Modeling of Scheduling Batch Processor in Discrete Parts Manufacturing

  • M. Mathirajan
  • Ravindra Gokhale
  • M. Ramasubramaniam
Chapter

Abstract

Processing using batch processors (BPs) is common in many manufacturing environments. Generally in a manufacturing environment, BPs are bottleneck operations due to their longer processing time. Batch processing also involves many complexities like compatibility of jobs that can be processed, sizes of different jobs, capacity constraint of the processor, and so on. Considering all these factors, proper scheduling of BPs is important. This chapter focuses on scheduling of BPs in three real life applications, namely, automobile gear manufacturing, semiconductor manufacturing, and steel casting industries. Integer programming models are formulated for the problems under consideration. These models will help the decision makers to understand the problems better and hence work toward appropriate solutions for the problems.

Keywords

Completion Time Mixed Integer Linear Programming Model Wafer Fabrication Total Weighted Tardiness Batch Processing Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Almada-Lobo, B., Oliveira, J. F., & Carravilla, M. A. (2008). Production planning and scheduling in the glass industry: A VVS approach. International Journal of Production Economics, 114, 363–375.CrossRefGoogle Scholar
  2. Azizoğlu, M., & Webster, S. (2000). Scheduling a batch processing machine with non-identical job sizes. International Journal of Production Research, 39, 325–335.Google Scholar
  3. Chan, F. T. S., Au, K. C., & Chan, P. L. Y. (2006). A Decision support system for production scheduling in an ion plating cell. Expert Systems with Applications, 30, 727–738.CrossRefGoogle Scholar
  4. Damodaran, P., & Srihari, K. (2004). Mixed integer formulation to minimize makespan in a flow shop with batch processing machines. Mathematical and Computer Modelling, 40, 1465–1472.MathSciNetCrossRefMATHGoogle Scholar
  5. Fanti, M. P., Maione, B., Piscitelli, G., & Turchiano, B. (1996). Heuristic scheduling of jobs on a multi-product batch-processing machine. International Journal of Production Research, 34(8), 2163–2186.CrossRefMATHGoogle Scholar
  6. Fasano, G. (2008). MIP-based heuristic for non-standard 3D-packing problems. 4OR: A Quarterly Journal of Operations Research, 6, 291–310.MathSciNetCrossRefMATHGoogle Scholar
  7. Garey, M. R., & Johnson, D. S. (1979). Computers and intractability: A guide to the theory of NP-completeness. San Francisco: W. H. Freeman and Co.Google Scholar
  8. Gokhale, R., & Mathirajan, M. (2011). Heuristic algorithms for scheduling of a batch processor in automobile gear manufacturing. International Journal of Production Research, 49, 2705–2728.CrossRefGoogle Scholar
  9. Graham, R. L., Lawler, E. L., Lenstra, J. K. & Rinnooy Kan, A. H. G. (1979). Optimization and approximation in deterministic sequencing and scheduling: a survey. Annals of Discrete Mathematics, 5, 287–326.Google Scholar
  10. Koh, S. G., Koo, P. H., Ha, J. W., & Lee, W. S. (2004). Scheduling parallel batch processing machines with arbitrary job sizes and incompatible job families. International Journal of Production Research, 42, 4091–4107.CrossRefMATHGoogle Scholar
  11. Li, S., Ng, C. T., Cheng, T. C. E., & Yuan, J. (2011). Parallel-batch scheduling of deteriorating jobs with release dates to minimize the makespan. European Journal of Operational Research, 210, 482–488.Google Scholar
  12. Malve, S., & Uzsoy, R. (2007). A genetic algorithm for minimizing maximum lateness on parallel identical batch processing machines with dynamic job arrivals and incompatible job families. Computers & Operations Research, 34, 3016–3028.MathSciNetCrossRefMATHGoogle Scholar
  13. Mathirajan, M., & Sivakumar, A. I. (2006a). Minimizing total weighted tardiness on heterogeneous batch processing machines with incompatible job families. International Journal of Advanced Manufacturing Technology, 28, 1038–1047.CrossRefGoogle Scholar
  14. Mathirajan, M., & Sivakumar, A. I. (2006b). A literature review, classification and simple meta-analysis on scheduling of batch processors in semiconductor. International Journal of Advanced Manufacturing Technology, 29, 990–1001.CrossRefGoogle Scholar
  15. Oulamara, A. (2007). Makespan minimization in a no-wait flow shop problem with two batching machines. Computers & Operations Research, 34(4), 1033–1050.MathSciNetCrossRefMATHGoogle Scholar
  16. Ozturk, O., Espinouse, M.-L., Mascolo, D., & Gouin, A. (2010). Optimizing the makespan of washing operations of medical devices in hospital sterilization services. In Proceedings of 2010 IEEE Workshop on Health Care Management, Italy, 1–6.Google Scholar
  17. Padberg, M. (2000). Packing small boxes into a big box. Mathematical Methods of Operations Research, 52, 1–21.MathSciNetCrossRefMATHGoogle Scholar
  18. Perez, I. C., Fowler, J. W. & Carlyle, W. M. (2005). Minimizing total weighted tardiness on a single batch process machine with incompatible job families. Computers and Operations Research, 32, 327–341.Google Scholar
  19. Ponsignon, T., & Mönch, L. (2011). Heuristic approaches for master planning in semiconductor manufacturing. Computers & Operations Research, 39, 479–491.CrossRefGoogle Scholar
  20. Potts, C. N., & Kovalyov, Y. (2000). Scheduling with batching: A review. European Journal of Operational Research, 120, 228–249.Google Scholar
  21. Ramasubramanian, M., Mathirajan, M., & Ramachandran, V. (2010). Minimizing makespan on a single heat-treatment furnace in Steel Casting Industry. International Journal of Services and Operations Management, 7, 112–142.CrossRefGoogle Scholar
  22. Roberts, C. A., Dessouky, M. M., & Dessouky, Y. M. (1999). A virtual plant modeller (VPMOD) for batch-chemical processes. Journal of Intelligent Manufacturing, 10, 211–223.Google Scholar
  23. SIA-Semiconductor Industry Association (2012, September). Industry statistics. Retrieved November 28, 2012, from http://www.sia-online.org/clientuploads/GSR/September%202012%20GSR%20table%20and%20graph%20for%20press%20release.pdf
  24. Uzsoy, R., Lee, C. Y., & Martin-Vega, L. A. (1992). A review of production planning and scheduling models in the semiconductor industry, part I: System characteristics, performance evaluation and production planning. IIE Transactions, 24, 47–61.CrossRefGoogle Scholar
  25. Yaghubian, A. R., Hodgson, T. J., Joines, J. A., Culbreth, C. T., & Huang, J. C. (2001). Dry-or-buy decision support for dry kiln scheduling in furniture production. IIE Transactions, 33, 131–136.Google Scholar
  26. van der Zee, D. J., Van Harten, A., & Schuur, P. C. (2001). On-line scheduling of multi-server batch operations. IIE Transactions, 33, 569–586.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • M. Mathirajan
    • 1
  • Ravindra Gokhale
    • 2
  • M. Ramasubramaniam
    • 3
  1. 1.Department of Management StudiesIndian Institute of ScienceBangaloreIndia
  2. 2.Indian Institute of Management IndoreIndoreIndia
  3. 3.School of Maritime ManagementIndian Maritime UniversityChennaiIndia

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