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In wafer fabrication, the material cost of wafer is expensive. It is imperative to repair the defective wafers produced during the manufacturing process for reducing the cost and increasing the yield of wafer fabrication. However, repairing defective wafer will not only increase the work‐in‐process (WIP) level but the flow time of rework lots as well. In wafer fabrication, rework of wafer is only allowed in the photolithography area, where is the bottleneck of the entire wafer fab. The purpose of this paper is to develop a dispatching rule concerned with rework for photolithography area.

The research developed a load‐oriented integrated rule, Re‐Disp, to consider the lots' sequencing decision and rework consideration at the photolithography area, in wafer fabrication. Simulation test and statistical analysis have been done on a virtual wafer fabrication plant. In the simulation model, some combinations of dispatching and rework rules, which are popular in practice, have been modeled for benchmarking.

Integrated rules, Re‐Disp, is better than those combinations of dispatching rules and rework rules under statistical analysis. System will be more stable when the integrated dispatching rule is used for control of the wafer schedule.

The paper developed a new dispatching rule for wafer fabrication concerned with rework for photolithography.

This research proposes weighted grey relational analysis (WGRA) method to evaluate the performance of 325 multilevel dispatching rules in the wafer fabrication process.

The research methodology involves multilevel dispatching rule generation, simulations, WGRA and result analysis. A complete permutation of multilevel dispatching rules, including the partial orders, is generated from five basic rules. Performance measures include cycle time, move, tool idling and queue time. The simulation model and data are obtained from a wafer fab in Malaysia. Two seasons varying in customer orders and objective weights are defined. Finally, to benchmark performance and investigate the effect of varying values of coefficient, the models are compared against TOPSIS and VIKOR.

Results show that the seasons prefer different multilevel dispatching rules. In Normal season, the ideal first basic dispatching rule is critical ratio (CR) and CR followed by shortest processing time (SPT) is the best precedence pairing. In Peak season, the superiority of the rule no longer heavily relies on the first basic rule but rather depends on the combination of tiebreaker rules and on-time delivery (OTD) followed by CR is considered the best precedence pairing. Compared to VIKOR and TOPSIS, WGRA generates more stable rankings in this study. The performance of multicriteria decision-making (MCDM) methods is influenced by the data variability, as a higher variability produces a much consistent ranking.

As research implications, the application illustrates the effectiveness and practicality of the WGRA model in analyzing multilevel dispatching rules, considering the complexity of the semiconductor wafer fabrication system. The methodology is useful for researchers wishing to integrate MCDM model into multilevel dispatching rules. The limitation of the research is that the results were obtained from a simulation model. Also, the rules, criteria and weights assigned in WGRA were decided by the management. Lastly, the distinguishing coefficient is fixed at 0.5 and the effect to the ranking requires further study.

The research is the first deployment WGRA in ranking multilevel dispatching rules. Multilevel dispatching rules are rarely studied in scheduling research although studies show that the tiebreakers affect the performances of the dispatching rules. The scheduling reflects the characteristics of wafer fabrication and general job shop, such as threshold and look-ahead policies.

Constructing an effective production control policy is the most important issue in wafer fabrication factories. Most of researches focus on the input regulations of wafer fabrication. Although many of these policies have been proven to be effective for wafer fabrication manufacturing, in practical, there is a need to help operators decide which lots should be pulled in the right time and to develop a systematic way to alleviate the long queues at the bottleneck workstation. The purpose of this study is to construct a photolithography workstation dispatching rule (PADR). This dispatching rule considers several characteristics of wafer fabrication and influential factors. Then utilize the weights and threshold values to design a hierarchical priority rule. A simulation model is also constructed to demonstrate the effect of the PADR dispatching rule. The PADR performs better in throughput, yield rate, and mean cycle time than FIFO (First‐In‐First‐Out) and SPT (Shortest Process Time).

Automated guide vehicles (AGVs) are driverless vehicles that perform material handling operations in both flexible and conventional facilities. We provide here a review of recent work on the design of AGV guide paths and dispatching rules, including related issues such as idle vehicle location, and location of pickup and delivery stations. Different types of guide paths and related layouts, including optimal and heuristic approaches to the path design, are reviewed here. Dispatching rules and algorithms, including zone control, are also proposed and compared with commonly‐used rules.

Dispatching rule‐based scheduling is a kind of dynamic scheduling commonly used in real world applications. Because of the lack of scheduling objective, it cannot optimize the specific performances at which shop managers aim in the current production period. To overcome the limitations of the dispatching rule‐based scheduling, an iterative learning scheduling scheme is proposed in this paper. A scheduling objective function, which reflects the performance criteria in which the shop managers are most interested, is established and used to guide the optimization of the crucial performances. According to the value of the scheduling objective obtained from the last simulation period, the parameters are adjusted so as to decrease the objective during the next simulation period. Experimental results show that the iterative learning scheduling overcomes the limitations of the dispatching rule‐based scheduling and achieves higher performances.

The purpose of this paper is to consider the interaction among shop floor control (SFC) strategies (order review/release, dispatching, and rework strategies) and its impact on the performance of wafer fabrication. How to select a suitable set of SFC strategies in wafer fabrication is the main topic.

The paper tried to find the better combination of these strategies by specific performance indicators. A virtual wafer fab is built based on a real case in Taiwan and used for simulation test. Seven ORR rules, eight dispatching rules, and three rework rules are considered in the simulation test.

The paper finds that the performance of most ORR strategies will be improved when combined with suitable dispatching and rework strategies. But no single strategy can satisfy all performance indicators.

The performance of most ORR strategies will be improved when combined with suitable dispatching and rework strategies. No single strategy can satisfy all performance indicators. In practice, we should choose SFC strategies carefully based on the system conditions. Furthermore, ORR, dispatching, and rework strategies cannot be separately considered. Instead, they should be combined and integrated for improving the system performance.

Simulation tests and statistical analysis are done for three kinds of SFC strategies on a virtual wafer fab. The suitable combinations of SFC strategies for different performance indicators are suggested in this paper. The selection of ORR, dispatching and rework rules in wafer fabrication are discussed in the paper.

To address management issues in the development of flexible production systems in the enterprises of knowledge-intensive industries, this chapter considers four basic approaches to planning production processes. Based on these approaches, the methodology of the agent-based approach, which satisfies the fundamental requirements of today's production systems, is formulated, with much attention paid to the rules of dispatching as a key tool of operational control over the production plan and its implementation. The advantage of simulation-based approaches is that they can dynamically adjust the ongoing integration of planning, depending on the state of flexible production systems, in the use of combined approaches and methods of management of production processes.

The development of a rule‐based expert system (ES), driven by a discrete event simulation model, that performs dynamic shop scheduling is described. Based on a flowtime prediction heuristic that has been developed and base‐line runs to establish the efficacy of scheduling strategies such as shortest processing time (SPT), critical ratio, total work, etc., a rescheduling‐based dispatching strategy is investigated in a dynamic job shop environment. The results are discussed and analyzed.

Reviews a critical aspect of job shop scheduling research, namely the decision regarding release timing of orders to the manufacturing shopfloor. Covers articles specifically addressing the order release problem; the information should prove helpful for researchers employing order release policies in their research. The release decision literature is classified into three areas: descriptive studies including case and survey research, analytical or optimization‐based research, and simulations of theoretical and empirically derived job shops. Presents tables describing the release rules and summarizing the characteristics of the simulation research. Identifies a number of topics within the order release research area in need of further investigation, including the comparison of larger sets of release rules, the use of more realistic simulation models such as the dual resource constrained job shop model, the need for further empirical identification of release policies, and the use of release policies that consider dynamic shop conditions.

The definition of cycle time is the time from the wafer start to the wafer output. It usually takes one or two months to get the product since customer decides to produce it. The cycle time is a critical factor for customer satisfaction because it represents the response time to the market. Long cycle time reflects the ineffective investment for the capital. The cycle time is very important for foundry because long cycle time will cause customer unsatisfied and the order loss. Consequently, all of the foundries put lots of human source in the cycle time improvement. Usually, we make decisions based on the experience in the cycle time management. We have no mechanism or theory for cycle time management. We do work‐in‐process (WIP) management based on turn rate and standard WIP (STD WIP) set by experiences. But the experience didn’t mean the optimal solution, when the situation changed, the cycle time or the standard WIP will also be changed. The experience will not always be applicable. If we only have the experience and no mechanism, management will not be work out. After interview several foundry fab managers, all of the fab can’t reflect the situation. That is, all of them will have an impact period after product mix or utilization varied. In this study, we want to develop a formula for standard WIP and use statistical process control (SPC) concept to set WIP upper/lower limit level. When WIP exceed the limit level, it will trigger action plans to compensate WIP Profile. If WIP Profile balances, we don’t need too much WIP. So WIP level could be reduced and cycle time also could be reduced.