標題: | 新製程導入情境下連線式步進機之排程 Scheduling of In-Line Steppers in New Process Introduction Scenarios |
作者: | 巫木誠 WU MUH-CHERNG 國立交通大學工業工程與管理學系(所) |
關鍵字: | 排程;半導體;流線型工廠;基因演算法;承載區容量限制;scheduling;semiconductor;flowshop;port capacity constraints;genetic algorithm |
公開日期: | 2010 |
摘要: | 步進機是晶圓廠產出的瓶頸,其生產排程的研究一直很受重視。過去文獻都採「巨
觀塑模」分析,將一部步進機當成單機來排程,這種研究方法,只能應用於「高良率」
情境;若應用於「低良率」情境,會因塑模過於粗略,造成步進機產能損失而不知。有
鑑於此,本研究提出一個三年期的專題計畫,來探討步進機在「新製程導入」情境下的
排程研究。本研究擬改採用「微觀塑模」分析,亦即,將一部步進機更細部解構,看成
是一個特殊的流線型工廠,並藉此微觀模型,發展各種排程方法來提升步進機的產出率。
本計畫各年度的研究範疇規劃如下。第一年主要是研究單機排程,決策變數只有一
個維度,就是工件的排序。第二年研究範疇為多機排程,決策變數增擴為兩個維度,包
括:工件指派、工件排序。第三年研究範疇為家族式派工的多機排程,決策變數增擴為
三個維度,包括:工件指派、家族間工件排序、家族內工件排序。
各年度所擬採用之研究方法,基本上有下列四種:隨機式進化搜尋法,數學規劃法;
發展新的染色體解讀法,發展多染色體表達法。各年度將根據實證結果,逐步改良所發
展的演算法。本研究議題不僅有學術創意,也有工業實用性,研究成果應可幫助提升我
國晶圓廠的國際競爭力。 In-line steppers (simply called steppers) are the bottleneck of a semiconductor wafer fab, and their scheduling has been extensively investigated. Prior literature adopts a macro-level modeling paradigm, in which a stepper is taken as a single machine. Using such a paradigm is appropriate in a high-yield scenario, but may not be so in a low-yield scenario. In practice, low-yield scenarios are not uncommon due to frequent introduction of new processes. We thus propose a 3-year project to investigate the scheduling of in-line steppers in new process introduction (NPI) scenarios. In the project, we attempt to use a micro-level modeling paradigm, in which an in-line stepper is taken as a featured flow shop, and develop various scheduling algorithms in order to increase the productivity of in-line steppers. The research scope of each year is described below. In the 1st year, we focus on single machine scheduling, which includes only one-dimensional decision variables (job sequencing). In the 2nd year, we extend the scope to the scheduling of multiple machines—which include two-dimensional variables (job allocation and job sequencing). In the 3rd year, we further extend the scope to family-based scheduling of multiple machines—which include three-dimensional variables (job allocation, among-family sequencing, and within-family sequence). Four solution approaches will be examined: evolutionary search algorithms, mathematical programming, chromosome representation schemes, and chromosome interpretation schemes. This research project is not only unique in academic merit and has a significant effect in increasing the productivity of in-line steppers, which in turn substantially influence the ultimate performance of a wafer fab. |
官方說明文件#: | NSC99-2221-E009-110-MY3 |
URI: | http://hdl.handle.net/11536/100531 https://www.grb.gov.tw/search/planDetail?id=2109649&docId=336865 |
顯示於類別: | 研究計畫 |