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Then, in the second stage the layout is analyzed as a control factor of the experiment, and it is verified for which response variables the layout is significant. In order to facilitate the understanding of the results, a summary is presented in Table 8 , which shows the relationship between each control factor and the response variables for each of the three layouts. In both cases the level of significance was 0. For the final time response variable h , the job shop and virtual cell layouts had very similar behavior.

They differ from the traditional cell layout in the demand type factor, where the job shop and the virtual cell have a slight increase in the final time when the type of demand is controlled. However, the average value of the total time for the traditional cell layout was h, while the average value of the total time for the virtual cell layout was 4, h, a significant difference.

However, the average value of throughput found for the virtual cell layout was better than the traditional cell layout. This is due to the complexity of batches of parts, showing that the virtual cell layout presents greater flexibility. The variable average work in process parts presents as key control factor among the three layouts the type of demand, once again evidencing that the formation of the cells dedicated to the type of demand is important.

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However, the average value of the work in process for the virtual cell layout was smaller than the traditional cell layout. It is noticed that despite the large variation in the demand type, the behavior of the virtual cell layout was more flexible. The virtual cell layout had a slight gain in the factor arrival time between batches.

That is, the job shop layout had a smaller variation when the level of this factor increased. As for the factor type of demand, the virtual cell layout proved to be better than the job shop and the traditional cell layout. That is, it was more efficient when the level of this factor was changed, showing that the virtual cell layout really can present the virtues of the other two layouts.

It should be noticed the increase in resource utilization when the systems were managed with a maintenance plan, which left the machines always available.


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This shows that maintenance is a very important factor for production systems. The response variable total waiting time hours also had different results for the three layouts. The virtual cell layout had an average value of waiting time lower than the other two layouts. Finally, for the variable lead time, which corresponds to the total time for moving from the entry of the raw material to the finished product, it presented very similar results for the three models.

The virtual cell layout underwent fewer variations when the levels of each factor were changed. This shows that this type of layout has greater robustness when variations in some factors take place.

An improvement of a cellular manufacturing system design using simulation analysis

In this second stage of results analysis the type of layout was included as a control factor with three levels: job shop, traditional cell, and virtual cell. It was verified how the response variables behaved in relation to the type of layout. Regarding the final time, Figure 7 shows that the traditional cell layout had a significant increase in relation to the job shop and virtual cell layouts.

The cells highlighted in Table 10 shows the three factors in which the confidence intervals do not intersect between the virtual cell and the traditional cellular layouts. Figure 8 associates throughput with the layouts, showing a better performance by the job shop and virtual cell layouts when compared with the traditional cell layout. Figure 9 shows how the layouts behaved in relation to the average work in process.

In this response variable, the job shop and virtual cell layouts again present better performance, and the virtual cell layout was still better than the job shop. This shows that the virtual cell layout can be located between job shop and traditional cell layouts, having advantages of both. Figure 10 illustrates the behavior of the type of layout with respect to the response variable referred to as average resource utilization.

Once again, the job shop and virtual cell layouts outperformed the traditional cell layout. Figures 11 and 12 show the behavior of the layouts with respect to the waiting total time and lead time variables, respectively. It is noticed a very similar behavior for both cases, where again the virtual cell and job shop layouts performed better.

In summary, Table 11 presents the performance of each layout for the response variables, always having the virtual cellular layout as the reference of the comparison. The minus sign indicates a worse result when compared to the virtual cell, and the plus signal indicates a better result compared to the virtual cell. The aim of this research was to compare the virtual cell layout with other types of layout.

It has a performance similar to the job shop layout, but it is better than the traditional cell layout. In addition, a greater number of control factors and response variables were considered compared with previous studies such as Mello and Reaes This greater amount of response variables provided a broader analysis of the three layouts. In general, such different results found in the case of the traditional cell layout can be understood by the wide variety of parts. All parts in each batch were generated from 40 pre-established features, and Excel's random function resulted in high batch variability, leading to a poor performance of the traditional cell layout.

A significant factor for the poorer performance of the traditional cell layout was the parts supplier. By leaving the supplier working exclusively in the cell, there was an imbalance of this operation, that is, while in a cell the supplier worked uninterruptedly, while the supplier became idle in the cell for cylindrical parts.

This behavior influenced the processing times, and reduced throughput and resource utilization. Another issue to be considered is the continuous flow, which, in the case considered in this paper, did not take place as in the traditional cell layout, since the production was based on batches of parts and not one piece flow. The setup times were the same for all three layouts, and the only difference occurred in entry of the batch in the cells, when the time was ten times shorter for the traditional cell layout when compared to the virtual cell and job shop layouts.

The objective of showing a knowledge gap with respect to virtual cells signals the importance of this topic, and the possibilities that have not yet been investigated about it in manufacturing companies. As a suggestion of future work, the amount of levels of some factors can be increased, which would improve the focus on the influence of certain factors on the response variables. Another suggestion would be the exclusion of one or more factors, seeking to focus on factors that can be directly controlled in the manufacturing system without depending on the interference of the customers.

For example, factors such as features per part are customer requirements, and can hardly be influenced by the system. With regard the papers limitations: the use of a process plan with alternatives, it is suggested to include an additional level for this factor, or two different penalties, in order to investigate the gains that are pointed out in the literature. It is suggested to address the issue of operator flexibility, which was implemented in a simplified way in this research. A study should be carried out relating the results found in this paper with the equipment costs, which may originate from obsolescence, maintenance, upgrade and replacement.

How to cite this article: Decker Junior, C. Assessment of shop floor layouts in the context of process plans with alternatives. Production, 29, e Agarwal, A. Evaluating functional and cellular manufacturing systems: a model and case analysis. International Journal of Manufacturing Technology and Management , 3 6 , Al-Aomar, R. A GA-based parameter design for single machine turning process with high-volume production. Alhourani, F. Cellular manufacturing system design considering machines reliability and parts alternative process routings. International Journal of Production Research , 54 3 , Andersen, A.

Towards a generic design method for reconfigurable manufacturing systems. Journal of Manufacturing Systems , 42 , Andrade, J. Barriers and challenges to improve interfunctional integration between Product Development and Production Planning and Control in Engineering-to-Order Environment. Arkat, J. Scheduling of virtual manufacturing cells with outsourcing allowed. International Journal of Computer Integrated Manufacturing , 27 12 , Assad, A. Comparing functional and cellular layouts: A simulation study based on standardization.

International Journal of Production Research , 41 8 , Bazargan-Cart, M. Cheng Ying, N. Pratical Production layout design for multi-product and small-lot-size production: A case study. Journal Teknologi , 78 7 , Chin, S. Virtual Cells: Evalution of different lot sizing splitting strategies. International Journal of Manufacturing Research , 8 1 , Colosimo, B. Rule based system for non linear process plan generation.

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Studies in Informatics and Control , 9 2 Costa, R. Dakov, I. Journal of Economic Asymmetries , 7 1 , Deep, K. Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm. Shadana , 41 9 , Defersha, F. A mathematical model and a parallel multiple search path simulated annealing for an integrated distributed layout design and machine cell formation.

Journal of Manufacturing Systems , 43 , Deja, M. Solid State Phenomena , , Feature-based generation of machining process plans for optimised parts manufacture. Journal of Intelligent Manufacturing , 24 4 , Devise, O. Indicators for measuring performances of morphology and material handling systems in flexible manufacturing systems.

International Journal of Production Economics , 64 , Dias, L. Layout and process optimisation: using computer-aided design CAD and simulation through an integrated systems design tool. Drira, A. Facility layout problems: A survey. Annual Reviews in Control , 31 2 , Drolet, J. Simulation-based performance comparison between dynamic cells, classical cells and job shops: a case study. International Journal of Production Research , 46 2 , Ekren, B. A simulation based experimental design to analyze factors affecting production flow time. Simulation Modelling Practice and Theory , 16 3 , Ertay, T.

Simulation approach in comparison of a pull system in a cell production system with a push system in a conventional production system according to flexible cost: A case study.


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International Journal of Production Economics , , Ferreira, J. Performance comparison of the virtual cell layout with cellular and job shop configurations using simulation and design of experiments. An investigation of the influence of alternative process plans on equipment control. Journal of Manufacturing Systems , 19 6 , On the efficiency of alternatives in process plans. Journal of the Brazilian Society of Mechanical Sciences , 23 3 , Freitas Filho, F. Fuchigami, H. Fung, R. A multi-stage methodology for virtual cell formation oriented agile manufacturing.

International Journal of Advanced Manufacturing Technology , 36 , Garza-Reyes, J. A Lean Six Sigma framework for the reduction of ship loading commercial time in the iron ore pelletising industry. Production Planning and Control , 27 13 , Gomes, J. Gupta, A. Configuration selection of reconfigurable manufacturing system based on performance. International Journal of Industrial and Systems Engineering , 20 2 , Haddou Benderbal, H.

Flexibility-based multi-objective approach for machines selection in reconfigurable manufacturing system RMS design under unavailability constraints. International Journal of Production Research , 55 20 , Hamedi, M. Functional and distributed layouts and their effectiveness on capability-based Virtual Cellular Manufacturing systems performance. Dubai: IEEE. A survey on formation of virtual cellular manufacturing systems VCMSs and related issues. Scientific Research and Essays , 7 40 , Capability-based virtual cellular manufacturing systems formation in dual-resource constrained settings using Tabu Search.

Hamedi, H. Virtual cellular manufacturing system based on resource element approach and analyzing its performance over different basic layouts. International Journal of Industrial Engineering Computations , 3 2 , Javadi, B. An integrated approach for the cell formation and layout design in cellular manufacturing systems. International Journal of Production Research , 51 20 , Jayachitra, R.

Lecture 26 Production Planning and Control

Performance analysis of Virtual Cellular Manufacturing: a simulation study. International Journal of Services and Operations Management , 8 1 , A Fuzzy programming approach for formation of virtual cells under dynamic and uncertain conditions. International Journal of Engineering Science and Technology , 2 6 , Jerbi, A. Comparing functional and cellular layouts using simulation and Taguchi method. Journal of Manufacturing Technology Management , 21 5 , Kamaruddin, S. The effect of layout design on productivity: an empirical study.

International Journal of Productivity and Quality Management , 7 4 , Karl, A. Supply chain resilience and key performance indicators: a systematic literature review. Production , 28 0 , e Khaksar-Haghani, F. A genetic algorithm for solving a multi-floor layout design model of a cellular manufacturing system with alternative process routings and flexible configuration.

International Journal of Advanced Manufacturing Technology , 66 , Khilwani, N. A methodology to design virtual cellular manufacturing systems. Journal of Intelligent Manufacturing , 22 4 , Kleijnen, J. Kongchuenjai, J.

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An integer programming approach for process planning for mixed-model parts manufacturing on a CNC machining center. Lv, J. Discussion on the application of activity-based costing in virtual manufacturing cell mode. Applied Mechanics and Materials , , Mahdavi, I. Multi-objective cell formation and production planning in dynamic virtual cellular manufacturing systems.

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It delights a rich human-resource to business. We use cookies to give you the best possible experience. By using our website you agree to our use of cookies. Dispatched from the UK in 3 business days When will my order arrive? Home Contact us Help Free delivery worldwide. Free delivery worldwide. Bestselling Series. Harry Potter. Popular Features. New Releases. Cellular Manufacturing Systems : Design, planning and control. Description Batch manufactcring is a dominant manufacturing activity in the world, generating a great deal of industrial output. In the coming years, we are going to witness an era of mass customization of products.

The major problems in batch manufacturing are a high level of product variety and small manufacturing lot sizes. The product variations present design engineers with the problem of designing many different parts.