A New Combined Dispatching Rule of One-of-a-Kind Assembly Production Process

Article Preview

Abstract:

In this paper, we researched a one-of-a-kind assembly production system where every product is unique (i.e. each product has its unique tree-like process route) and arrives one by one randomly with the exponentially distributed interarrival times. We proposed a new effective combined dispatching rule (ELFT rule) that is constructed by considering three factors: the latest finishing time (LFT), the remaining path size (RPS) and whether an operation is on the critical path (CP). We did many numerical experiments to compare the efficiency between the proposed rule and other rules that were reported in existing studies such as LFT rule and EDD rule. The performance analysis shows that the proposed dispatching rule is more effective in reducing the number of tardy products and total tardiness time.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

409-412

Citation:

Online since:

December 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] J.C. Wortmann. Production management systems for one-of-a-kind products. Computers in Industry, Vol. 19(1992), p.79–88.

DOI: 10.1016/0166-3615(92)90008-b

Google Scholar

[2] R. Rangsatitratsamee, W.G. Ferrell, and M.B. Kurz, Dynamic rescheduling that simultaneously considers efficiency and stability. Computers & Industrial Engineering, Vol. 46(2004), p.1–15.

DOI: 10.1016/j.cie.2003.09.007

Google Scholar

[3] T.C. Chiang, and L.C. Fu. Using dispatching rules for job shop scheduling with due date-based objectives. International Journal of Production Research, Vol. 44(2007), pp.3245-3262.

DOI: 10.1080/00207540600786715

Google Scholar

[4] P.D.D. Dominic, S. Kaliyamoorthy, and M.S. Kumar. Efficient dispatching rules for dynamic job shop scheduling. International Journal of Advanced Manufacturing Technology, Vol. 24(2004), pp.70-75.

DOI: 10.1007/s00170-002-1534-5

Google Scholar

[5] W. Mouelhi-Chibani and H. Pierreval. Training a neural network to select dispatching rules in real time. Computers and Industrial Engineering, Vol. 58(2010), pp.249-256.

DOI: 10.1016/j.cie.2009.03.008

Google Scholar

[6] M.K. Reeja and C. Rajendran. Dispatching rules for scheduling in assembly jobshops – part 1. International Journal of Production Research, Vol. 38(2000), p.2051-(2066).

DOI: 10.1080/002075400188492

Google Scholar

[7] K.M. Mohanasundaram, K. Natarajan, G. Viswanathkumar, P. Radhakrishnan, and C. Rajendran. Scheduling rules for dynamic shops that manufacture multi-level jobs. Computers and Industrial Engineering Vol. 44(2002), pp.119-131.

DOI: 10.1016/s0360-8352(02)00188-2

Google Scholar

[8] B.K. Choi and N.K. You. Dispatching rules for dynamic scheduling of one-of-a-kind production. International Journal of Computer Integrated Manufacturing, Vol. 19(2006), pp.383-392.

DOI: 10.1080/09511920500407541

Google Scholar

[9] C. Hicks, D.P. Song, and C.F. Earl. Dynamic scheduling for complex engineer-to-order products. International Journal of Production Research, Vol. 45(2007), pp.3477-3503.

DOI: 10.1080/00207540600767772

Google Scholar