A new dynamic scheduling for batch processing systems using stochastic utility evaluation function

Abstract

In long production cycles, the earliness and tardiness weight (utility) of products vary depending on the time. It is necessary to reflect the weight of products for earliness and tardiness at decision epochs to decide on the optimal strategy. This research demonstrates the use of Stochastic Utility Evaluation (SUE) function approach to optimize system performance using multiple criteria. In addition, this research explores how SUE function using stochastic information can be derived and used to strategically improve existing approaches. SUE function for earliness and tardiness is used in an existing model to develop a triobjective problem. Typically, this problem is very complex to solve due to its trade-off relationship. However SUE function makes it relatively easy to solve the tri-objective problem since SUE function can be incorporated in an existing model. It is observed that SUE function can be effectively used for solving a tri-objective problem. INTRODUCTIONThe semiconductor industry has continued to be an important field of research in recent years because of the widespread use of integrated circuits (IC) in devices ranging from personal computers to high-tech electronics. Due to the growth of the semiconductor market, research in IC fabrication technology and methodology is steadily expanding. Wafer production is a very complex process with a long production cycle; and much of the complexity results from batching, time-step, and sequencing problems at several stages of the cycle. The majority of problem-solving methods attempt to minimize production attributes such as cycle time, earliness and tardiness (Mathirajan and Sivakumar 2006). Most often, the batch process itself is the bottleneck, particularly since competing factors come into play for the important decision to run a partial batch versus waiting for future arrivals to form a full batch. On-time delivery and rapid production of wafers are the two critical factors affecting the retention of customers and influencing the performance of manufacturer. Diffusion furnaces are the most commonly used batch processors in semiconductor production. Yet while they can handle a batch of products concurrently, their processing times are too slow compared to serial processors that handle one product at a time. This research analyzes forthcoming performance-enhancing measures in the decision-making phase of batch processing that aid in controlling batch processors. At the decision epoch, most models use a static weight for product type; however, if earliness and tardiness are considered at the decision point, the dynamic weight for product type needs to be estimated according to stochastic information in the long-run control of a batch processor and multiple product types. 2302978-1-4577-2109-0/11/$26.00 ©2011 IEEE

Effect of upstream re-sequencing in controlling cycle time performance of batch processors

“…They performed a comparative evaluation of the approach by modifying MBH and DBH to use utility function, referred to as MBH-U and DBH-U respectively. Subsequently, they have used a utility function based approach to model the batch control problem for multiple criteria by assigning penalty weights to tardiness, earliness and cycle time (Park & Banerjee, 2011). The performance of the utility function based approach is limited to the definition of the utility functions and their accuracy.…”