Effect of Buffer Size Variation on Remanufacturing Environment

Abstract:

A remanufacturing is an independent institution in which a variety of activities such as disassembly, inspection, disposing, refurbishing, repairing, remanufacturing, transportation and reassembly are performed. We propose an approach that uses an open queuing network, decomposition principle and expansion methodology to analyze the remanufacturing system and use Taguchi method to find out how much the buffer sizes affect on performance. The objective function values, throughput and total cost, are calculated for each experiment. Main effects plots show how each factor affects the response characteristic.

• Periodical: Advanced Materials Research (Volume 845)
• Pages: 755-759
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.845.755
• Online since: December 2013
• Authors: Vahid Abbasgholi Pourghadim*, M.Y. Noordin, Kuan Yew Wong
• Keywords: Buffer Allocation, Limited Capacity, Queuing Networks, Remanufacturing

References

[1] Chaharsooghi, S. and N. Nahavandi, Buffer allocation problem, a heuristic approach, Scientia Iranica 10(4) (2003) 401-409.

[2] Demir, L., Tunali, S., & Løkketangen, A., A tabu search approach for buffer allocation in production lines with unreliable machines, Engineering Optimization, 43(2) (2011) 213–231.

DOI: 10.1080/0305215x.2010.481022

[3] Spinellis, D., Papadopoulos, C., & Smith, J. M., Large production line optimization using simulated annealing, International Journal of Production Research, 38(3) (2000) 509–541.

DOI: 10.1080/002075400189284

[4] Aksoy, K. H., & Gupta, S. M., Near optimal buffer allocation in remanufacturing systems with N-policy, Computers, Industrial Engineering, 59(2010) 496–508.

DOI: 10.1016/j.cie.2010.06.004

[5] Amiri, M. and A. Mohtashami, Buffer allocation in unreliable production lines based on design of experiments, simulation, and genetic algorithm, The International Journal of Advanced Manufacturing Technology 62(1-4) (2012) 371-383.

DOI: 10.1007/s00170-011-3802-8

[6] Helber, S., Cash-flow-oriented buffer allocation in stochastic flow lines, International Journal of Production Research, 39(14) (2001) 3061–3083.

DOI: 10.1080/00207540110056144

[7] Nahas, N., Ait-Kadi, D., & Nourelfath, M., Selecting machines and buffers in unreliable series-parallel production lines, International Journal of Production Research, 47(14) (2009) 3741–3774.

DOI: 10.1080/00207540701806883

[8] Shi, L., & Men, S., Optimal buffer allocation in production lines, IIE Trans, 35(2003) 1–10.

DOI: 10.1080/07408170304431

[9] Dolgui, A., Eremeev, A., & Sigaev, V., HBBA: Hybrid algorithm for buffer allocation in tandem production lines, Journal of Intelligent Manufacturing, 18 (2007) 411–420.

DOI: 10.1007/s10845-007-0030-z

[10] Can, B., & Heavey, C., A comparison of genetic programming and artificial neural networks in metamodeling of discrete-event simulation models, Computers, Operations Res. 39 (2012) 424-436.

DOI: 10.1016/j.cor.2011.05.004

[11] Aksoy, H. K. and S. M. Gupta, Buffer allocation plan for a remanufacturing cell, Computers & Industrial Engineering, 48(3) (2005) 657-677.

DOI: 10.1016/j.cie.2003.03.007