Skip to main content
Log in

Efficient wafer sorting scheduling using a hybrid artificial immune system

  • General Paper
  • Published:
Journal of the Operational Research Society

Abstract

The efficiency of wafer sorting scheduling is of particular importance in semiconductor fabrication, especially in the face of strong industry competition. This paper presents a novel hybrid artificial immune system (HAIS) algorithm for solving the wafer sorting scheduling problem, aimed at minimizing the total setup time and the number of testers used. To evaluate the performance of the proposed HAIS algorithm and to compare it with existing approaches, computational experiments were conducted on 480 simulation instances generated from the characteristics of a real wafer probe centre. The experimental results revealed that the proposed HAIS algorithm is highly effective and efficient, as compared with state-of-the-art algorithms on the same benchmark.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3

Similar content being viewed by others

References

  • Allahverdi A, Ng CT, Cheng TCE and Kovalyov MY (2008). A survey of scheduling problems with setup times or costs. European Journal of Operational Research 187 (3): 985–1032.

    Article  Google Scholar 

  • Bang JY and Kim YD (2011). Scheduling algorithms for a semiconductor probing facility. Computers and Operations Research 38 (3): 666–673.

    Article  Google Scholar 

  • Chen TR, Chang TS, Chen CW and Kao J (1995). Scheduling for IC sort and test with preemptiveness via Lagrangian relaxation. IEEE Transactions on Systems, Man, and Cybernetics 25 (8): 1249–1256.

    Article  Google Scholar 

  • Cheng TCE and Sin CCS (1990). A state-of-the-art review of parallel-machine scheduling research. European Journal of Operational Research 47 (3): 271–292.

    Article  Google Scholar 

  • Chiang TC, Shen YS and Fu LC (2008). A new paradigm for rule-based scheduling in the wafer probe centre. International Journal of Production Research 46 (15): 4111–4133.

    Article  Google Scholar 

  • Ellis KP, Lu Y and Bish EK (2004). Scheduling of wafer test processes in semiconductor manufacturing. International Journal of Production Research 42 (2): 215–242.

    Article  Google Scholar 

  • Engin O and Döyen A (2004). A new approach to solve hybrid flow shop scheduling problems by artificial immune system. Future Generation Computer Systems 20 (6): 1083–1095.

    Article  Google Scholar 

  • Gong M, Jiao L and Zhang X (2008). A population-based artificial immune system for numerical optimization. Neurocomputing 72 (1-3): 149–161.

    Article  Google Scholar 

  • Hsieh YC, You PS and Liou CD (2009). A note of using effective immune based approach for the flow shop scheduling with buffers. Applied Mathematics and Computation 215 (5): 1984–1989.

    Article  Google Scholar 

  • Huang KL and Liao CJ (2006). Ant colony optimization combined with taboo search for the job shop scheduling problem. Computers and Operations Research 35 (4): 1030–1046.

    Article  Google Scholar 

  • Lin JT, Wang FK and Lee WT (2004). Capacity-constrained scheduling for a logic IC final test facility. International Journal of Production Research 42 (1): 79–99.

    Article  Google Scholar 

  • Lin SW and Ying KC (2008). A hybrid approach for single-machine tardiness problems with sequence-dependent setup times. Journal of the Operational Research Society 59 (8): 1109–1119.

    Article  Google Scholar 

  • Lin SW and Ying KC (2009). Applying a hybrid simulated annealing and tabu search approach to non-permutation flowshop scheduling problems. International Journal of Production Research 47 (5): 1411–1424.

    Article  Google Scholar 

  • Lin SW, Lee ZJ, Ying KC and Lin RH (2011). Meta-heuristic algorithms for wafer sorting scheduling problems. Journal of the Operational Research Society 62 (1): 165–174.

    Article  Google Scholar 

  • Musilek P, Lau A, Reformat M and Wyard-Scott L (2006). Immune programming. Information Sciences 176 (8): 972–1002.

    Article  Google Scholar 

  • Naderi B, Khalili M and Tavakkoli-Moghaddam R (2009). A hybrid artificial immune algorithm for a realistic variant of job shops to minimize the total completion time. Computer & Industrial Engineering 56 (4): 1494–1501.

    Article  Google Scholar 

  • O'Connor JJ and Robertson EF (2012). Student’s t-Test, MacTutor History of Mathematics Archive. University of St Andrews, http://www-history.mcs.st-andrews.ac.uk/Biographies/Gosset.html.

  • Ovacik IM and Uzsoy R (1996). Decomposition methods for scheduling semiconductor testing facilities. International Journal of Flexible Manufacturing Systems 8 (4): 357–387.

    Article  Google Scholar 

  • Pearn WL, Chung SH and Yang MH (2002a). A case study on the wafer probing scheduling problem. Production Planning & Control 13 (1): 66–75.

    Article  Google Scholar 

  • Pearn WL, Chung SH and Yang MH (2002b). The wafer probing scheduling problem (WPSP). Journal of the Operational Research Society 53 (8): 864–874.

    Article  Google Scholar 

  • Pearn WL, Chung SH, Yang MH and Chen YH (2004). Algorithms for the wafer probing scheduling problem with sequence-dependent set-up time and due date restrictions. Journal of the Operational Research Society 55 (11): 1194–1207.

    Article  Google Scholar 

  • Pearn WL, Chung SH, Yang MH and Shiao KP (2008). Solution strategies for multi-stage wafer probing scheduling problem with reentry. Journal of the Operational Research Society 59 (5): 637–651.

    Article  Google Scholar 

  • Tan KC, Goh CK, Mamun AA and Ei EZ (2008). An evolutionary artificial immune system for multi-objective optimization. European Journal of Operational Research 187 (2): 371–392.

    Article  Google Scholar 

  • Tavakkoli-Moghaddam R, Rahimi-Vahed A and Mirzaei AH (2007). A hybrid multi-objective immune algorithm for a flow shop scheduling problem with bi-objectives: Weighted mean completion time and weighted mean tardiness. Information Sciences 177 (22): 5072–5090.

    Article  Google Scholar 

  • Yang J and Chang TS (1998). Multiobjective scheduling for IC sort and test with a simulation test bed. IEEE Transactions on Semiconductor Manufacturing 11 (2): 304–315.

    Article  Google Scholar 

  • Ying KC (2012). Scheduling identical wafer sorting parallel machines with sequence-dependent setup times using an iterated greedy heuristic. International Journal of Production Research 150 (10): 2710–2719.

    Article  Google Scholar 

  • Ying KC and Cheng HM (2010). Dynamic parallel machine scheduling with sequence-dependent setup times using an iterated greedy heuristic. Expert Systems with Applications 37 (4): 2848–2852.

    Article  Google Scholar 

  • Zandieh M, Fatemi Ghomi SMT and Moattar Husseini SM (2006). An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times. Applied Mathematics and Computation 180 (1): 111–127.

    Article  Google Scholar 

  • Zhang Z (2007). Immune optimization algorithm for constrained nonlinear multiobjective optimization problems. Applied Soft Computing 7 (3): 840–857.

    Article  Google Scholar 

  • Zhou Y, Beizhi Li and Yang J (2006). Study on job-shop scheduling with sequence dependent setup times using biological immune algorithm. International Journal of Advanced Manufacturing Technology 30 (1-2): 105–111.

    Article  Google Scholar 

Download references

Acknowledgements

This research was financially supported in part by the National Science Council of the Republic of China (Taiwan), under the Contract Nos. NSC 100-2221-E-027-040-MY2 and NSC 101-2410-H-182-004-MY2.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ying, KC., Lin, SW. Efficient wafer sorting scheduling using a hybrid artificial immune system. J Oper Res Soc 65, 169–179 (2014). https://doi.org/10.1057/jors.2013.8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/jors.2013.8

Keywords

Navigation