The cellular Manufacturing System (CMS) layout problems have not received adequate attention from researchers in comparison to cell formation in the past two decades . For this lack of information on layouts, the benefits of CMS can not be validated . A key element to exploit the benefits of CM is efficient layout designs. A poor physical layout will offset some or all expected benefits. The right solution to plant layout problems is important because material handling costs have been estimated to range from 20% to 50% of the total manufacturing operating expenses. An efficient facility layout can reduce these costs by at least 10% to 30% .
Developing a group of machine cells and their corresponding part families to minimize the inter-cell and intra-cell material flow is the basic objective of the designing of a cellular manufacturing system (CMS). Afterwards achieving a competent celllayout is essential in order to minimize the total inter-cell part travels, which is principally noteworthy .
Today’s industrial world witnesses an increasing global competition, where old technologies failed to overcome the new form of change in demand. The application of group technology to production systems has in industries led to the introduction of cellular manufacturing (CM) which tries to take advantage of the similarity between parts. Each CMS design is consisted of four important decisions; namely cell formation (CF), group layout (GL), group scheduling (GS) and resource allocation , in which most of studies have developed CF problems [2, 3]. Only a few studies have concentrated on integrating two or more CMS decisions. Kia et al.  proposed an integration of CF and GL models considering the multi-rows layout utilization to locate machines in the cells configured with flexible shapes and several design features (e.g., alternative process routings, operation sequence, processing time, production volume of parts, purchasing machine, duplicate machines, machine capacity, lot splitting, intra-celllayout, inter-celllayout, multi-rows layout of equal area facilities and flexible reconfiguration). Jolai et al.  considered the integration of CL and GL models and proposed an
solve the inter and intra-celllayout problems by considering single time period and stochastic demands. Tavakkoli-Moghaddam et al.  proposed a novel QAP-bases formulation to simultaneous plan of the optimum intra and inter-cell facility layouts for the SSFLP. Palekar et al.  designed the SDFLP using quadratic integer programming model. Finally, they used dynamic programming (DP) and approximate solution methods to solve the problem in small and large sizes, respectively. Montreuil and Laforge  addressed the SDFLP by a scenario tree of probable futures. Krishnan et al.  proposed three mathematical models for designing a facility layout in an uncertain environment by considering multiple product demand scenarios. Moslemipour and Lee  designed an optimal machine layout for each period of the SDFLP by considering independent uncertain product demands with normal. Lee and Moslemipour  developed a novel mathematical formulation for planning a facility layout with the highest stability for the total time scheduling prospect of the uncertain DFLP by utilizing the QAP model. This layout has the maximal capability to exhibit a little sensitivity to product demand changes. Lee et al.  proposed a novel hybrid AC/SA approach using ant colony and SA having outstanding performance to solve the SDFLP.
Proposing new mathematical programming models in which the practical aspects of a cellular environment are taken into account should be a useful research especially for those who want to design an efficient manufacturing system. There are many researches in literature in which the uncertainty of the manufacturing system like stochastic nature of part demand and production mix has been regarded. However, almost the parts arriving rate in a CMS environment is not considered as a major factor which has a significant impact on machine busy time. In this paper machine utilization factor is investigatedin presence of uncertainty in parts arrival rate and mean number of parts processed by machines. Ghezavati & Saidi-Mehrabad (2011)proposed an efficient hybrid self-learning method to solve the CFP. This paper is extension of their work by incorporating some other real world production elements like machine busy time and dynamic alternative process routings associated with the inter-celllayout determination. In a queue system, the customers (parts) have a stochastic arriving rate and wait in a queue to be served by an available server (machine). Two kinds of arriving patterns can be considered: Number of arrivals in a time interval follows a probability distribution or this value is determined by the mean number of parts processed by a machine based on its processing time. Figure1 illustrates the concept of a queue system in the CMS environment. Three different concepts are defined during this research: first is the Machine Utilization Factor (MUF) which can be calculated for a specific part by this part mean number of arrivals divided by the mean number of total parts which should be processed on the corresponded machine. The second is the Total Machine Utilization Factor (TMUF) which is the sum of MUF for all parts processed by this machine. The third concept implemented in this paper is the Efficiency Factor (EF) which is the sum of TMUF value for all machines. The TMUF must be less than 1 so that the queue system will remain in a stable mode. Hence the number of arrivals should be less than the number of processed parts on the specific machine. The alternative process routing controls this rational theory. In this paper a new mathematical model has been developed in order to design an efficient CMS in which the maximum EF is obtained through the optimal selection of the alternative process routings. The main objectives of proposed mathematical model are to minimize the intra cell art trips, system reconfiguration cost and also maximization of the system EF value.
In this paper, by improving and combining the studies of Lee and Chiang (2001), Chiang and Lee (2004) and Solimanpur et al. (2004), we propose an integrative and easy to code approach which integrates all three phases of a CMS design: cell formation, its location sequence on the bi- directional linear flow layout and the intra-cell machine layouts. Indeed, the work of Solimanpur et al. (2004) develops a strong Ant Colony Optimization technique for the inter-celllayout problem without considering other phases of a CMS design, i.e., cell formation and intra-celllayout problems. We modify their approach to be able to implement it for our intra-cell (and not inter-cell) layout decision making as a part of our integrated approach. Moreover, the paper by Chiang and Lee (2004) only considers the joint problem of manufacturing cell formation and its layout assignment. The objective of that study is to minimize the inter-cell flow cost under the cell size constraint. They, however, do not consider the effect of incorporating intra-cell decisions (within inter-cell and cell formation ones) on a more important criterion, i.e., the total material flow cost. In this paper, we consider this criterion as the objective function. Moreover, we notice that all these design decisions are correlated in the sense that they affect each other. Hence, we propose an integrative and simultaneous consideration of different design decisions instead of available sequential approaches. Our computational results, as will be discussed, show that by incorporating intra-cell decisions in cell formation and inter-cell design process, and through implementing our proposed integrated approach, a manufacturer can largely reduce her total material flow cost.
When writing Java applications, you may need to use layouts to give your windows a specific look. A layout controls the position and size of children in a container. Layout classes are subclasses of the abstract class Layout. Both SWT and Swing provide several standard layout classes, and you can write custom layout classes. Other UI toolkits embed implicit layout managers in each panel type.
Research into nanoscale electronics has increased significantly over the last decade. VLSI technology is going to approach a scaling limit in deep nanometer regime. International Technology Road- map for Semiconductors (ITRS)  reports several possible technology solutions to replace the current CMOS technology. Quantum-dot cellular automata (QCA) may overcome some of the limitations of current technologies, because it not only gives a solution at the nanoscale, but also it offers new methods of computation and information transformation [2-6]. In conventional logic circuits information is transferred by electrical current, but QCA operates using the Columbic interaction that connects the state of one QCA cell to the state of its neighbors. High density, fast switching speed, and low power dissipation are the advantages of QCA circuits over the current CMOS technology. QCA sequential circuits
Nowadays it is important for an organization or any company to have an effective and efficient manufacturing facility layout. While in industry sectors, it is important to manufacture the products that have good quality and meet customer’s demand to ensure the continuity of the company over time. The processes could be conducted under existing resources such as machines, employees and other facilities. In order to make and distribute things that can be sold, all decision variables are set at a level in which, for both maximum production control and efficiency, goods are to be standardized and produced away from the market and then be held in inventory until demanded and then delivered to the consumer with profit (Vargo and Lusch, 2004).
Enables edit segment mode, which you use to select existing tracks and change their positions, while Layout automatically adjusts the angles and sizes of adjacent segments to maintain connectivity. Equivalent to selecting the Edit Segment Mode option in the Route Settings dialog box.
ABSTRACT: In this paper, ongoing engine reconditioning process layout of an automobile industry are studied and a new layout is developed based on the systematic layout planning pattern theory to reduce engine reconditioning cost and increase productivity Since it is an automobile assembly plant, the company has both processes as well as product layouts. The number of equipment and travelling area of material in engine reconditioning have been analyzed. The detailed study of the plant layout such as operation process chart, activity relationship chart and the relationship between equipment and area has been investigated. The new plant layout has been designed and compared with existing plant layout. The new plant layout shows that the distance and overall cost of material flow from stores to dispatch area are significantly decreased. The implementation of proposed model will help in the overall improvement of production performance of the engine reconditioning unit of the corporation.
Abstract— In this research, cellular manufacturing layout design based on Systematic Layout Planning (SLP) and selection of facilities layout design by Analytic Hierarchy Process (AHP) are applied to a case study of an Electronic Manufacturing Service (EMS) plant. Currently layout of this manufacturing plant is a process layout, which is not suitable due to the nature of an EMS that has high-volume and high- variety environment. Moreover, quick response and high flexibility are also needed. Then, cellular manufacturing layout design was determined for the selected group of products. SLP was used to analyzed and designed possible cellular layouts for the factory. In order to evaluate the best alternative layout, criteria for plant selection were determined. These performance measures were weighted by AHP. Then, the best cellular layout design was selected. This case study has shown the practical guideline for design and selection of the best EMS layout.
The objective of this thesis is to improve the production floor layout of the MTA department and to evaluate the proposed alternative layouts using ARENA simulation. This project is conducted at Agilent Technologies, Inc., an Electronics Manufacturing company located in Bayan Lepas, Penang. The major problem faced by the company is high cross-over frequency for E-Cal and Coaxial Waveguide Adapter products between two buildings. There is high flow intensity between departments which have high interrelationship. This leads to high travelling time and high travelling cost. Two alternative layouts are proposed using the 11 steps in Systematic Layout Planning, which is a systematic way of generating layout alternatives. The proposed alternative layout involves transferring the departments which have high interrelationship close to each other. The proposed alternative layouts are evaluated using ARENA simulation student version. The best alternative is chosen based on the performance measures which have the most significant improvement, which are total travel distance, total travel time, total travel cost, number of cross-over, output, average resource utilization, total average WIP level, total average waiting time and total time spent in the system. The best alternative layout is Layout Design 2, which does not need extra space for re-layout. Total travel distance for Coaxial Waveguide Adapter will reduce significantly by 78.1% and for E-Cal the total travel distance will reduce by 62.87%. Total travel time for coaxial waveguide adapter is reduced by 86.42 % while for e-cal is reduced by 75.17%. This will subsequently reduce cost of travel for coaxial waveguide adapter by 86.42% and for E-cal is reduce by 68.09%. The output for coaxial waveguide adapter will
AYOUT planning is defined as the work or the plan for the installation of machine, tools, devices or other objects required for the production process under the conditions of the structure and the existing building so that the production becomes safe and highly efficient. The layout planning must be conducted with care in order to meet the requirements for the production demands and the production process. Planning and controlling the productivity is usually aimed at maximizing the use of limited resources and at satisfying the customers. The resources in this context can be defined as all facilities for production such as machine, equipment, labor and raw materials for the production. To maximize the usefulness of the limited resources, the factory managers must be responsible for this and they could work with the department of planning and controlling the productivity to predict, plan, outline, analyze, control the
In order to achieve an economical profitable manufacturing process, most patterns are fitted with the maximum amount of cavities (In present condition it is 2 castings in a single shell mold). In many cases a non-symmetrical layout is the result, especially in relation to orientation of component in mold cavity as well as location of gating junction. Because of lack of permeability and common riser for both cavities and also due to different flow patterns gating system, the whole filling process of both cavities is inherently uneven. The gas is not able to come out of mold cavity and it forms a blow hole , shrinkage cavity and micro holes over inside and outside of casting. As shown in Fig.1 and 6 casting shows a blow hole and internal shrinkage cavity and micro pin holes defects. The casting yield is of 54 % with previous condition of gating system as shown in fig.5 which is required to be optimized.
For auxiliary facilities in warehousing arrangement, under normal circumstances, we follow the process from starting, such as a business process after the storage of goods to be timely scan goods scanned are placed into the storage area for storage, storage after the classification of goods to be placed into their respective positions, waiting for demand comes after the timely collection of goods ready to ship cargo scanning. Under this process, the area of design aids in the process tend to be close to the department or footprint together to facilitate the management and shipping and receiving. For these regions, companies must be in the process of designing the warehouse, the shipping and receiving area, storage area, working out of such advance planning, so there is a macro to control, according to pre-planned area, the transceiver cargo area reasonable set according to the shape of warehousing. After the whole enterprise should be classified storage area, divided into equal units of the cell, and the cell area is clear how much, according to a work area required number of cells can be designed to meet their place.