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	1. A Bottleneck-based dynamic scheduling algorithm for semiconductor wafer fabrication
	Cao Zhengcai,Deng Jijie
	Electrics, Communication and Autocontrol Technology 21 February 2013
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (0 B)

	Abstract:Semiconductor wafer fabrication is a very complicated manufacturing system with characteristics such as reentry of lots into machines, alternative machine with unequal capacity and shifting bottlenecks. The optimization and scheduling of semiconductor wafer fabrication has long been a hot research field. Bottleneck is the key factor to the wafer fabrication which has essential influence on the throughput rate, cycle time, time-delivery rate, etc. The scheduling policies on bottleneck machines have significant impact on cost decreasing, achieving throughput target and improving production-resource scheduling and therefore need to be optimized. In this paper, considering the characteristic information concerning bottleneck and whole production line, a rolling horizon bottleneck prediction method is proposed through predict the wait time of the lot in machines and the machine load. Then, based on the above prediction bottleneck, we proposed a novel rolling horizon dynamic bottleneck-based scheduling algorithm. The algorithm analyzes the key factors which influence the bottleneck shifting and the upstream and downstream scheduling policies of bottleneck. Applied to a simulation wafer fabrication, our proposed bottleneck prediction method and bottleneck-based scheduling algorithm improve the cycle time, machine utility apparently compared to other heuristic scheduling method
	TO cite this article:Cao Zhengcai,Deng Jijie. A Bottleneck-based dynamic scheduling algorithm for semiconductor wafer fabrication[OL].[21 February 2013] http://en.paper.edu.cn/en_releasepaper/content/4522240


	2. Efficient Reliability Dispositioning of Gross Fail Area Defects
	Sun Yanlong,Rong Guoguang
	Electrics, Communication and Autocontrol Technology 11 August 2011
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	Abstract:Various issues in semiconductor manufacturing such as equipment malfunction or process marginalities can result in specific spatial failure patterns of devices at wafer Sort, which could lead to yield or reliability issues in assembly test or with the end customer. Due to the variability and complexity of these Gross Fail Area (GFA) defects, it is difficult, and in some cases nearly impossible to automate the containment and dispositioning of wafers without severely affecting factory output. Containment of impacted material using traditional Statistical Bin Limits (SBL) and limited GFA detection screens post Sort, can often put too much material on hold, or worse, allow impacted material to escape the factory. The current dispositioning procedures are mostly manual and tedious, requiring the review by engineers of large quantities of both affected and unaffected material. The manual procedures, prone to user error, may involve risk of RSI (repetitious stress injury) from the large extent of 'click and kill' inking. In this paper we describe a new breakthrough methodology for automating the accurate screening and inking of certain GFA defects. The wafer map of the Sort bin test results is first converted into a pixel image with just the failed bins that constitute the GFA of interest. Image analysis techniques are applied to identify and extract attributes such as location, size, orientation etc. of the clusters of contiguous failed dice. These attributes are used in rules that are implemented in software to test for the existence of the specific failure patterns, resulting in highly accurate screening. Good die, known to have impaired functionality due to their being adjacent to the clusters meeting specific fail criteria, are then inked programmatically, as their location on the wafer and other descriptive information are known. The entire process is automated, requiring no human intervention.
	TO cite this article:Sun Yanlong,Rong Guoguang. Efficient Reliability Dispositioning of Gross Fail Area Defects[OL].[11 August 2011] http://en.paper.edu.cn/en_releasepaper/content/4438057

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