obtained, to minimize the handling cost and maximize the utility of the machines.

Abstract: Cellular manufacturing (CM) is a production approach directed towards reducing costs, as well as increasing system's flexibility in today's small-to-medium lot production environment. Many structural and operational issues should be considered for a successful CM design and implementation; such as cell formation (CF), production planning, group layout (GL), resource allocation and scheduling. Most researchers have addressed these issues sequentially or independently, instead of jointly optimizing a combination of these issues. In order to attain better results to ensure that the system will be capable of remaining efficient in unknown future situations, these issues should be addressed simultaneously. In this paper possibility of developing a comprehensive mathematical model which considers these issues is discussed.

Abstract: Cell formation is one of the key issues in cellular manufacturing research. A two-stage cell formation method is proposed. With this approach, parts are first clustered into different groups based on similarity factor; then, machines are assigned to these part groups according to the principle of maximum machine utility. Examples show that the proposed method is feasible in grouping parts and machines into cells so that machine utilization and manufacturing systems efficiency are improved.

Abstract: Cell formation which involves grouping similar parts into part families and the corresponding machines into machine cells is one of the key research issues for designing cellular manufacturing system. Functionally identical machines may vary in production performance. In the paper, processing cost is employed to differentiate the performance of machines, and a two-stage cell formation approach for manufacturing systems with multiple functionally identical machines is proposed. With this approach, parts are firstly clustered into part groups based on process similarity; secondly, machines are then assigned to part groups according to their performance to form manufacturing cells. A heuristic algorithm based on process similarity is presented for part group identification, and a mathematical model with the objective of minimizing the total processing cost is established. An example is employed to illustrate the benefit of the proposed approach and the results suggest that the proposed approach is feasible.

Abstract: Cell formation, which involves grouping similar parts into part families and the corresponding machines into machine cells, is one of the key research issues for designing cellular manufacturing system. In this paper, a mathematical model which targets at maximizing the machine utilization and similarity of the part groups is built. A heuristic algorithm based on clustering analysis is proposed. An example is employed to illustrate the benefit of the approach and the results suggest that the proposed approach is feasible.