a. Find the duplicate cell for complete line:
b. The arrange of cell:
For each kind of cell, the number of copy cell is four. First of all, the whole process is arranged. Then, the duplicate cell is copy to other area. The figure 4.13 shows the assembly process.
62
Bracket (5)
Bracket
Bracket (5) Bracket
Bracket
Bracket
B r a c k e t
Cell 1 Cell 2 Cell 3 and Cell 4 Cell 5 Cell 6 Cell 7
Figure 4. 13 Cell arrangement
First, the cell one takes material and assembles it. Then, the unfinished part transfers to cell to and do the assembly test function. Next, the part moves to the bracket. In this area, many parts will be run here, because the time of this cell is longest, that is why we need the number of bracket. After finishing running process, the part transfer to cell 6 and cell 7 to finish the whole assembly process. The finish product is located on cell 7. For the duplicate with four cells, we have the layout of whole process in the figure 4.14.
63
Figure 4. 14: Layout for 4 duplicate cells c. The material and the finished product transfer
The material and finished product is use conveyor to transfer. As shown in the figure 4.15. In this case, the material is not process and it is stuff at the end of conveyor for material.
It is taken back by one operator. Then, it transfers again on the conveyor.
64
Brack et (5)
Bracket Brack et (5)
Bracket Bracket Bracket
B r a c k e t Cell 1Cell 2Cell 3 and Cell 4Cell 5
Cell 6Cell 7 Brack et (5)
Bracket Brack et (5)
Bracket Bracket Bracket
B r a c k e t Cell 1Cell 2Cell 3 and Cell 4Cell 5
Cell 6Cell 7 Brack et (5)
Bracket Brack et (5)
Bracket Bracket Bracket
B r a c k e t Cell 1Cell 2Cell 3 and Cell 4Cell 5
Cell 6Cell 7 Brack et (5)
Bracket Brack et (5)
Bracket Bracket Bracket
B r a c k e t Cell 1Cell 2Cell 3 and Cell 4Cell 5
Cell 6Cell 7
Conveyor for Material Conveyor for finishing product
Figure 4. 15: Combined production layout 1
The other method is use circular conveyor for material transfer. And the linear for the finished product transfer. It is show in the figure 4.16. Because the limit of paper, the cells are not shown clear, the cell 1 and cell 7 is shown. The seven cells are similar with the above Figure 4.16.
65
Figure 4. 16 Combined production layout 1 4.6. Evaluation
Figure 4. 17 Flow manufacturing
The Figure 1.5 describes one example of continuous flow manufacturing and this is layout of the continuous flow manufacturing. First, all materials transfer to the ASSY (assembly) to assemble all material together. Then, this unfinished part moves to assembly function test aim to check the function of the assembly processing. After that, this part downloads test program in the TPDL (test program download). Next, this program is executed in the Run-in process. After finishing it, the part puts in the PFT (Program Function Test).
Subsequently, this part loads some software in the SWDL (software download). Finally, this part is finished by the packing process in the Pack (packing) station.
66
The current situation of continuous flow manufacturing is described in the figure 4.18 and 4.19. In the figure 4.1, the conveyor includes two parts. Part one includes ASSY, AFT, SWDL with 37 operators and the time is shown by figure 4.18. Part two includes PFT, Packing SWDL with 41 operators. This time of 41+37 = 78 stations and the other factors is drawn in two figures. As we can see, the balance rate of this production is 63% and the cycle time of this line is 8.008 seconds.
Figure 4. 18 Time for conveyor 1
Figure 4. 19: Time for conveyor 2
To evaluate the effective of the combine production line, it is easy to see the result from the current situation and the new solution by table 4.10.
Name Formula Continuous flow
manufacturing
Combined production line
Direct labor 78 64
Work Hour standard 8 hours 8 hour
67
Loss rate 5% 5%
Bottleneck cell Max(cell) 8.004 seconds 30.04/4= 7.51 seconds
Working hour WH=DL*WHS 624 hours 512 hours
Balance rate 0.63 0.95
Table 4. 10 The comparison between current situation and result The balance rate of combined production line is calculated:
This combined production line has 28 cells, and the cycle time is 30.04 seconds. The machine cells do not calculate in this situation. The time of assembly cell is most imbalance of processing. The total time of assembly cell is:
Total time of assembly cell = (89.06+87.05+116.03+107.59) = 399.7 seconds So balance rate = 399.73/ (30.04x14) = 95 %.
4.7. Conclusion
The preceding example demonstrates how to design the combined production line in order to significantly improve the efficiency of throughput and consequently, increase the profit contribution of a manufacturing cell. The example also demonstrates how the designing process of combined production line functions.
The benefit of implementing a combined production line is a decreased number of worker necessary to achieve a balanced rate of production. The number of workers decreases from 74 to 64 workers in this example. And the balance rate is increased, so that the mean of production effectiveness is improved. We can easily see the benefit after a comparison with the current situation of a company. In addition, the main point of implementing the combined production line is that it is compatible with current market trends, when a scale of mass production is no longer suitable. This is why cellular manufacturing has become evermore necessary for companies to develop it they are to meet market trends.
68
Although the preceding example provides insight into the design of a new manufacturing cell, the combined production line approach can also be used to improve the overall performance of line, because cycle time is reduced and a minimum loss rate will be based on the sequence specified.
69
Future Study
The limitation of this thesis provides a direction for future research. So far, we have focused on designing the combined production line for difficult cases such as with mechanical cases (including CNC, NC machines). The case study provided only mentions one simple case of involving notebook manufacturing, but it points out larger solutions applicable to more diverse manufacturing environment. Thus, for complicated cases, it may develop a huge quantity of solutions. After that, designers can choose the best solution available.
Instead, our goal is to extend our current approach to simulation problems. Due to the huge number of solutions could be generated, it wastes a great amount of time and cost when does in a practical way. This is why we should check it using a simulation. Steps are known and one algorithm should be found, that is a good way to simulate, because it already indicates the algorithm for the programmer, so they can develop the algorithm to be programmed. This development will help designers to save both time and cost.
Finally, our work thus far has focused on utilization of a flexible cell component.
Nowadays, the market trend is to change from quantity to quality. Thus, one cell does not produce one kind of product, it has to produce a variety of kinds. So, the cell machine and operators also have to change in order to respond to the demands of the product involved. It is the same purpose of Cellular Manufacturing given in the introduction section of this paper.
In conclusion, for future study, we want to explore the simulation and flexible cell structure as well as mechanical implementation as a way of affecting a combined production line. Then, we can develop the advantages and eliminate the disadvantages of this method and review the process to make it more practical.
70
Conclusions
This thesis addressed the information of a combined production line, where cell manufacturing and flow manufacturing are duly combined. A simulated experiment has been illustrated. The initial definition of combine production line is mentioned.
To determine the performance of the combined production line, comparisons were made in one department of one company. It has been tested with a real production line and real workers. According to test results, this kind of manufacturing method can provide optimal solution in some situations. The advantages of this manufacturing method are easy to see because it contains advantages of both cellular and flow manufacturing in several characteristics, such as with worker competition, flexibility of product, easy to supply materials, continuous flow of work, and smooth and uninterrupted operations. In addition, this method is suitable for companies that may want to change this manufacturing method from a form of flow manufacturing to cellular manufacturing. It helps to save cost and time involved, we have to consider the disadvantages of such a method as well. We need to calculate the time spent carefully, initial capital and machine utilization dispensed with intentionally or unintentionally.
To successfully use the combined production line approach and obtain its optimal potential benefits, a designer must understand the designing step (section 3.2) to evaluate the solution. Without such knowledge, a designer may develop the combined production line through trial-and-error. However, the number of iterations required to do so would be rather unwieldy and the designer might not be able to incorporate the new configuration because they would not understand why the configuration is efficient or inefficient. A deeper understanding could quickly use the design process to find a better solution in a lesser amount of time.
When performing a preliminary design for forming a manufacturing cell, a designer should use the process based on the above writing. After designing a solution, taken from analysis, it might not be useful in itself. However, its value is taken from a relative basis, when comparing results to other iterations of the same analysis, it may be quite useful. By comparing these results versus comparing the input parameters and manufacturing cell configurations that were employed, the designer can quickly determine which design parameters have the greatest leverage to form improved manufacturing cell performance.
The most importance component of the designing process is the design engineer him or herself. The basis of knowledge can provide this method; thereby, it will allow the designer
71
to perform their job better. In this way the value of the design tool to the organization is increased by the skills of the designer. This is because the designers continue to be responsible for the design process. The method aids the designer in developing an efficient design in a timely sequence manner for little ỏ not design cost expenditure.
In the future, mechanical products need to be implemented and comparisons between some methods should be made, so that family parts are assigned into proper cell groups. It is believed that this may allow for a significant improvement other than the experimental results described in this paper and promise to increase optimal performance of the combined production line approach even more.
72
References
[1]. M.I. Khan, “Industrial Engineering”, New Age International Pvt Ltd, India2.
[2]. Wilson J. M. and Foulds L. R., “Approach to cell formation problem”, Volume 33, Issue 4 (April 2006), 1010 – 1032, (2006).
[3]. Russell and Taylor, “Operation managements”, fifth edition, (2006).
[4]. J. Nichol and A. Soni, “The Portal to Lean Production”, (2006).
[5]. Wei N. C., Olugbenga O. M., “A clustering approach for minimizing intercell trips in cell formation”, January 2007, Springer science and business media, LLC 2007.
[6]. Tran V. D., “Thiết kế dây chuyền sản xuất”, Vietnam (2005).
[7]. Tran V. D., “Quản Lý Sản Xuất”, Vietnam (2006).
[8]. S. Nicoletti, G. Nicosia, A. Pacifici, “Group technology with flow shop cells”, April 1988, Roma Italia.
[9]. King, J. R. and Nakornchai, “V(1982) Machine-component group formation in group technology: review and extension. International Journal of production research”, 20(2), 117-133.
[10]. S. D. Lee and C. P. Chiang, “A cut-tree-based approach for clustering machine cells in the bidirectional linear flow layout”, International Journal of production research, 15, 3491-3512.
[11]. B. Rekiek, P. D. Lit and A. Delchambre, “Designing Mixed-Product Assembly lines”, IEEE Transactions on Robotics and Automation, Vol. 16, No. 3, June (2000).
[12]. A. Agarwal, “Partitioning bottleneck work center for cellular manufacturing: an integrate performance and cost model”, Int. J. Production economics 111, pp. 635-647, (2008).
[13]. C. P. Chiang and S. D. Lee, “A genetic-based algorithm with the optimal partition approach for the cell formation in bi-directional linear flow layout”, Int. J. Computer integrated manufacturing, Vol. 17, No. 4, pp. 367 -375, (2004).
[14]. P. D. Lit, J. Danloy, A. Delchambre and J. M. Henrioud, “An Assembly-Oriented Product Family Representation for Integrated Design”, IEEE Transactions on Robotics and Automation, Vol. 19, No. 1, (2003).
[15]. W. Ying and L. Bin, “Job-shop Scheduling using Genetic Algorithm”, IEEE, (1996).
[16]. N. Chaiyarataiia and A. M. S. Zalzala, “Recent developments in Evolutionary and Genetic Algorithms: Theory and Applications”, Genetic Algorithms in Engineering
73
Systems: Innovations and Applications, 2-4 September 1997, Conference Publication NO.
446, IEE, (1997).
[17]. R.D. Pullen, “A survey of cellular manufacturing cells”, Production Engineering, (1976).
[18]. “Manufacturing Engineer”, Developing the Sequence, April (1994).
[19]. ”Manufacturing Engineer”, Going Cellular, February (2003).
[20]. W. P. McLaughlin, “The introduction of cellular manufacturing at Bomford Turner”, 1, (1994).
[21]. P. C. Kulkarni, K. Shanker, “A Genetic Algorithm for Layout problems in Cellular Manufacturing Systems”, IEEE IEEM, (2007).
[22]. H. Kor, H. Iranmanesh, H. Haleh, and S. M. Hatefi, “A Multi-objective Genetic Algorithm for optimization of Cellular manufacturing system”, IEEE IEEM, (2009).
[23]. R. D. Lorenzo, S. Fichera, V. Grasso, “Scheduling a cellular manufacturing system with GA”, Second International Conference on Knowledge-Based Intelligent Elecuonic System, 21-23, April (1998).
[24]. N. Morad and AMs Zalzala, “Formulations for cellular manufacturing and batch scheduling using genetic algorithms”, UKACC International Conference on CONTROL '96, 2-5 September 1996, Conference Publication No. 427 0 IEE (1996).
[25]. D. Patrick, P. Green and T. York, “A distributed genetic algorithm environment for unit workstation clusters”, Genetic Algorithms in Engineering Systems: Innovations and Applications, 2-4 September 1997, Conference Publication No. 446, O IEE, (1997).
[26]. Y. Xing, Z. Chen, J. Sun and L. H. An, “Improved Adaptive Genetic Algorithm for Job-Shop Scheduling Problem”, Third International Conference on Natural Computation (ICNC 2007).
[27]. J. Stender, “Introduction to Genetic Algorithms”, (1995).
[28]. W. Ying, L. Bin, “Job-shop Scheduling using Genetic Algorithm”, (1996).
[29]. “Job-shop Scheduling using Genetic Algorithm, Recent Developments in Evolutionary and Genetic Algorithms: Theory and Applications”, Genetic Algorithms in Engineering Systems: Innovations and Applications, 2-4 September 1997, Conference Publication NO.
446, IEEE , (1997).
[30]. J. GOMBINSKI, “Group Technology -An Introduction”, (1995).
[31]. J. L. Burbidge, Heinemann, “The Introduction of Group Technology”, 268pp. (1975).
[32]. J. D. Tedford, BSc, PhD, CEng, Ml Prod E T. J. Ferris, MSc “The application of group trachnology at the production planning phase of a new product”, (1960).
[33]. Y. Hu, F. Ye, Z. Fang, “A study on the integration of lean production and group
74 technology”, ICMIT (2000).
[34]. W. T. Whitfield, “Applying Group Technology to Petermann Auto Components”, The Production Engineer-September, (1972).
[35]. C. C. Gallagher, T. J. Grayson, “Group technology in the plastics moulding industry”, The Production Engineer, April (1973).
[36]. “Some lessons from a decade of Group Technology”, The Production Engineer, November (1980).
[37]. “The economic benefits of group technology”, The Production Engineer, November (1980).
[38]. M. T. Leung, R. Quintana, A. S. Chen, “A Paradigm for Group Technology Cellular Layout Planning”, JIT Facility, IEEE, (2008).
[39]. J.M. Proth, “Group technology in production management A tool to simplify some scheduling problems”, (1986).
[40]. J. V. Zyl, A. J. Walker, “Product Line Balancing”, IEEE, (2001).
[41]. L. Gu, S. Hennequin, A. Sava and X. Xie, “Assembly Line Balancing Problems Solved by Estimation of Distribution”, Proceedings of the 3rd Annual IEEE Conference on Automation Science and Engineering Scottsdale, AZ, USA, Sept 22-25, (2007).
[42]. B. Ying, Z. H. Shun, Z. Liao, “Mixed-model Assembly Line Balancing Using the Hybrid Genetic Algorithm”, IEEE, (2009).
[43]. Z. R. Jun, C. D. Fang , W. Yong, Y. Z. Hua1,W. X. Xin, “Study on Line Balancing Problem Based on Improved Genetic Algorithms”, IEEE , (2007).
[44]. E. Falkenauer, A. D. Roctedings, “A genetic algorithm for bin packing and line balancing”, IEEE International Conference on Robotic and Automation, May (1992).
[45]. A. Baykasoglu, L. OzbakIr, L. Gorkemli, B. Gorkemli, “Balancing Parallel Assembly Lines via Ant Colony Optimization”, IEEE, (2009).
[46]. D. A. Ajenblit, Roger L. “Wainwright Applying genetic algorithms to the U-shaped assembly line balancing problem”, IEEE, (1998).
[47]. U. Martinez, W. S. Duff, “Heuristic approaches to solve the U-shaped line balancing problem augmented by genetic algorithms”, Proceedings of the 2004 Systems and Information Engineering Design Symposium Matthew H. Jones, Stephen D. Patek, and Barbara E. Tawney, eds.
[48]. B. Rekiek and A. Delchambre, “Hybrid Assembly Line Design”, Proceedings of the 4th IEEE International Symposium on Assembly and Task Planning Soft Research Park, Fukuoka, Japan May 28-29,(2001).
75
[49]. S.M.J Mirzapour AI-e-hashem, M. B. Aryanezhad , H. Malekly , S. J. Sadjadi, “Mixed Model Assembly Line Balancing Problem under Uncertainty”. IEEE, (2009).
[50]. J. Driscoll, D. Thilakawardana, “The definition of assembly line balancing difficulty and evaluation of balance solution quality”, Robotics and Computer Integrated Manufacturing, 17, 81-86, (2001).