scholarly journals Infrared Laser Confocal Microscopy: Fast, Flexible, Cost-Effective Inspection and Metrology Tool for Microelectronic Manufacturing

2007 ◽  
Vol 15 (1) ◽  
pp. 36-37
Author(s):  
David Rideout

Microelectronics and semiconductor wafer manufacturing are among the fastest evolving technology industries today. Wafer sizes typically are 200 mm to 300 mm while critical dimensions are shrinking to 0.09 μm and smaller. As the size of discrete devices continues to be reduced while device density increases, the need for fast, accurate, flexible metrology and inspection tools in the microelectronics industry grows.Back in the early 1980's, semiconductor inspection was performed primarily by brightfield optical microscopes and with automated detection tools. The adaptation of automated detection tools led to the systematic control of increasingly smaller defects. The smallest detectable defect using these automated tools fell to below the 0.30-micron mark during the 1990's.

2003 ◽  
Vol 766 ◽  
Author(s):  
Vineet Sharma ◽  
Arief B. Suriadi ◽  
Frank Berauer ◽  
Laurie S. Mittelstadt

AbstractNormal photolithography tools have focal depth limitations and are unable to meet the expectations of high resolution photolithography on highly topographic structures. This paper shows a cost effective and promising technique of combining two different approaches to achieve critical dimensions of traces on slope pattern continuity on highly topographic structures. Electrophoretically deposited photoresist is used on 3-D structured wafers. This photoresist coating technique is fairly known in the MEMS industries to achieve uniform and conformal photoresist films on 3D surfaces. Multi step exposures are used to expose electrophoretically deposited photoresist. AlCu (Cu-0.5%), 0.47-0.53 μm thick metal film is deposited on 3D structured silicon substrate to plate photoresist. By combining these two novel methods, metal (AlCu) traces of 75 μm line width and 150 μm pitch (from top flat to down the slope) have been demonstrated on isotropically etched 350 μm deep trenches with 5-10% line width loss.


2011 ◽  
Vol 186 ◽  
pp. 36-40 ◽  
Author(s):  
Bing Hai Zhou

Photolithography area is usually a bottleneck area in a semiconductor wafer manufacturing system (SWMS). It is difficult to schedule photolithography area on real-time optimally. Here, an Elman neural network (ENN)-based dynamic scheduling method is proposed. An ENN-based sample learning algorithm is proposed for selecting best combination of scheduling rules. To illustrate the feasibility and practicality of the presented method, the simulation experiment is developed. A numerical example is use to evaluate the proposed method. Results of simulation experiments show that the proposed method is effective to schedule a complex wafer photolithography process.


2013 ◽  
Vol 10 ◽  
pp. 231-235
Author(s):  
Wai Yi Foong ◽  
Amir Hamzah bin Hassan

In semiconductor wafer manufacturing, there are only a few processes but many steps. Each wafer must go through the processes multiple times (steps) and sometimes not in the same sequence. All the wafers in lot size of 25 pieces are transferred between the processes using an Automated Guided Vehicle from stocker to stocker. Then, the wafers are manually transferred to the processing tool. Although the tools are designed per SEMI S2/S8 standards [1,, the equipment technician can get into awkward postures when performing the preventive maintenance. Both the manual material handling between the tools and awkward postures during preventive maintenance can pose an ergonomic challenge. However, some techniques can be used to minimize the impact. This paper shares the techniques which can ease ergonomic problems in semiconductor wafer manufacturing


Author(s):  
Jacus S. Nacis ◽  
Marilou R. Galang ◽  
Jason Paolo H. Labrador ◽  
Milflor S. Gonzales ◽  
Aurora Maria Francesca D. Dablo ◽  
...  

AbstractAdvances in nutritional genomics are intended to revolutionize nutrition practice. A basic understanding of nutritional genomics among nutritionist-dietitians is critical for such advancements to occur. As a precedent to the development and integration of gene-based nutrition advice, this study aimed to assess hospital-based nutritionist-dietitians’ perceptions of nutritional genomics. A total of ten focus group discussions (FGDs) with sixty-one registered nutritionist-dietitians (RNDs) from hospitals in the National Capital Region (NCR), Philippines, were conducted from October to November 2019. Data were collected using a pretested semistructured discussion guide, and thematic analysis was subsequently performed. Diverging perceptions about nutritional genomics were noted among the FGD participants. Five themes emerged relating to the enablers and barriers of gene-based nutrition advice: training and capacity building, the extent of information to be disclosed, cost, ethical considerations, and government support. Themes related to the desired features of the gene-based nutrition advice included being consent-driven, cost-effective, technology-oriented, and guided by standards. The results of this study suggest that training and continued learning will equip RNDs to provide nutrition advice based on genetic information. However, other factors, such as cost and ethical considerations, are critical dimensions that need to be acknowledged and addressed before integrating gene-based advice into nutrition practice.


2021 ◽  
Vol 8 (2) ◽  
pp. 205395172110461
Author(s):  
Bernhard Rieder ◽  
Yarden Skop

Over recent years, the stakes and complexity of online content moderation have been steadily raised, swelling from concerns about personal conflict in smaller communities to worries about effects on public life and democracy. Because of the massive growth in online expressions, automated tools based on machine learning are increasingly used to moderate speech. While ‘design-based governance’ through complex algorithmic techniques has come under intense scrutiny, critical research covering algorithmic content moderation is still rare. To add to our understanding of concrete instances of machine moderation, this article examines Perspective API, a system for the automated detection of ‘toxicity’ developed and run by the Google unit Jigsaw that can be used by websites to help moderate their forums and comment sections. The article proceeds in four steps. First, we present our methodological strategy and the empirical materials we were able to draw on, including interviews, documentation, and GitHub repositories. We then summarize our findings along five axes to identify the various threads Perspective API brings together to deliver a working product. The third section discusses two conflicting organizational logics within the project, paying attention to both critique and what can be learned from the specific case at hand. We conclude by arguing that the opposition between ‘human’ and ‘machine’ in speech moderation obscures the many ways these two come together in concrete systems, and suggest that the way forward requires proactive engagement with the design of technologies as well as the institutions they are embedded in.


Author(s):  
Azamat Abdoullaev

How reality or the world with its parts and levels might be truly symbolized and represented by emerging semantic technology and knowledge systems appears the most challenging topic in the field of top ontology and ontology engineering. Along with causality, knowing the relationship of meaning makes all the difference in true representation of the real world features, in understanding (sensing, reading, or resolving) the real meaning values of world knowledge representation and reasoning. A formal account of meaning (or significance) is becoming a decisive issue in the whole matter of the Semantic Web promising machine-based processing by means of advanced information technologies. For without understanding the nature of meaning, its critical dimensions, mechanisms, and algorithms of representation in computable forms, the whole enterprise of semantic technology is an otiose undertaking and expensive academic mystification. As far as computing ontology is viewed as a semantic model where the relationships among resources are to be identified, differentiated, or processed by automated tools [SICoP, 2005], the above meaningful topics presuppose creating the standard ontology framework. As far as the emerging Semantic Web is the universal medium for the exchange of information across users, systems, applications, and networks, the unified frame ontology is the universal semantic platform for a uniform organization of all human knowledge.


1992 ◽  
Vol 35 (1) ◽  
pp. 41-49
Author(s):  
Stephen Grotzinger ◽  
Douglas Cooper

In the control of environmental contaminants, it is often useful to sample at preselected locations to determine concentrations and their means. These locations might be on a surface, throughout a room, or outdoors. Applications include air and water pollution control, industrial hygiene, and contamination control in industry. Contamination is a major cause of yield and reliability losses in the microelectronics industry. Sampling the cleanroom environment or sampling the product surfaces can help diagnose and prevent contamination problems, but sampling is becoming increasingly expensive. One wants to use sampling resources effectively to achieve desired low levels of uncertainly. We assume that the locations to be sampled have been selected, perhaps as described by Cooper et al. We show how to calculate the optimal number of samples to be taken at each location so as to minimize the uncertainty in the mean over the entire region under study, subject to a cost constraint. We consider two distinet criteria for measuring this uncertainty. We also address the optimal allocation for minimizing the cost, subject to an upper bound on the standard error. We also discuss the differences between these approximate solutions and the true solutions, which are integers.


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