• DocumentCode
    1460113
  • Title

    Control of a Single Batch Processor With Incompatible Job Families and Future Job Arrivals

  • Author

    Tajan, John Benedict C ; Sivakumar, Appa Iyer ; Gershwin, Stanley B.

  • Author_Institution
    Singapore-MIT Alliance, Singapore, Singapore
  • Volume
    24
  • Issue
    2
  • fYear
    2011
  • fDate
    5/1/2011 12:00:00 AM
  • Firstpage
    208
  • Lastpage
    222
  • Abstract
    We examine the problem of minimizing the mean cycle time of a batch processor with incompatible job families and future job arrivals. Batch processors frequently found in wafer fabrication include oxidation and diffusion ovens. When the problem is deterministic with a fixed number of job arrivals, the problem is NP-hard; an optimal dynamic program formulation is developed and empirically tested on small problem instances. For larger problem instances with possibly infinite job arrivals, an online heuristic based on model predictive control (MPC) is proposed. The proposed heuristic has two parameters: the number of job families considered f, and the number of future job arrivals L. Statistical analysis of simulation results shows that the MPC-based heuristic has significantly lower mean cycle time than a benchmark look-ahead method under the assumption that the arrival time is deterministic and job families of consecutive job arrivals are uncorrelated. These observations also hold true when the predicted arrival times can be erroneous, indicating that the suggested MPC-based heuristic is as robust as the benchmark with respect to errors in forecasted arrival times. When the job families of future job arrivals are positively correlated, the mean cycle time of jobs passing through the batch processor is significantly reduced, regardless of control policy. We infer that the introduction of correlation generates less improvement for policies that foresee events longer into the future. For this reason, when the correlation is high, the MPC-based heuristic, which considers events that occur farther into the future, may have worse performance than the benchmark. The results suggest two ways to improve the performance of the batch processor. First, we can use a heuristic that has better mean performance, which may entail much larger computational costs. Another option is to continue using a simple look-ahead policy at the batch processor, and focus attention on controlling the upstream processors, such that the batch processor arrival process exhibits correlated job families between consecutive arrivals. This introduction of correlation causes a significant reduction of cycle time regardless of system parameter and batch processor control policy.
  • Keywords
    batch processing (industrial); computational complexity; dynamic programming; predictive control; semiconductor device manufacture; statistical analysis; MPC-based heuristic; NP-hard; benchmark look-ahead method; computational costs; incompatible job family; job arrival; mean cycle time; model predictive control; optimal dynamic program formulation; single batch processor control; statistical analysis; upstream processor; wafer fabrication; Algorithm design and analysis; Batch production systems; Complexity theory; Dynamic programming; Dynamic scheduling; Processor scheduling; Program processors; Batch processor; cycle time; optimal control; wafer fabrication;
  • fLanguage
    English
  • Journal_Title
    Semiconductor Manufacturing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0894-6507
  • Type

    jour

  • DOI
    10.1109/TSM.2011.2120850
  • Filename
    5720553