Scheduling of Batch Processors in Semiconductor Manufacturing – A Review

In this paper a review on scheduling of batch processors (SBP) in semiconductor manufacturing (SM) is presented. It classifies SBP in SM into 12 groups. The suggested classification scheme organizes the SBP in SM literature, summarizes the current research results for different problem types. The classification results are presented based on various distributions and various methodologies applied for SBP in SM are briefly highlighted. A comprehensive list of references is presented. It is hoped that, this review will provide a source for other researchers/readers interested in SBP in SM research and help simulate further interest.Singapore-MIT Alliance (SMA

Markov Process Modeling of A System Under WIPLOAD Control

This paper analyzes a proposed release controlmethodology, WIPLOAD Control (WIPLCtrl), using a transfer line case modeled by Markov process modeling methodology. The performance of WIPLCtrl is compared with that of CONWIP under 13 system configurations in terms of throughput, average inventory level, as well as average cycle time. As a supplement to the analytical model, a simulation model of the transfer line is used to observe the performance of the release control methodologies on the standard deviation of cycle time. From the analysis, we identify the system configurations in which the advantages of WIPLCtrl could be observed.Singapore-MIT Alliance (SMA

Performance of a Serial-Batch Processor System with Incompatible Job Families under Simple Control Policies

A typical example of a batch processor is the diffusion furnace used in wafer fabrication facilities (otherwise known as wafer fabs). In diffusion, silicon wafers are placed inside the furnace, and dopant is flown through the wafers via nitrogen gas. The higher the temperature, the faster the dopant penetrates the wafer surface. Then, a thin layer of silicon dioxide is grown, to help the dopant diffuse into the silicon. This operation can take 10 hours or more to finish processing, as compared to one or two hours for other wafer fab operations, according to Uzsoy [8]. Diffusion furnaces typically can process six to eight lots concurrently; we call the lots processed concurrently a batch. The quantity of lots loaded into the furnace does not affect the processing time. Only lots that require the same chemical recipe and temperature may be batched together at the diffusion furnace. We wish to control the production of a manufacturing system, comprised of a serial processor feeding the batch processor. The system produces different job types, and each job can only be batched together with jobs of the same type. More specifically, we explore the idea of controlling the production of the serial processor, based on the wip found in front of the batch processor. We evaluate the performance of our manufacturing system under several simple control policies under a range of loading conditions and determine which control policies perform better under which conditions. It is hoped that the results obtained from this small system could be extended to larger systems involving a batch processor, with particular emphasis placed on the applicability of such policies in wafer fabrication.Singapore-MIT Alliance (SMA

Scheduling rules to achieve lead-time targets in outpatient appointment systems

This paper considers how to schedule appointments for outpatients, for a clinic that is subject to appointment lead-time targets for both new and returning patients. We develop heuristic rules, which are the exact and relaxed appointment scheduling rules, to schedule each new patient appointment (only) in light of uncertainty about future arrivals. The scheduling rules entail two decisions. First, the rules need to determine whether or not a patient's request can be accepted; then, if the request is not rejected, the rules prescribe how to assign the patient to an available slot. The intent of the scheduling rules is to maximize the utilization of the planned resource (i.e., the physician staff), or equivalently to maximize the number of patients that are admitted, while maintaining the service targets on the median, the 95th percentile, and the maximum appointment lead-times. We test the proposed scheduling rules with numerical experiments using real data from the chosen clinic of Tan Tock Seng hospital in Singapore. The results show the efficiency and the efficacy of the scheduling rules, in terms of the service-target satisfaction and the resource utilization. From the sensitivity analysis, we find that the performance of the proposed scheduling rules is fairly robust to the specification of the established lead-time targets

Control of Job Arrivals with Processing Time Windows into Batch Processor Buffer

Consider a two-stage manufacturing system composed of a batch processor and its upstream feeder processor. Jobs exit the feeder processor and join a queue in front of the batch processor, where they wait to be processed. The batch processor has a finite capacity Q, and the processing time is independent of the number of jobs loaded into the batch processor. In certain manufacturing systems (including semiconductor wafer fabrication), a processing time window exists from the time the job exits the feeder processor till the time it enters the batch processor. If the batch processor has not started processing a job within the job’s processing time window, the job cannot proceed without undergoing rework or validation by process engineers. We generalize this scenario by assigning a reward R for each successfully processed job by the feeder processor, and a cost C for each job that exceeds its processing time window without being processed by the batch processor. We examine a problem where the feeder processor has a deterministic processing time and the batch processor has stochastic processing time, and determine that the optimal control policy at the feeder processor is insensitive to whether the batch processor is under no-idling or full-batch policy.Singapore-MIT Alliance (SMA

Optimisation of flow-shop scheduling with batch processor and limited buffer

This paper deals with a flow-shop scheduling problem with limited intermediate buffer. Jobs are grouped in incompatible job families. Each job has to be processed by a batch processor followed by a discrete processor in the same order. The batch processor can process several jobs simultaneously so that all jobs of the same batch start and complete together. We assume that the capacity of batch processor is bounded. The batch processing time is identical for batches of the same family. A batch which has completed processing on the batch processor may block the processor until there is a free unit in the buffer. The objective is to determine a batching and scheduling for all jobs so as to minimise mean completion time. A lower bound and two heuristics algorithm are developed. Moreover, a two-stage method embedded with a Differential Evolution (DE) algorithm is also developed. DE is one of the latest evolutionary computation algorithms, which implements mutation, crossover, and selection operators to improve the candidate solutions iteratively. Three variants of DE are first compared with a continuous Genetic Algorithm employing the random key representation. Then, one variant of the DE with the best convergence speed is selected. Numerical experiments are conducted to evaluate the performances of the selected two-stage meta-heuristic and two heuristics

Optimal Methodology for Synchronized Scheduling of Parallel Station Assembly with Air Transportation

We present an optimal methodology for synchronized scheduling of production assembly with air transportation to achieve accurate delivery with minimized cost in consumer electronics supply chain (CESC). This problem was motivated by a major PC manufacturer in consumer electronics industry, where it is required to schedule the delivery requirements to meet the customer needs in different parts of South East Asia. The overall problem is decomposed into two sub-problems which consist of an air transportation allocation problem and an assembly scheduling problem. The air transportation allocation problem is formulated as a Linear Programming Problem with earliness tardiness penalties for job orders. For the assembly scheduling problem, it is basically required to sequence the job orders on the assembly stations to minimize their waiting times before they are shipped by flights to their destinations. Hence the second sub-problem is modelled as a scheduling problem with earliness penalties. The earliness penalties are assumed to be independent of the job orders.Singapore-MIT Alliance (SMA

Reinforcement learning based predictive maintenance for a machine with multiple deteriorating yield levels

This paper proposes a predictive maintenance methodology for a machine in manufacturing with deterior- ating quality states represented by multiple deteriorating yield levels. Imperfect minor maintenance and perfect major repair are considered. The underlying yield level cannot be directly obtained. Instead, product quality inspection information is used as the observed system state. The optimal maintenance policy associated with each possible observed system state is learnt by modeling the problem as hidden semi-Markov decision processes and solving it using policy iteration based Q-P learning. Then the future maintenance time can be estimated by re-simulating the system model using the learned maintenance policy. A set of experimental studies is conducted to testify the effectiveness of the proposed methodology and to investigate the impacts of involved system parameters.Published versio